Docstoc

Assessment of Energy and Capacity Savings Potential in Iowa

Document Sample
Assessment of Energy and Capacity Savings Potential in Iowa Powered By Docstoc
					           Final Report – Volume I




           Assessment of Energy and
           Capacity Savings Potential in
           Iowa


           Prepared for the Iowa Utility Association
           February 2008
           In Collaboration with Summit Blue Consulting, Nexant, Inc., A-TEC
           Energy Corporation, and Britt/Makela Group




Iowa Utility Association – Joint Assessment Study
                                                                                             Investigators:

             Hossein Haeri, Ph.D., Scott Dimetrosky, Charles Bicknell, Collin Elliot,
                   Tina Jayaweera, Ph.D., Eli Morris, Tony Larson, Aquila Velonis,
     Allen Lee, Ph.D., Eric Flora, Ross Notebaart, Nathan Vellinga, Dan Groshans,
                                Meghan Lee, Sara Wist, Rick Ogle and Ken Seiden
                                                                    Quantec, LLC.



                 Kevin Cooney, Randy Gunn, Mary Klos, Daniel Klos, Adam Knickelbein,
                                         Beth Baker, Rachel Freeman and Roger Hill
                                                             Summit Blue Consulting



                           Terry Fry, Sam Mueller, Patrick Johanning and Angela Patnode
                                                                            Nexant, Inc.




K:\2007 Projects \2007-111 (IUA) IUA State-Wide Savings Potential\Reports and Presentations\Final Report\IUA Final
Report_010807.doc




 Quantec Offices
 720 SW Washington, Suite 400          1722 14th St., Suite 210
 Portland, OR 97205                    Boulder, CO 80302
 (503) 228-2992; (503) 228-3696 fax                              1007 fax
                                       (303) 998 -0102; (303) 998-
 www.quantecllc.com



         Printed on
         recycled paper
Table of Contents: Volume I

        Acknowledgements............................................................................................................ ix

Executive Summary .............................................................................................1
        Overview..............................................................................................................................1
        Methodology ........................................................................................................................2
        Planning Considerations ......................................................................................................8

1.      Introduction ................................................................................................1
        Project Scope and Objectives...............................................................................................1
        Definition of Resource Potentials ........................................................................................2
        General Approach to Estimating Resource Potentials .........................................................3
        Considering the Role of Uncertainty ...................................................................................4
        Organization of this Report................................................................................................10

2.      Data Collection .........................................................................................11
        Primary Data Collection ....................................................................................................11
        Utility Database Mining.....................................................................................................14
        Secondary Data ..................................................................................................................14
        Summary of Data Collection for High Priority Measures .................................................14
        Business Segment Data......................................................................................................17
        Additional Utility Data for Potential Analysis...................................................................17

3.      Energy Efficiency .....................................................................................19
        Scope of Analysis ..............................................................................................................19
        Methodology......................................................................................................................20
        Summary of Resource Potential – Electricity....................................................................21
        Summary of Resource Potential – Natural Gas .................................................................23
        Detailed Resource Potential...............................................................................................24

4.      Demand Response...................................................................................39
        Scope of Analysis ..............................................................................................................39
        Estimate Demand Response Resource Potentials ..............................................................40
        Summary of Demand Response Resource Potential..........................................................43
        Resource Costs and Supply Curves ...................................................................................44
        Resource Acquisition Schedule .........................................................................................47
        Demand Response Resource Results by Program Option .................................................47




Iowa Utility Association – Joint Assessment Study                                                                                             i
5.      Renewable Resources .............................................................................79
        Scope..................................................................................................................................79
        Methodology......................................................................................................................80
        Summary of Findings.........................................................................................................80
        Biomass Energy .................................................................................................................83
        Clean Energy......................................................................................................................88
        Passive Efficiency Resources ..........................................................................................102
        Emission Reductions........................................................................................................105




Iowa Utility Association – Joint Assessment Study                                                                                              ii
Tables and Figures


Executive Summary .........................................................................................E-1
        Table 1. Technical and Economic Electric Energy-Efficiency Potential (GWh in
        2018) by Utility................................................................................................................E-3
        Table 2. Technical and Economic Electric Energy-Efficiency Potential (GWh in
        2018) by Sector (Alliant and MidAmerican) ...................................................................E-4
        Table 3. Technical and Economic Gas Energy-Efficiency Potential (Thousand
        decatherms in 2018) by Utility ........................................................................................E-4
        Table 4. Technical and Economic Gas Energy-Efficiency Potential (Thousand
        decatherms in 2018) by Sector (Alliant, Aquila, and MidAmerican)..............................E-5
        Table 5. Alliant Energy Technical and Market Potential (MW in 2018) .......................E-5
        Table 6. MidAmerican Energy Technical and Market Potential (MW in 2018) .............E-5
        Table 7. Levelized Costs and Market Potential (MW in 2018) .......................................E-6
        Table 8. Market Potential for DG Renewable Resources (2018) ....................................E-7
        Table 9. Economic Potential for Passive Renewable Resources by Fuel (2018) ............E-7
        Figure 1. Cumulative Supply Curve for Dispersed Generation Renewable
        Resources (2018) .............................................................................................................E-7

1.      Introduction ................................................................................................1
        Figure 2. General Methodology for Assessment of Demand-Side Resource
        Potential ...............................................................................................................................4

2.      Data Collection .........................................................................................11
        Table 10. Residential Primary Data Collection Efforts .....................................................12
        Table 11. Non-Residential Primary Data Collection Efforts .............................................13
        Table 12. Summary of Data Sources for Residential Sector Measures .............................14
        Table 13. Summary of Data Sources for Non-Residential Sector Measures .....................16

3.      Energy Efficiency .....................................................................................19
        Table 14. Energy-Efficiency Measure Counts (Base-Case Scenario) ...............................19
        Table 15. Technical and Economic Electric Energy-Efficiency Potential (GWh in
        2018) by Utility..................................................................................................................21
        Table 16. Technical and Economic Electric Energy-Efficiency Potential (GWh in
        2018) by Sector (Alliant and MidAmerican) .....................................................................22
        Table 17. Technical and Economic Energy-Efficiency Potential (GWh in 2018)
        by Sector and Resource Type ............................................................................................22
        Table 18. Technical and Economic Gas Energy-Efficiency Potential (Thousand
        decatherms in 2018) by Utility ..........................................................................................23



Iowa Utility Association – Joint Assessment Study                                                                                              iii
        Table 19. Technical and Economic Gas Energy-Efficiency Potential (Thousand
        decatherms in 2018) by Sector (Alliant, Aquila, and MidAmerican)................................23
        Table 20. Technical and Economic Gas Energy-Efficiency Potential (Thousand
        decatherms in 2018) by Sector and Resource Type...........................................................24
        Table 21. Residential Sector Electric Energy-Efficiency Potential by Utility (GWh
        in 2018) ..............................................................................................................................24
        Figure 3. Residential Sector Electric Economic Potential by Segment .............................25
        Table 22. Residential Sector Electric Energy-Efficiency Potential by End Use
        (GWh in 2018) ...................................................................................................................26
        Figure 4. Residential Sector Electric Economic Potential by End Use .............................26
        Table 23. Residential Sector Gas Energy-Efficiency Potential by Utility
        (Thousand decatherms in 2018).........................................................................................27
        Figure 5. Residential Sector Gas Economic Potential by Segment ...................................28
        Table 24. Residential Sector Gas Energy-Efficiency Potential by End Use
        (Thousand decatherms in 2018).........................................................................................28
        Figure 6. Residential Sector Gas Economic Potential by Segment ...................................29
        Table 25. Commercial Sector Energy-Efficiency Potential by State (GWh in
        2018) ..................................................................................................................................29
        Figure 7. Commercial Sector Economic Potential by Segment.........................................30
        Table 26. Commercial Sector Electric Energy-Efficiency Potential by End Use
        (GWh in 2018) ...................................................................................................................30
        Figure 8. Commercial Sector Economic Potential by End Use .........................................31
        Table 27. Commercial Sector Gas Energy-Efficiency Potential by Utility
        (Thousand decatherms in 2018).........................................................................................32
        Table 28. Commercial Sector Gas Energy-Efficiency Potential by End Use
        (Thousand decatherms in 2018).........................................................................................32
        Figure 9. Commercial Sector Gas Economic Potential by End Use..................................33
        Table 29. Industrial Sector Energy-Efficiency Potential by State (GWh in 2018)............34
        Figure 10. Industrial Sector Economic Potential by Segment ...........................................34
        Table 30. Industrial Sector Electric Energy-Efficiency Potential by End Use
        (GWh in 2018) ...................................................................................................................35
        Figure 11. Industrial Sector Electric Economic Potential by End Use ..............................35
        Table 31. Industrial Sector Gas Energy-Efficiency Potential by Utility (Thousand
        decatherms in 2018)...........................................................................................................36
        Figure 12. Industrial Sector Gas Economic Potential by Segment....................................37
        Table 32. Industrial Sector Gas Energy-Efficiency Potential by End Use
        (Thousand decatherms in 2018).........................................................................................37
        Figure 13. Industrial Sector Gas Economic Potential by End Use ....................................38

4.      Demand Response...................................................................................39
        Figure 14. Schematic Overview of Demand Response Assessment Methodology ...........41



Iowa Utility Association – Joint Assessment Study                                                                                              iv
        Table 33. Alliant Energy Technical and Market Potential (MW in 2018) .......................43
        Table 34. MidAmerican Energy Technical and Market Potential (MW in 2018) .............44
        Table 35. Levelized Costs and Market Potential (MW in 2018) .......................................45
        Figure 15. Alliant Energy Territory Supply Curve (Cumulative MW in 2018) ...............46
        Figure 16. MidAmerican Energy Territory Supply Curve (Cumulative MW in
        2018) ..................................................................................................................................46
        Table 36. Residential DLC Air-Conditioning: Technical and Market Potential
        (MW in 2018) ....................................................................................................................48
        Table 37. Assumptions for DLC Residential Air-Conditioning Potential .........................50
        Table 38. DLC Air-Conditioning and Water Heating: Technical and Market
        Potential (MW in 2018) ....................................................................................................51
        Table 39. Assumptions for DLC Residential Air-Conditioning and Water Heating
        Potential .............................................................................................................................52
        Table 40. DLC Air-Conditioning: Technical and Market Potential (MW in 2018) .........53
        Table 41. Assumptions for DLC Small Commercial Air-Conditioning Potential.............54
        Table 42. DLC Large Commercial: Technical and Market Potential (MW in
        2018) ..................................................................................................................................55
        Table 43. Assumptions for DLC Large Commercial Potential..........................................56
        Table 44. Thermal Energy Storage: Technical and Market Potential (MW in
        2018) ..................................................................................................................................58
        Table 45. Assumptions for TES Potential..........................................................................59
        Table 46. Interruptible Program: Technical and Market Potential (MW in 2018) ...........61
        Table 47. Assumptions for Interruptible C&I Potential.....................................................62
        Table 48. Demand Buyback: Technical and Market Potential (MW in 2018) ..................64
        Table 49. Assumptions for DBB Potential ........................................................................65
        Table 50. Time of Use Rates: Technical and Market Potential (MW in 2018) .................67
        Table 51. Assumptions for Residential TOU Potential .....................................................68
        Table 52. Residential CPP : Technical and Market Potential (MW in 2018)...................71
        Table 53. Assumptions for Residential CPP Potential.......................................................72
        Table 54. C&I CPP: Technical and Market Potential (MW in 2018)................................73
        Table 55. Assumptions Used for C&I CPP .......................................................................74
        Table 56. RTP: Technical and Market Potential (MW in 2018)........................................76
        Table 57. Assumptions for C&I RTP ................................................................................77

5.      Renewable Resources .............................................................................79
        Table 58. Installed DG Renewable Capacity by Resource (2006) ....................................81
        Table 59. Technical Potential for DG Renewable Resources (2018) ................................81
        Table 60. Technical Potential for Passive Renewable Resources (2018)..........................82
        Table 61. Market Potential for DG Renewable Resources (2018) ....................................82
        Table 62. Economic Potential for Passive Renewable Resources by Fuel (2018) ............83


Iowa Utility Association – Joint Assessment Study                                                                                               v
        Figure 17. Cumulative Supply Curve for Dispersed Generation Renewable
        Resources (2018) ...............................................................................................................83
        Table 63. Biomass Energy Prototypical Generating Units ................................................85
        Table 64. Costs for Technologies Considered (2007 Dollars)...........................................86
        Table 65. Biomass Energy Technical Potential (GWh in 2018) by Resource
        Category.............................................................................................................................87
        Table 66. Biomass Energy Market Potential (GWh) by Sector in 2018............................88
        Table 67. Costs, Measure Life and Capacity Factor for Clean Energy Resources ............89
        Table 68. Technical Potential of Clean Energy Resources by Technology (GWh
        in 2018) ..............................................................................................................................92
        Figure 18. PV Potential Methodology ...............................................................................93
        Table 69. Potential Hydro Sites .........................................................................................96
        Table 70. Technical Potential by Technology Class (GWh in 2018) ................................96
        Figure 19. Estimated Average Annual Wind Speeds for Iowa ..........................................98
        Table 71. Clean Energy Market Potential (GWh) by Sector in 2018 ..............................100
        Figure 20. Clean Energy Average Monthly Market Potential (2018) .............................100
        Table 72. Passive Efficiency Potentials by Sector (GWh in 2018) .................................102
        Table 73. Passive Efficiency Potentials by Sector (1000 DTh in 2018)..........................103
        Table 74. Levelized Costs of Passive Efficiency Measures in Residential Sector ..........103
        Figure 21. Residential Sector Passive Renewable Resources: Economic Electric
        Potential by End Use........................................................................................................104
        Table 75. Levelized Costs of Passive Efficiency Measures in Commercial Sector ........104
        Figure 22. Commercial Sector Passive Renewable Resources: Economic Electric
        Potential by End Use........................................................................................................105
        Figure 23. Commercial Sector Passive Renewable Resources: Economic Gas
        Potential by End Use........................................................................................................105
        Table 76. Estimated Emissions Savings Potential ...........................................................106




Iowa Utility Association – Joint Assessment Study                                                                                             vi
Table of Contents: Volume II

Appendix A: Energy Efficiency Measure Descriptions

Appendix B: Customer Surveys

        B-1 Summary of Survey Results

        B-2 Survey Instruments

Appendix C: Supplemental Material – Energy Efficiency

Appendix D: Supplemental Material – Demand Response

Appendix E: Supplemental Material – Renewables

Appendix F: Building Simulations

Appendix G: Attribution of Energy Savings: An Assessment of the Net-to-Gross Ratio Issue

Appendix H: Bibliography of Specific Conservation Potentials Assessment and Best Practices
Studies

Appendix I:      Benchmarking and Best Practices Study




Iowa Utility Association – Joint Assessment Study                                          vii
Acknowledgements
This study required compilation of a large amount of data from various sources, including
several departments from Alliant, Aquila, and MidAmerican. It would be difficult to overstate
the importance of the contributions made by staff at each of the utilities, all of whom made
exceptional efforts to meet the comprehensive data requests necessary to complete this study in a
timely manner. We are especially indebted to Tom Balster, Bob Holmes, Sarah Else Harvey
Dorn, Dorothy Landt, Lisa Pucelik, Julie Blackwell, and Gilbert Nunez from Alliant Energy;
Matt Daunis and Nora Hard from Aquila; David J. McCammant, Rick Leuthauser, Judy Moore,
John O’Roake, and Richard Walker from MidAmerican Energy.

We acknowledge with gratitude the guidance and insight provide by the staff of the Iowa Office
of Consumer Advocate (OCA), including Jennifer Easler, Joe Murphy, Khosrow Khojasteh, and
other members of the OCA Team who worked closely with us and supplied valuable feedback on
our approach and methodology, ensuring that the study would meet the expectations of all
stakeholders.

We are especially grateful to Jack Clark of the Iowa Utility Association for coordinating this
large and complex effort. His hard work, attention to detail, and facilitation skills allowed us to
complete this study on time and on budget.




Iowa Utility Association – Joint Assessment Study                                                ix
Executive Summary

Overview
Quantec, LLC, in collaboration with Nexant, Inc., Summit Blue Consulting, A-TEC Energy
Corporation, and the Britt/Makela Group, was retained by the Iowa Utility Association to
conduct an assessment of technical and economic opportunities for electric and gas energy-
efficiency and renewable resources in the service territories of the Association’s three investor-
owned utility members, namely Alliant Energy Corporation (Alliant), Aquila, Inc. (Aquila), and
MidAmerican Energy Company (MidAmerican).1

Chapter 35 of the 1999 Iowa Administrative Code (199 IAC 35) sets forth the Iowa Utility Board
(IUB) rules to implement legislation enacted in 1990 and modified in 1996 requiring the Utilities
to provide energy-efficiency programs for their customers. The current rules with respect to this
assessment became effective on February 17, 1999.

The goals of this project, as specified in the request for proposals (January 31, 2007), included:
    1. Conduct primary market research to collect data on energy-efficiency measures
       including, but not limited to, current saturations and market adoption trends, and other
       key inputs for the technical assessment.
    2. Develop estimates of “technical” and “economic” potentials for electric energy-efficiency
       and peak capacity reduction, natural gas energy efficiency, and select renewable
       resources2 for all major end uses in various customer sectors (including the low-income
       segment or the residential class) by construction vintage for each of the utilities.3
    3. Investigate the implications of certain provisions of the Federal Energy Policy Act of
       2005 (EPACT), particularly raising equipment efficiency standards and implementation
       of demand response programs.
    4. Review best practices for the delivery and verification of savings from the deployment of
       technical resources identified in this study to inform future program planning design and
       evaluation, including the low-income programs.
    5. Assess the trends in new construction energy code compliance in the residential sector
       and determine the effects of non-compliance on energy savings potentials.

This study addressed each of these objectives. Specifically, the Quantec team conducted a
substantial primary data collection effort in order to provide both utility-specific and Iowa-


1
    Atmos Energy Corporation received a waiver from the Iowa Utilities Board (IUB) not to participate in the
    study.
2
    Non-renewable dispersed generation (e.g. Combined Heat & Power) was considered outside the scope of this
    study.
3
    The assessment of economic potential was added to the scope of work when the contract was awarded to the
    Quantec Team in May 2007.



Iowa Utility Association – Joint Assessment Study                                                      ES-1
specific inputs for the technical and economic potential estimates. In addition, the 2005 EPACT
provisions were incorporated into the potential estimates, as known changes in federal standards
effectively raised the baseline efficiency standards and, in some cases, lowered the potential
estimates. The best practices research included a benchmarking study to compare utility impacts
vs. spending, plus focused on the various approaches for incorporating freeridership and
spillover effects into net-to-gross estimates, with a recommendation for how these effects should
be examined in Iowa. Finally, Volume III contains the results of the code compliance study. This
stand-alone study was initiated in late 2007 in order to allow a large enough inventory of homes
that were required to meet the 2006 IECC, which was not fully enforced in Iowa until April
2007.

Methodology
This general methodology is best described as a combination “top-down/bottom-up” approach.
The top-down methodology component begins with the most current utility load forecasts,
decomposes them into their constituent customer sector, customer segment, and end-use
components. The bottom-up component considers the potential technical impacts of various
demand-side and supplemental resource technologies, measures, and practices on each end use,
which are then estimated based on engineering calculations, taking into account fuel shares,
current market saturations, technical feasibility, and costs. These unique impacts are aggregated
to produce estimates of resource potential at the end-use, customer sector, and service territory
levels. In many ways, the approach is analogous to generating two alternative load forecasts at
the end-use level (one with and one without DSM and supplemental resources) and calculating
resource potential as the difference between the two forecasts.

Separate assessments of technical and economic potential for residential, commercial, and
industrial sectors were made for each utility, split by fuel type. Within each utility’s sector-level
assessment, the study further distinguished among customer segments or facility types and their
respective applicable end uses. In total, the analysis assessed the technical and economic
potential for 304 unique electric and 152 unique gas energy-efficiency measures. These measures
are primarily composed of technologies that are currently available on the market. Within the 10-
year span of this study, it is likely new, unanticipated, measures will gain market acceptance,
changing the overall potential.

To ensure an accurate representation of the Iowa market for use in modeling the energy and
capacity savings potential, the data collection efforts included over 840 telephone and 380 on-
site surveys of residential and non-residential customers, trade allies and contractors. In addition
to the comprehensive primary data collection efforts, the study relied on other data sources,
including utility database mining, Dun and Bradstreet business segment data, and various
secondary sources such as studies conducted by other utilities and energy-efficiency agencies
around the country and third-party studies conducted by private research organizations, state and
federal agencies. Finally, the study relied on a substantial amount of utility data, including
customer counts, electric and gas sales, system hourly load shapes, sales and demand forecasts,
historical demand and efficiency achievements, and avoided costs.




Iowa Utility Association – Joint Assessment Study                                               ES-2
Summary of Results
Energy Efficiency

Table 1 and Table 2 show 2018 baseline sales (the end of the 10-year planning horizon) and
potential by utility and sector, respectively. As shown, the results of this study indicate 9,767
GWh of technically feasible electric energy-efficiency potential by 2018. Approximately
6,800 GWh of these resources are cost-effective at an average levelized per-unit cost of
3 cents/kWh. The identified economic potential amounts to 17% of forecast load in 2018 and
over 1,500 MW of peak demand reduction.

These savings are based on forecasts of future consumption absent any utility program activities.
While consumption forecasts account for the past savings each utility has acquired, the estimated
potential is inclusive of—not in addition to—current or forecasted program savings.

Technical and economic potential are a function of baseline sales, but are roughly comparable
when analyzing in percentage terms. Differences in technical potential as a percent of baseline
sales are driven by differences in the distribution of customers by segment and other utility-
specific customer characteristics. In addition to these differences, the economic potential varies
due to differences in utility avoided costs.

              Table 1. Technical and Economic Electric Energy-Efficiency Potential
                                    (GWh in 2018) by Utility
                                       Technical                Economic
                                     Potential as              Potential as   Economic    Economic      Average
               Baseline   Technical         % of    Economic          % of      as % of    Potential   Levelized
Utility          Sales     Potential    Baseline     Potential    Baseline    Technical       (MW)         Cost
Alliant          18,250        4,453         24%        3,304         18%          74%          662       $0.03
MidAmerican      21,329        5,314         25%        3,473         16%          65%          875       $0.03
Total            39,580        9,767         25%        6,777         17%          69%        1,537       $0.03


Each sector’s technical and economic potentials are given in Table 2. The residential sector
represents the largest portion of both the total technical and economic potentials at 51% and
47%, respectively. The commercial sector is the second largest contributor to the technical
potential, but because industrial improvements are highly cost-effective, it becomes the smallest
contributor to the economic potential at about 23% (Table 2).




Iowa Utility Association – Joint Assessment Study                                                          ES-3
                  Table 2. Technical and Economic Electric Energy-Efficiency Potential
                           (GWh in 2018) by Sector (Alliant and MidAmerican)
                                                 Technical                 Economic
                                               Potential as               Potential as   Economic    Economic      Average
                   Baseline         Technical         % of     Economic          % of      as % of    Potential   Levelized
 Sector              Sales           Potential    Baseline      Potential    Baseline    Technical       (MW)         Cost
 Residential             10,819            4,937         46%        3,215        30%          65%          997       $0.04
 Commercial              9,086             2,695         30%        1,563        17%          58%          270       $0.03
 Industrial              19,675            2,136         11%        1,999        10%          94%          270       $0.01
 Total                   39,580            9,767         25%        6,777        17%          69%        1,537       $0.03


 Table 3 and Table 4 show 2018 baseline sales and potential by sector and utility, respectively, for
 natural gas efficiency potential. As shown, the results of this study indicate over 40,000,000
 decatherms of technically feasible gas energy-efficiency potential by 2018, the end of the 10-
 year planning horizon. Approximately 28,500,000 decatherms of these resources are cost-
 effective at an average levelized per-unit cost of 44 cents/therm. The identified economic
 potential amount to 27% of forecast load in 2018 and over 1,500 peak day decatherms.

 As with electric potential, technical, and economic potential are a function of baseline sales, but
 they are roughly comparable across utilities when analyzing in percentage terms. Differences are
 again driven by utility customer characteristics and avoided costs.

                    Table 3. Technical and Economic Gas Energy-Efficiency Potential
                                (Thousand decatherms in 2018) by Utility
                                                                       Economic                   Economic
                                           Technical                  Potential as   Economic Potential (Peak      Average
              Baseline       Technical Potential as        Economic          % of      as % of            day     Levelized
Utility         Sales         Potential % of Baseline       Potential    Baseline    Technical  decatherms)           Cost
Alliant        27,484             10,600           39%         7,683          28%         72%           88,822        $0.45
Aquila         16,307             6,556            40%         4,842          30%         74%           58,990        $0.55
MidAm          61,704             23,497           38%         16,039         26%         68%          197,144        $0.40
Total          105,495            40,653           39%         28,564         27%         70%          344,855        $0.44


 Each sector’s technical and economic potentials are given in Table 4. As with electric potential,
 the residential sector represents the largest portion of both the total technical and economic
 potential (about 65% of each). Almost all the remaining potential lies in the commercial sector,
 with a small portion (897,000 decatherms) in industrial (Table 4).




 Iowa Utility Association – Joint Assessment Study                                                                   ES-4
                   Table 4. Technical and Economic Gas Energy-Efficiency Potential
              (Thousand decatherms in 2018) by Sector (Alliant, Aquila, and MidAmerican)
                                               Technical                     Economic                       Economic
                                             Potential as                   Potential as       Economic Potential (Peak            Average
                   Baseline       Technical         % of         Economic          % of          as % of            day           Levelized
Sector               Sales         Potential    Baseline          Potential    Baseline        Technical  decatherms)                 Cost
Residential          65,968           26,532            40%          18,654            28%            70%            248,713         $0.44
Commercial           34,475           13,224            38%            9,013           26%            68%              93,784        $0.48
Industrial             5,052             897            18%              897           18%            100%              2,459        $0.07
Total               105,495           40,653            39%          28,564            27%            70%            344,955         $0.44



  Demand Response

  Table 5 and Table 6 report estimated resource potential for all demand response resources for the
  residential, commercial, and industrial sectors for Alliant and MidAmerican. Market potential is
  highest in the industrial sector due to the interruptible program. Note, however, that the analysis
  does not account for program interactions and overlap, and thus the total technical and market
  potential estimates are provided as examples only, but are not fully attainable.

                                                Table 5. Alliant Energy
                                     Technical and Market Potential (MW in 2018)
                                                                                                                  Market
                                                                2018 Technical          2018 Market           Acceptance as
                     Sector            2018 Sector Peak
                                                                   Potential             Potential           % of 2018 Sector
                                                                                                                   Peak
              Residential                        988                     590                     71                   9%
              Commercial                         970                     602                     70                   9%
              Industrial                        1475                    1195                    262                  21%
              Total                             3434                    2388                    403                  14%
              Note: Individual results may not sum to total due to rounding.
              Note: Interactions between programs has not been taken into account.
              Note: DLC RES AC has been eliminated from these potential results to account for complete overlap with DLC RES AC
                    and water heating.

                                            Table 6. MidAmerican Energy
                                     Technical and Market Potential (MW in 2018)
                                                                                                                  Market
                                                                2018 Technical          2018 Market           Acceptance as
                     Sector            2018 Sector Peak
                                                                   Potential             Potential           % of 2018 Sector
                                                                                                                   Peak
              Residential                      1,367                   809                     97                     9%
              Commercial                         964                   388                     38                     5%
              Industrial                       1,516                   868                    159                    13%
              Total                            3,846                 2,065                    295                    10%
              Note: Individual results may not sum to total due to rounding
              Note: Interactions between programs has not been taken into account




  Iowa Utility Association – Joint Assessment Study                                                                                 ES-5
Table 7 displays the market potential and per-unit ($/kW-year) costs by the various demand
response programs examined as part of this study. The largest potential is for interruptible tariffs
and residential direct load controls. Real-time pricing and critical peak pricing (both C&I
programs) are estimated to be the least expensive options, with a levelized cost of $11/kW-year
for Alliant, while critical peak pricing and demand bidding are the least expensive options for
MidAmerican, with a levelized cost of $19/kW-year and $17/kW-year, respectively. These
results also do not account for program interactions and overlap.

                   Table 7. Levelized Costs and Market Potential (MW in 2018)
                                                 Alliant Energy               MidAmerican Energy
                Levelized Cost            Market             Levelized      Market         Levelized
                                       Potential (MW)      Cost ($/kW)   Potential (MW)   Cost ($/kW)
         Direct Load Control (DLC)
           Residential (A/C only)             48               $55            66              $56
           Residential (A/C and WH)           53               $62            72              $63
           Small Commercial (A/C)              1               $96            1               $81
           Medium to Large                     1              $119            1              $169
           Commercial
         Thermal Energy Storage                1              $135            1              $150
         (TES)
         Interruptible Tariffs               291               $45            170             $26
         Demand Bidding                       18               $14            15              $17
         TOU Rates                             7               $38            10              $87
         Critical Peak Pricing (CPP)
           Residential                        11               $95            15              $95
           C&I                                11               $11             9              $19
         Real-Time Pricing (RTP)               9               $11            ---             ---



Renewable Resources

In addition to traditional energy-efficiency resources, this report includes an analysis of two
classes of renewable resources: active (dispersed generation) and passive (energy-efficiency)
resources. Active resources, loosely defined as “dispersed generation” (DG), include energy-
based resources of biomass and three “clean generation” (non-combustion) resources: building
photovoltaics (on-site solar), small hydro, and small wind. Passive resources fall into two broad
categories: passive solar building design and renewable efficiency measures.

For DG resources, market potential represents the portion of technical potential that might
actually be installed. It should be realized that not all these resources are economic, but,
nonetheless, may be installed by customers willing to accept long payback times. For passive
efficiency measures, the economic potential is provided, as determined for other energy-
efficiency resources.

The market potential for all renewable resources is shown in Table 8 for DG renewable resources
savings and in Table 9 for passive resources. Compared to the technical potential of DG
resources, this potential is significantly less due to economic considerations, low awareness of
technologies, and other permitting or interconnection concerns (details are provided in the results



Iowa Utility Association – Joint Assessment Study                                                       ES-6
sections, below). Among the DG resources, biomass energy composes the largest percentage of
market potential (155 GWh), followed by small wind (103 GWh), and PV (25 GWh). The
percentage of technical potential economic for passive efficiency resources is 97% of electric
(453 GWh) and 88% of gas (644 thousand DTh).

                                       Table 8. Market Potential for DG Renewable Resources (2018)
                                                                                                     Percent of
                                                        Resource                  Potential (GWh)
                                                                                                      Potential
                                               Biomass Energy                            155               54%
                                               Building Photovoltaics                     25                8%
                                               Small Hydro                                 7                2%
                                               Small Wind                                103               36%
                                               Total                                     290              100%



         Table 9. Economic Potential for Passive Renewable Resources by Fuel (2018)
                                                                  Resource                                Potential
                                         Electric passive efficiency resources                               453 GWh
                                         Gas passive efficiency resources                                  643,806 Dth


Figure 1 presents the cumulative supply curve for all DG resources. Biomass Energy is broken
into potential from Industrial Biomass (direct combustion) and Anaerobic Digesters (biogas
combustion).

Figure 1. Cumulative Supply Curve for Dispersed Generation Renewable Resources (2018)

                                       $0.70
                                                                                                                   PV
                                       $0.60
              Levelized Cost ($/kWh)




                                       $0.50

                                       $0.40

                                       $0.30

                                       $0.20
                                                                                        Anaerobic                    Hydro
                                       $0.10                                            Digesters                 Wind
                                                                   Ind Biomass
                                        $-
                                                0         50,000        100,000     150,000     200,000    250,000       300,000
                                                                            Cummulative MWh




Iowa Utility Association – Joint Assessment Study                                                                                  ES-7
Planning Considerations
Resource potential studies are important means of developing reasonably reliable estimates of
the magnitude, costs, and timing of demand-side management resources and ,as such, serve as a
critical first step in a utility’s resource planning process. The results of these studies also help
guide and inform the program development process.

These studies are also complex undertakings, requiring compilation of a large amount of data
from multiple sources, and a number of pivotal assumptions about future technological trends,
market conditions, and consumer behavior. For example, the assessment of the technical
potential is inherently a static analysis and assumes “frozen” efficiencies for all baseline
technologies. Estimates of economic potentials similarly depend on assumed technology costs
and on determinants of the utility’s avoided costs, particularly for fuel prices.

Clearly, the emergence of new technologies and enhancements to existing ones will affect the
potentials for all types of demand-side management, and fluctuations in avoided costs will
directly affect the expected future value of these resources. The results of this study are also
sensitive to changes in macro-economic conditions and structural changes, such as fluctuations
in energy prices, the institution of more stringent energy codes and standards, or the imposition
of a carbon tax. The findings of this study, therefore, should be considered “indicative” rather
than “conclusive.” Inevitably, much of the data used in this study will have to be updated, and
many of its assumptions will need to be revisited periodically.

Resource potential assessment objectives differ from those of program design and product
development in that they seek to provide estimates of technically feasible and cost-effective
energy-efficiency opportunities. They are useful in understanding not only the amounts of
available opportunities, but the sectors and end uses where they might be concentrated. Yet, they
provide little information or guidance as to how and by what means the identified resource
potential might be deployed. The potential for many identified resources might be realized
through legislative action to institute efficiency codes and standards. Consumer education or
market transformation initiatives can also serve as an effective means of promoting energy
efficiency.

Finally, the scope of this study was limited to analyzing technical and economic potentials only.
Except in the case of renewables and demand response options, no attempt was made to account
for the effects of market barriers, which tend to impede the penetration of energy-efficiency
technologies and programs. Once the effects of such barriers are accounted for, amounts of
realistically achievable potential are likely to be lower than that suggested by the economic
potential.




Iowa Utility Association – Joint Assessment Study                                              ES-8
1.       Introduction

Quantec, LLC, in collaboration with Nexant, Inc., Summit Blue Consulting, A-TEC Energy
Corporation, and the Britt/Makela Group, was retained by the Iowa Utility Association to
conduct an assessment of technical and economic opportunities for electric and gas energy-
efficiency and renewable resources in the service territories of the Association’s three main
investor-owned utility members, namely Alliant Energy Corporation (Alliant), Aquila, Inc.
(Aquila), and MidAmerican Energy Company (MidAmerican).4

Chapter 35 of the 1999 Iowa Administrative Code (199 IAC 35) sets forth the Iowa Utility Board
(IUB) rules to implement legislation enacted in 1990 and modified in 1996 requiring the Utilities
to provide energy-efficiency programs for their customers. The current rules with respect to this
assessment became effective on February 17, 1999.

On September 14, 2006, the IUB Staff advised the rate-regulated utilities and interested
stakeholders that they should begin the process of initiating a new energy-efficiency plan and
should proceed to develop plans to replace their current plans that are scheduled to expire at the
end of 2008. The new plans are required to include an assessment of the potential for energy and
capacity savings in Iowa. This assessment would become the foundation on which each utility
could then develop their own tailored energy-efficiency plans that both comply with the IUB
rules and adhere to each company’s goals and objectives for this activity.

Project Scope and Objectives
Studies of demand-side management potentials are important tools for policy analysis, utility
resource planning, and program design. As such, reasonably accurate projections of actual
potentials for these resources, as well as reliable estimates of their associated costs, are critical in
guiding utilities as they design their resource acquisition programs. Demand-side management
objectives may be met through a broad range of technology- and activity-based measures,
behavior modification, and/or legislative action, such as the institution of energy-efficiency
codes and standards. Demand-side resource potential also varies depending on the utility’s load
characteristics, customer mix, local market conditions and climate.

The goals of this project, as specified in the request for proposals (January 31, 2007), included:
     1. Conduct primary market research to collect data on energy-efficiency measures
        including, but not limited to, current saturations and market adoption trends, and other
        key inputs for the technical assessment.
     2. Develop estimates of “technical” and “economic” potentials for electric energy-efficiency
        and peak capacity reduction, natural gas energy efficiency, and select renewable




4
     Atmos Energy Corporation received a waiver from the Iowa Utilities Board (IUB) not to participate in the
     study.



Iowa Utility Association – Joint Assessment Study                                                          1
        resources for all major end uses in various customer sectors (including the low-income
        segment or the residential class) by construction vintage for each of the three utilities.5
    3. Investigate the implications of certain provisions of the Federal Energy Policy Act of
       2005 (EPACT), particularly raising equipment efficiency standards and implementation
       of demand response programs.
    4. Review best practices for the delivery and verification of savings from the deployment of
       technical resources identified in this study to inform future program planning design and
       evaluation, including the low-income programs.
    5. Assess the trends in new construction energy code compliance in the residential sector
       and determine the effects of non-compliance on energy savings potentials.

This study addressed each of these objectives. Specifically, the Quantec team conducted a
substantial primary data collection effort in order to provide both utility-specific and Iowa-
specific inputs for the technical and economic potential estimates. In addition, the 2005 EPACT
provisions were incorporated into the potential estimates, as known changes in federal standards
effectively raised the baseline efficiency standards and, in some cases, lowered the potential
estimates. The best practices research primarily focused on the various approaches for
incorporating freeridership and spillover effects into net-to-gross estimates, with a
recommendation for how these effects should be examined in Iowa. Finally, the code compliance
study examined a sample of homes to assess compliance with the 2006 International Energy
Conservation Code (IECC).

Definition of Resource Potentials
Estimation of technical and economic potential in this study is based on best-practice research
methods and analytic techniques that are both standard in the utility industry and are consistent
with the requirements of Chapter 35 of the 1999 Iowa Administrative Code. Consistent with
accepted industry standards, this study’s approach distinguishes among four definitions of
resource potential widely used in utility resource planning.

Naturally occurring conservation refers to reductions in energy use that occur due to normal
market forces, such as technological change, energy prices, market transformation efforts, and
improved energy codes and standards. In this analysis, naturally occurring conservation is
accounted for in several ways. First, the potential associated with certain energy-efficiency
measures assumes a natural rate of adoption. For example, the savings associated with ENERGY
STAR® appliances account for current trends in customer adoption. Second, current codes and
standards are applied in the consumption characteristics of new construction. Finally, the
assessment accounts for the gradual increase in efficiency as older equipment in existing
buildings is retired and replaced by units meeting current standards. However, this assessment
does not forecast changes to codes and standards; rather, it treats them at a “frozen” efficiency
level.


5
    The assessment of economic potential was added to the scope of work when the contract was awarded to the
    Quantec Team in May 2007.



Iowa Utility Association – Joint Assessment Study                                                         2
Technical potential assumes that all available DSM measures and supplemental resource options
may be implemented, regardless of their costs or market barriers. For energy-efficiency
resources, technical potential further falls into two classes: discretionary (retrofit) and lost-
opportunity resources. It is important to recognize that the notion of technical potential is less
relevant to resources such as capacity-focused programs and distributed generation since most
end-use loads may be subject to interruption through load curtailment or displacement by on-site
generation from a strictly “technical” point of view.

Economic potential represents a subset of technical potential only consisting of those measures
that meet the cost effective criterion based on the societal test, as it is defined in Chapter 35 of
the 1999 Iowa Administrative Code. For each measure, the test is structured as the ratio of the
net present values of the measure’s benefits and costs. Only measures with a benefit-to-cost ratio
of 1.0 or greater are deemed cost effective. The methodology for cost-effectiveness calculations
and relevant benefit and cost elements are described in detail in Chapter 3 and Volume II,
Appendix C.

Achievable potential is defined as the portion of economic potential that might be assumed to be
reasonably achievable in the course of the planning horizon, given market barriers that may
impede customer participation in utility programs. Achievable potential can vary sharply based
on program incentive structures, marketing efforts, energy costs, customer socio-economic
characteristics, and other factors. This study did not analyze achievable potential.

General Approach to Estimating Resource Potentials
Resources analyzed in this study differ with respect to several salient attributes, such as the type
of load impact (energy or capacity), availability, reliability, and applicability to various customer
classes and customer segments (business, dwelling, or facility types). They also require
fundamentally different approaches in program design, incentive structures, and delivery
mechanisms for their deployment. Therefore, analysis of the potential for these resources
requires methods tailored to address the unique technical and market characteristics of each
resource. These methods, however, generally spring from a common conceptual framework, and
their applications to various resources rely on similar analytic methodologies.

This general methodology is best described as a combination “top-down/bottom-up” approach.
As illustrated in Figure 2, the top-down methodology component begins with the most current
utility load forecasts, decomposes them into their constituent customer sector, customer segment,
and end-use components. The bottom-up component considers the potential technical impacts of
various demand-side and supplemental resource technologies, measures, and practices on each
end use, which are then estimated based on engineering calculations, taking into account fuel
shares, current market saturations, technical feasibility, and costs. These unique impacts are
aggregated to produce estimates of resource potential at the end-use, customer sector, and service
territory levels. In many ways, the approach is analogous to generating two alternative load
forecasts at the end-use level (one with and one without DSM and supplemental resources) and
calculating resource potential as the difference between the two forecasts.




Iowa Utility Association – Joint Assessment Study                                                  3
     Figure 2. General Methodology for Assessment of Demand-Side Resource Potential



                                                         Load Forecast
                                                         Load Forecast

                     • Customer count/
                     • Sector sales
                                                          Sector Loads
                                                          Sector Loads         Calibration
                                                                               Calibration

                     • Simulation models/
                     • Secondary sources
                                                           Baseline
                                                            Baseline
                                                   End-Use Consumption (EUC)
                                                   End-Use Consumption (EUC)
                     • Measure savings
                     • Measure applicability
                     • Measure interactions
                                                      Technical Potential by
                                                      Technical Potential by
                     • Fuel shares
                                                        Measure/End-Use
                                                        Measure/End-Use
                     • Current saturations


                                                       Technical Potential
                                                       Technical Potential

                     • Measure costs
                     • Avoided costs
                     • Economic screens
                                                       Economic Potential
                                                       Economic Potential



                     • Market constraints
                     • Institutional constraints

                                                      Achievable Resource
                                                           Portfolios




Considering the Role of Uncertainty
Studies of energy-efficiency potential provide an important means of developing reliable
estimates of the magnitude, costs, and availability (timing) of these resources, and are a critical
first step in a utility’s resource planning process. The results of these studies also help inform the
utility’s work in developing energy-efficiency programs and products.

By their nature, these studies rely on large amounts of data and a number of pivotal assumptions
concerning the future in calculating technical and economic potentials. For example, the
assessment of the technical potential is inherently a static analysis and assumes “frozen”
efficiencies for all baseline technologies. Advances in technologies (e.g., the emergence of new
technologies and enhancements to existing ones) that reduce the energy intensity of electrical
equipment and appliances change the potential for various end uses. Cost-reducing innovations
and increases in demand for energy efficient products and technologies, on the other hand, can
be expected to improve the potentials for measures that do not currently meet cost-effectiveness
criteria and, at the same time, to increase the adoption of measures which do. If new energy
codes and standards for new buildings and equipment are adopted in the future, this would also
reduce estimates of technical potential as they would elevate the baseline assumptions used in
calculating technical potentials.



Iowa Utility Association – Joint Assessment Study                                                   4
Economic potentials are similarly sensitive to changes in technology costs and in determinants of
the utility’s avoided costs, particularly fuel prices.6 Clearly, fluctuations in avoided costs will
directly affect the expected future value of conservation resources. However, the direction of
these impacts depends on expectations of future movements in avoided costs. When avoided
costs rise above forecast levels, the value of conservation resources increase. Conversely, lower
future avoided costs lower the amounts of economic potential and diminish the value of
conservation investments already made.

Another consideration when analyzing the economic potential estimates is the economic analysis
is based on assumptions intended to reflect “average” or “typical” customers. This means, while
a measure might not pass the economic screen within the context of this study, there could be
instances where the measure would be cost-effective. For example, a premium central air
conditioner may not be cost-effective in an average single-family home, but, in a larger home
with more occupants, it could pass the economic screen due to higher cooling consumption.

Assumptions concerning measure life represent an additional source of uncertainty in economic
potentials. Laboratory analyses of technological performance rely on assumptions of maximum
useful measure life. It is generally accepted that physical life in the field differs from laboratory
performance. Unfortunately, measure life estimates based on laboratory results or optimum field
conditions do not account for real-life variables such as the installation, operation, and
maintenance practices employed, and the potential effects of remodeling and renovations at the
site in which the measure is installed. On the other hand, there are also cases where individual
measures and equipment might last well beyond their typical life expectancy.7

Estimates of economic potentials are also affected by future government policies, programs, and
regulations. In general, any government action that internalizes the costs of greenhouse gas
(GHG) emissions8 likely increases the avoided costs, therefore increasing the quantity of
economic potential. A 1998 study by the U.S. Energy Information Administration looking at the
effects of the Kyoto Treaty conditions estimated emissions limits to achieve the Kyoto Protocols
would lead to electricity price increases between 20% and 86%, reflecting mainly increased fuel
costs.9 Such a policy shift clearly would have profound ramifications in terms of cost-
effectiveness of energy-efficiency and renewable resources.


6
    Note projected avoided costs are developed by each utility based on their generation mix, expected fuel costs,
    and other economic considerations, and, as they are considered proprietary data, are not presented in this report.
7
    Skumatz, L. and C. Hickman, “Measure Life Study: The Effect of Commercial Building Changes on Energy
    Using Equipment.” Proceedings of ACEEE Summer Study on Energy Efficiency in Buildings, 1992, Vol.
    3:3.281-3.292.
8
    A range of approaches to reduce GHG emissions has been proposed and implemented. Most but not all
    approaches are directed at CO2 emissions specifically. The most probable approaches would be imposition of an
    emissions tax or implementation of a cap-and-trade market with specified and declining emissions limits. One
    likely effect of government efforts to reduce CO2 emissions would be to shift electricity generation to fuels or
    resources that produce less CO2 per kWh or to technologies that capture and keep the CO2 from entering the
    atmosphere.
9
    This scenario is based on carbon price peaks early in the 2008-2012 period, reaching between $67 and $348 per
    metric ton ($18 to $95 per metric ton of CO2) in 2010, then declining as energy markets adjust and more
    efficient, new technologies become available and gradually penetrate the market. See:
    http://www.eia.doe.gov/oiaf/kyoto/kyotobrf.html.



Iowa Utility Association – Joint Assessment Study                                                                   5
Adoption of renewable portfolio standard (RPS) policies, requiring electricity providers to obtain
a minimum percentage of their power from renewable energy resources by a certain date, would
also affect viability of many energy-efficiency and renewable energy programs. 10 The probable
effect of an RPS is an increase in avoided costs, which would make additional resources cost-
effective.

Tax credits for energy efficiency or renewables is another area where government policy would
affect the potentials for energy efficiency and renewables. Tax credits have been increasingly
popular as a way to promote efficiency increases. EPACT 2005 established federal tax credits for
consumers purchasing and installing specific products, such as energy-efficient windows,
insulation, doors, roofs, and heating and cooling equipment, up to $500 beginning in January
2006. EPACT 2005 also provides a credit equal to 30% of qualifying expenditures for purchase
of qualified photovoltaic systems and for solar water heating equipment. State incentives in the
form of personal and corporate tax breaks for specific energy-efficiency measures are also
becoming prevalent throughout the country.

Deployment Strategy and Timing
The objectives of resource potential assessment are different from those of program design and
product development in that they seek to provide estimates of technically feasible and cost-
effective energy-efficiency opportunities. They are also useful in understanding not only the
amounts of available opportunities, but the sectors and end uses where they might be
concentrated. Yet, they provide little information or guidance as to how and by what means the
identified resource potential might be deployed. The potential for many of the electrical
equipment or building shell measures might be realized through utility incentives or legislative
action to institute efficiency codes and standards. For example, approximately 35% of energy-
efficiency potential in the residential sector derives from lighting measures, primarily the
installation of compact fluorescent light bulbs. With the recent Energy Bill signed by President
George W. Bush on December 19, 2007, much of the identified residential lighting potential may
be realized without financial intervention by utilities.11

Energy awareness campaigns, energy education, and training programs similar to those offered
by Iowa investor-owned utilities can also serve as effective means of creating new energy saving
opportunities, increasing the adoption of available efficiency measures, or improving their
savings through more effective operation and maintenance.




10
     As of the end of 2006, 20 states plus the District of Columbia had RPS policies in place. Two additional states,
     Illinois and Vermont, had nonbinding goals for adopting renewables instead. The requirements varied from
     2.2% to 20% of the amount of electricity generated, with an average requirement around 15% within an average
     time horizon of 10 years from now. In the West, California and Nevada both have a 20% RPS requirement, and
     Washington and Montana have a requirement for 15% renewable generation.
11
     Under the measure, all light bulbs must use 25% to 30% less energy than today's products by 2012 to 2014. The
     phase-in will start with 100-watt bulbs in January 2012 and end with 40-watt bulbs in January 2014. By 2020,
     bulbs must be 70% more efficient. Note that the because the legislation was not signed until after a draft copy of
     this report had been produced the potential estimates do not account for these federal requirements.



Iowa Utility Association – Joint Assessment Study                                                                    6
The length of the planning horizon is also a major factor in the utility’s ability to deploy
identified resources. Energy-efficiency potential studies in North America have generally used a
10- or 20-year planning horizon. The shorter, 10-year planning period in this study would limit
the opportunity to capture the identified potentials associated with retrofit and normal equipment
turnover.

Market Acceptance
The economic potentials identified in this study represent energy-efficiency opportunities
expected to be technically feasible and cost-effective, according to the screening criteria
established in the Chapter 35 of the IA Administrative Rules.12 The actual levels of potentials,
which may be expected to be “achievable,” are likely to be lower than economic potentials
primarily for two reasons.

First, the application of economic screens in this study was based solely on incremental costs of
identified measures, including only direct capital and installation labor costs. It did not consider
administrative expenses associated with program development, marketing, and ongoing program
operation. Administrative costs tend to vary depending on several factors, such as fuel (gas
versus electricity), target market (customer sector), vintage (existing versus new construction),
location (urban versus rural), and program structure, primarily incentive levels. Clearly, once
these costs are explicitly accounted for, one should expect a decrease in economic potential as
certain measures would no longer meet the cost-effectiveness thresholds.

Administrative costs are also likely to vary in the future, depending on the program’s maturity.
In some cases, one might expect these costs to increase as market barriers tend to become more
difficult to surmount over time due to the “early-adopter” effect: the notion that customers with
an interest in energy efficiency tend to participate in utility programs in early years. Over time,
more intensive – and more costly – marketing efforts will be required to penetrate the market.
Second, significant market barriers exist in the new construction market, due to issues
concerning the concept of economically favorable “windows of opportunity.” That is, unlike the
retrofit market, new-construction energy-efficiency opportunities can be captured only as they
become available. This, in turn, requires greater effort by the utility to maintain on-going
relationship with the trade allies in the new construction market.

It is reasonable to expect marginal increases in marketing costs would be offset to some degree
by a decline in technology costs. In this study, however, costs for all technologies and measures
are represented in nominal value, implicitly accounting for lower future technology
improvements.




12
     Economic screening of measures in this study explicitly accounts for the effects of dual-fuel savings applicable
     to certain measures, such as insulation and weatherization. However, it does not account for other, non-energy
     benefits, such as improved comfort (in the residential sector), improved productivity (such as the effects of
     better lighting in commercial settings), or industrial process improvements. The latter benefits, however, are
     unlikely to alter the results of economic screening as the majority of measures with such benefits are already
     cost-effective solely based on their energy benefits.



Iowa Utility Association – Joint Assessment Study                                                                  7
Estimating Achievable Potential and Establishing Targets
Outside the influence of these factors on economic potential are uncertainties concerning market
acceptance of energy-efficiency measures and programs offered by utilities. Surely, levels of
cost-effective, energy-efficiency potential that is realistically achievable depends on several
factors, including customers’ willingness to participate in energy-efficiency programs (which is
partially a function of incentive levels), retail energy rates, and a host of market barriers which
have historically impeded the adoption of energy-efficiency measures and practices by
consumers.13 These barriers tend to vary depending on customer sector, local energy market
conditions, and other, hard-to-quantify factors.

Projection of achievable potential, however, poses significant analytic challenges due to
uncertainties in the factors discussed above. A review of the energy-efficiency literature,
particularly potential assessment and evaluations, indicates several approaches used to estimate
achievable potential:

     1. Benchmarking. Determination of achievable potentials may be based on either external
        or internal benchmarks. “External” benchmarks involve relying on the experiences of
        similar programs offered by other utilities. This approach provides valuable measures for
        approximating market penetration potentials. However, due to differences across various
        jurisdictions (such as customer mix, energy costs, etc.) and variations in program design
        parameters (such as intensity of marketing effort, marketing incentive structures, etc.),
        these data may not be transferable from one jurisdiction to another. “Internal”
        benchmarking, on the other hand, involves using the utility’s own past experience to
        estimate achievable potential. This method also will have to be used with caution for two
        reasons: first, past experience is not necessarily a reliable indicator of future trends (e.g.,
        programs historically run may not have been well designed or implemented); and second,
        existing programs may have indeed saturated the market to the extent that they have
        exhausted most of the expected potential.

     2. Delphi Method. This method involves surveys of experts and energy-efficiency program
        managers to obtain their professional views on what might be expected to be achievable.

     3. Customer Surveys. While benchmarking and surveys of experts might be useful
        indicators of program participation, another approach is to elicit information on
        willingness to participate directly from the utility customers.



13
     Consumers’ apparent unwillingness to invest in energy efficiency has been attributed to the existence of certain
     market barriers for energy efficiency. A rich literature exists concerning what has become known as the “market
     barriers to energy efficiency” debate. Market barriers identified in the energy-efficiency literature fall into five
     broad classes of market imperfections thought to inhibit investments in energy efficiency: (1) misplaced or split
     incentives; (2) high front costs and lack of access to financing; (3) lack of information and uncertainty
     concerning the benefits, costs, and risks of energy-efficiency investments; (4) investment decisions guided by
     convention and custom: and (5) time and “hassle” factors. For an ample discussion of these barriers, see
     William H. Golove and Joseph H. Eto, “Market Barriers to Energy Efficiency: A Critical Reappraisal of the
     Rationale for Public Policies to Promote Energy,” Lawrence Berkeley National Laboratory, University of
     California, Berkeley, California, LBL-38059, March 1996.



Iowa Utility Association – Joint Assessment Study                                                                      8
A review of recent conservation potential assessment studies in North America indicates a wide
range for achievable potentials, from 30% (New Jersey) to 75% (New England) of economic
potentials across all sectors.14 However, due to differences in methodology, underlying
assumptions (e.g., length of the planning horizon), variations in local market conditions (e.g.,
customer mix, electric rates, and historical conservation efforts), it is difficult to estimate an
“average” or “typical” figure from these studies. The calculated averages reported here should
therefore be interpreted in light of these limitations and be considered only as “indicative”
measures of what might be achievable. The available data indicate, on the whole, an estimated
average market penetration of approximately 47% across all sectors. Assuming unlimited
funding and no cost-effectiveness criteria, one study estimated a maximum penetration rate of
80%.

The Power and Conservation Council in the Pacific Northwest, a region with a history of
conservation planning that began in the late 1970s, has historically assumed that 85% percent of
economic potential are likely to be achievable. Recent data from the Council indicates that while
the region has indeed achieved significant portions of the expected economic potential since the
early 1980s, a large portion of these savings have been achieved through the implementation of
energy codes and standards, particularly in Oregon and Washington.15

More rigorous attempts have been made by several utilities to develop realistic estimates of
achievable potentials. For example, a survey of about 30 national energy-efficiency experts
conducted for Tacoma Power in 2006 found between 30% to 48% of economic potentials are
likely to be achievable across all sectors for existing buildings, assuming a 50% incentive and a
10-year planning horizon.

Arguably, many of these market barriers may be mitigated through program design features,
particularly incentive levels, marketing efforts, and delivery mechanisms. Higher incentives,
especially when they can be justified by incorporating non-energy benefits as allowed in some
jurisdictions, can help increase customers’ willingness to participate in utility-sponsored
programs. More aggressive marketing and establishing effective partnerships with local trade
allies can also improve market acceptance.

Resource potential studies are complex undertakings, requiring large amounts of technical and
market data and relying on a number of pivotal assumptions concerning the future to calculate
the technical and economic potentials. Given the length of the planning horizon and the changing
conditions in the market for energy efficiency, the results of this study will be subject to many
uncertainties. Planning is ultimately a dynamic process, reflecting changing market conditions.
Therefore, it is important to consider the findings of this study as indicative, rather than
conclusive. Inevitably, much of this study’s data will have to be updated, and many of its
underlying assumptions will need to be revisited periodically.




14
      See Appendix H for a bibliography of the referenced studies.
15
     “Achievable Savings: A Retrospective Look at the Northwest Power and Conservation Planning Assumptions,”
      Council Document 2007-7 May 2007, Northwest Power and Conservation Council.



Iowa Utility Association – Joint Assessment Study                                                          9
Organization of this Report
This report is organized in three volumes. The present document, Volume I, presents the
methodology and findings, and includes the following chapters:

     Chapter 2, ““Data Development,” provides an overview of the methods and findings from
      the comprehensive primary and secondary data collection and analysis efforts

     Chapter 3, “Energy Efficiency,” presents the technical and economic potential available
      from energy-efficiency resources

     Chapter 4, “Demand Response,” presents the technical and economic potential available
      from demand response programs

     Chapter 5, “Renewable Resources,” describes the various types of small scale renewable
      resources available and the technical and market potential of these resources

Supplemental technical information, assumptions, data, and other relevant details are presented
in Volume II as appendices. These include:

     Appendix A: Energy Efficiency Measure Descriptions

     Appendix B: Customer Surveys, including Survey Instruments and Summary of Results

     Appendix C: Supplemental Material – Energy Efficiency, including Data & Assumptions
      and Detailed Results

     Appendix D: Supplemental Material – Demand Response

     Appendix E: Supplemental Material – Renewables

     Appendix F: Simulations

     Appendix G: Attribution of Energy Savings: An Assessment of the Net-to-Gross
      Ratio Issue

     Appendix H: Bibliography of Referenced Studies

Finally, Volume III contains the results of the code compliance study. This stand-alone study
was initiated in late 2007 in order to allow a large enough inventory of homes that were required
to meet the 2006 IECC, which was not fully enforced in Iowa until April 2007.




Iowa Utility Association – Joint Assessment Study                                             10
2.      Data Collection

Primary Data Collection
The 2007 Assessment of Energy and Capacity Savings Potential data collection efforts included
a combined total of over 1,200 telephone and on-site surveys of residential and non-residential
customers, trade allies and contractors (Table 10 and Table 11). This primary research, and the
potential study overall, differed significantly from previous assessments which, to a large extent,
relied primarily on secondary data.

This approach represented a concerted effort to ensure an accurate representation of the Iowa
market for use in modeling the energy and capacity savings potential. To maximize the values of
the data collection efforts, certain measures that represent disproportionately large savings
potentials were given highest priority in the surveys. For these measures, the comprehensive
survey effort collected three metrics critical to estimating efficiency potential, including:

      Equipment saturation: The percent of customers that own specific equipment, efficient
       or standard efficiency (e.g., the percent of single-family homes with air-conditioning);

      Efficiency penetration: The percent of the installed equipment stock considered efficient
       (e.g., the percent of installed central air-conditioners that exceed SEER 13); and

      Market share: The percent of current sales of equipment that is considered efficient (e.g.,
       the percent of central air-conditioner sales in the last 12 months that exceeded SEER 13).

Primary data collection findings were validated through comparisons to available state and
regional secondary data. The findings of the data collection efforts were also presented to the
utilities, the Iowa Utility Association, the Iowa Office of Consumer Advocate, independent third-
party consultants contracted by these groups, and interested stakeholders.

The following tables present each of the residential and non-residential data collection efforts
that were undertaken, the measures investigated, the sources of the samples, stratification
methods, and the number of completed surveys. The survey instruments and the detailed
tabulations of the results for each of these efforts are presented in Volume II, Appendix B.




Iowa Utility Association – Joint Assessment Study                                               11
                                     Table 10. Residential Primary Data Collection Efforts
                                                                                                                                  Number of
Data Collection Effort        Method                 Measures                          Sources                 Stratification      Surveys/
                                                                                                                                     Visits
Residential Appliance       Telephone      Residential Appliances and       Iowa Single-Family                By Building Type   405
Saturation Survey           Survey         Household Characteristics        Homeowners, Residents of          and Utility
(RASS)                                                                      Multi-Family Buildings, Mobile/
                                                                            Manufactured Home
                                                                            Residents, and Low-Income
                                                                            Households Identified from
                                                                            Database of Utility Customers
Residential On-Site         In-Person      Residential Appliances and       Participants in RASS Agreeing     N/A                67
Validation Effort           On-Site        Household Characteristics        to Site Visits
                            Audits
Residential On-Site         In-Person      CFLs                             Iowa Single-Family                By Building Type   277
CFL Survey                  On-Site                                         Homeowners, Residents of          and Utility
                            Audits.                                         Multi-Family Buildings, Mobile/
                            Concurrent                                      Manufactured Home
                            with Utility                                    Residents, and Low-Income
                            Program                                         Households
                            Audit
Residential HVAC            Telephone      Residential Central Air          Residential HVAC Dealers and      N/A                30
Trade Ally Survey           Survey         Conditioners, Air and Ground     Installers Identified Through
                                           Source Heat Pumps, Gas           Yellow-Page Searches, Lists
                                           Furnaces, Boilers, Electric      of Participating Trade Allies
                                           Furnaces                         from Utilities, and D&B Data.
Residential Plumber         Telephone      Water Heaters (Gas/Electric,     Residential Plumbers              N/A                20
Trade Ally Survey           Survey         Tankless/Storage Tank and        Identified Through Yellow-
                                           Heat Pump Water Heaters)         Page Searches, Lists of
                                           Showerheads and Faucets          Participating Trade Allies from
                                                                            Utilities, and D&B Data.
Retailer Survey             Telephone      Thermostats, Water Heaters       Retail Stores Installers          By Utility and     73
                            Survey         (Gas, Electric, Storage and      Identified Through Yellow-        Measure Type
                                           Tankless), Clothes Washers       Page Searches, and D&B
                                           and, Refrigerators, Freezers,    Data.
                                           Dishwashers, CFLs, Room
                                           ACs, Dehumidifiers, Lighting
                                           fixtures, Ceiling fans, Attic
                                           Fans, Televisions, HDTVs,
                                           DVD Players, Set-Top
                                           Receivers, Monitors, Printers,
                                           Faucet Aerators,
                                           Showerheads, Windows,
                                           Doors
Residential Home            Telephone      Heating Equipment, Cooling       Builders Identified Through       N/A                32
Builder                     Survey         Equipment, Ducts, Water          Yellow-Page Searches, Lists
                                           Heating, Windows, Lighting,      of Participating Builders from
                                           Siding, Framing, Barriers,       Utilities, and D&B Data.
                                           Insulation, Attic Fans,
                                           Showerheads, Faucets
Total Residential Surveys                                                                                                        904




        Iowa Utility Association – Joint Assessment Study                                                                             12
                            Table 11. Non-Residential Primary Data Collection Efforts
                                                                                                                          Number of
Data Collection Effort     Method               Measures                         Sources                Stratification     Surveys/
                                                                                                                            Visits
Non-Residential End      Telephone    Heating and Cooling Systems,     Utility Provided Samples of     Customer              195
User                     Survey       Controls, Refrigeration, Water   Non-Residential Customers       Segment/Building
                                      Heating, Commercial Kitchen                                      Type
                                      Equipment, Lighting and
                                      Lighting Controls
Non-Residential End      In-Person    Heating and Cooling Systems,     Participants in Non-            Customer              40
User Site Visits         On-Site      Controls, Refrigeration, Water   Residential End User            Segment/Building
                         Audits       Heating, Commercial Kitchen      Telephone Survey Agreeing       Type
                                      Equipment, Lighting and          to Site Visits
                                      Lighting Controls
Non-Residential          Telephone    Lighting and HVAC Controls,      Builders Identified Through     N/A                   21
Builders                 Survey       Sensors, Insulation Cool         Yellow-Page Searches, Lists
                                      Roofs, Ducts, Lighting,          of Participating Builders
                                      Windows, Lighting Equipment      from Utilities, and D&B Data.
Non-Residential          Telephone    Lighting and HVAC Controls,      A&E Firms Identified            N/A                   17
Architects &             Survey       Sensors, Insulation Cool         Through Yellow-Page
Engineering Firms                     Roofs, Ducts, Lighting,          Searches, and D&B Data.
                                      Windows, Lighting Equipment
Non-Residential          Telephone    Lighting Equipment and           Lighting Vendors Identified     N/A                   12
Lighting Vendors         Survey       Controls                         Through Yellow-Page
                                                                       Searches, Lists of
                                                                       Participating Trade Allies
                                                                       from Utilities, and D&B Data.
Compressed Air           Telephone    Compressed Air Equipment,        Compressed Air Vendors          N/A                   12
Vendors                  Survey       Motors and Drives                Identified Through Yellow-
                                                                       Page Searches, Lists of
                                                                       Participating Trade Allies
                                                                       from Utilities, and D&B Data.
Mechanical               Telephone    Heating and Cooling              Mechanical Contractors          N/A                   12
Contractors              Survey       Equipment, Controls, Motors      Identified Through Yellow-
                                      and Drives                       Page Searches, Lists of
                                                                       Participating Trade Allies
                                                                       from Utilities, and D&B Data.
Refrigeration            Telephone    Refrigeration Equipment,         Refrigeration Specialists       N/A                   12
Specialists              Survey       Motors, Drives, Lighting,        Identified Through Yellow-
                                      Insulation Measures, and         Page Searches, Lists of
                                      Controls                         Participating Trade Allies
                                                                       from Utilities, and D&B Data.
Total Non-Residential Surveys                                                                                               321




       Iowa Utility Association – Joint Assessment Study                                                                    13
       Utility Database Mining
       Saturation and penetration data for HVAC and shell measures were also examined in a separate
       data collection effort. This separate effort consisted of mining utility databases of the audit
       programs. Over the current program period (2004–2008), the utilities have conducted thousands
       of audits of both residential and small non-residential customers. The program databases record
       both the recommended measures that can result in significant energy savings for the participants
       and the existing equipment stock at the time of the audit. This valuable data is significantly more
       extensive than the equivalent data collection effort that could have been conducted during the
       assessment; consequently, existing data was mined and the results incorporated into the study.

       Secondary Data
       As noted above, to limit the length of the surveys, thereby increasing participation in the surveys
       while not causing an undue burden to the utility customers, each effort was carefully designed to
       focus on high impact measures that the respective survey respondent was best suited to discuss.
       As a result, the saturations and penetrations, some lower impact measures, and specialty items
       relied more on secondary data such as findings from the national ENERGY STAR Program,
       studies conducted by other utilities and energy-efficiency agencies around the country, and third-
       party studies conducted by private research organizations, state and federal agencies.

       Summary of Data Collection for High Priority Measures
       The various data sources for each of the high priority measures are summarized in Table 12 and
       Table 13. The customer surveys provided the majority of the saturation data, and the utility audit
       data and site visits provided much of the penetration data, while the trade ally and other
       “upstream” market actor surveys provided the market share information. Secondary data was
       relied upon to fill in data gaps or verify the primary data collection findings.

                     Table 12. Summary of Data Sources for Residential Sector Measures
                                                         Primary Data                                      Secondary Data
                                End-use                   HVAC/
                     Utility   Customer                   Plumber     Appliance                   Trade       Retailer      Additional
                     Audit     Telephone   Customer      Trade Ally    Retailer   Home Builder   Assoc-       Partner       Studies /
Measure Type         Data       Surveys    Site Visits    Surveys      Survey       Survey       iations     Sales Data      Reports
HVAC Equipment
Residential
Central AC                                                                                                                
Furnaces                                                                                                                 
Geothermal/Air
Source/Add-on
Heat Pumps                                                                                                               
Programmable
Thermostats                                                                                                              
Other Heating
Clothes Washers                                                                                                             


       Iowa Utility Association – Joint Assessment Study                                                                  14
                                                         Primary Data                                      Secondary Data
                                End-use                   HVAC/
                     Utility   Customer                   Plumber     Appliance                   Trade       Retailer      Additional
                     Audit     Telephone   Customer      Trade Ally    Retailer   Home Builder   Assoc-       Partner       Studies /
Measure Type         Data       Surveys    Site Visits    Surveys      Survey       Survey       iations     Sales Data      Reports
Water Heating                                                                                                              
Clothes Dryers                                                                                                               
Building Envelope
Windows                                                                                                                     
Insulation                                                                           
Other
Refrigerators                                                                                                              
Appliances for
Demand
Response                                                                                                                    
CFLs                                                                                                                        




       Iowa Utility Association – Joint Assessment Study                                                                  15
           Table 13. Summary of Data Sources for Non-Residential Sector Measures

                                           Primary Data Sources                      Secondary Data Sources
                                  Telephone                                   Trade
                                   Survey /                                  Assoc-
                                  Site Visits                  Builders /    iations     National ES
                        Audit      with Non-        Trade        A&E        (GAMA/I        Retailer      Additional
                         Data     residential        Ally        Firm       HPA/NE Partner Sales         Studies /
    Measure Type        Mining    Customers        Surveys      Surveys        MA)          Data          Reports
  HVAC Equipment
  Central Air
  Conditioning                                                                                           
  Furnaces                                                                                              
  Geothermal/Air
  Source/Add on
  Heat Pump                                                                                             
  Boilers                                                                                                 
  Programmable
  Thermostats                                                                                             
  Building Energy
  Management
  Systems                                                                                                 
  Occupancy
  Sensors                                                                                                 
  Heat Recovery
  from Exhaust Air
  to Water Heating                                                                                        
  Other Heating
  Clothes washers                                                                          
  Water Heating                                                 
  Clothes Dryers                                                  
  Building Envelope
  Windows                                                                                                  
  Insulation                                                     
  Other
  Motors/ASDs                                                                                             
  Refrigerators                                                                                           
  Appliances for
  Demand Response
  Program                                                                                                  
  CFLs/T8
  Lighting/High Bay
  Lighting/LED
  Exit/Pulse Start
  Metal Halide                                                                                            




Iowa Utility Association – Joint Assessment Study                                                                     16
Business Segment Data
Quantec and Summit Blue Consulting, as part of the joint utility potential study, conducted a
separate task to better classify non-residential customers into specific business segments.
Although the utility customer databases contain SIC codes, the data are missing or believed to be
outdated for a substantial number of customers. The goal of this task, therefore, was to merge a
third-party source of customer firmographic information with the CSS.

To conduct this task, the study team purchased Dun & Bradstreet (D&B) firmographic data for
the entire State of Iowa. The data contained such fields as SIC, number of employees, annual
revenue, and square footage of facilities. Data were then merged with each of the utility
databases using a hierarchy approach, which started with a “hard” match for name and address
and eventually went down to a “fuzzy logic” approach, which looked for specific text strings
(e.g., bakery) in the company name to assign SIC code.

The results of this task were used to characterize the non-residential customers into different
business segments, identifying the number of customers, energy consumption, and potential for
each of these segments. Separate memos describing the details of this process were provided to
each of the utilities.

Additional Utility Data for Potential Analysis
Extensive data sets were also provided by each of the investor-owned utilities participating in
this study. These data, provided by sector where applicable, included:
            Customer counts
            Electric and gas sales (consumption)
            System hourly load shapes
            Peak demand history
            Sales and demand forecasts
            Historical demand and efficiency achievements
            Avoided costs
            Line losses

Finally, there were many more additional data sources for both the energy-efficiency, demand,
and renewable potential estimates, including measure costs and benefits. Additional sources and
data development specific to each of these tasks, therefore, are presented in the each of the
following chapters.




Iowa Utility Association – Joint Assessment Study                                             17
3.      Energy Efficiency

Scope of Analysis
The main focus in assessing energy-efficiency resources was producing reasonable estimates of
savings available in each utility’s service territory over the 10-year planning horizon to inform
the creation of the next 5-year plan. Separate assessments of technical and economic potential for
residential, commercial, and industrial sectors were made for each utility, split by fuel type.
Within each utility’s sector-level assessment, the study further distinguished among customer
segments or facility types and their respective applicable end uses. Ten residential segments
(existing and new construction for single-family, multifamily, manufactured, low income single-
family, and low-income multifamily), 24 commercial segments (12 building types within the
existing and new construction), and 32 industrial segments (16 facility types, also within existing
and new construction vintages) were analyzed.

The study includes a comprehensive set of energy-efficiency electric and natural gas measures
applicable to Iowa’s climate and customer characteristics. This list includes both measures
analyzed in the previous 5-year plan (which may be in current utility programs) and new
measures that have become commercially available over the past five years. The analysis began
by assessing the technical potential for 304 unique electric and 152 unique gas energy-efficiency
measures (Table 14).

               Table 14. Energy-Efficiency Measure Counts (Base-Case Scenario)
  Sector, Potential Type           Electric Measure Counts                    Gas Measure Counts
 Commercial
   Technical               146 unique, 3,296 permutations across   71 unique, 1,227 permutations across
                           segments                                segments
   Economic                105 unique, 1,377 permutations across   54 unique, 548 permutations across segments
                           segments
 Residential
  Technical                142 unique, 2,004 permutations across   73 unique, 777 permutations across segments
                           segments
   Economic                80 unique, 872 permutations across      44 unique, 371 permutations across segments
                           segments
 Industrial
   Technical               16 unique process improvements, 632     8 unique process improvements, 134
                           permutations across segments            permutations across segments
   Economic                16 unique process improvements, 618     8 unique process improvements, 134
                           permutations across segments            permutations across segments


Considering all permutations of these measures across all customer sectors, customer segments,
and fuels, customized data had to be compiled and analyzed for nearly 8,000 measures. For
electricity, of the 304 unique measures, 191 meet the cost-effectiveness criterion for economic
potential, while 106 out of 152 gas measures were deemed cost-effective in at least one
permutation of the above distinguishing categories. This study did not fully address all plug load



Iowa Utility Association – Joint Assessment Study                                                                19
measures, especially in the residential sector, thus underestimating the total potential in this end
use. These types of measures may more appropriately be characterized as part of a market
transformation effort pursued at the larger regional—if not national—level. A complete list of
energy-efficiency measures analyzed is provided in Volume II, Appendix C.

The remainder of this section is divided into three parts: A brief description of the methodology
for estimating technical and economic potential; summary resource potentials by fuel; and
finally, detailed sector-level results.

Methodology
The basic methodology for estimating energy-efficiency potential is consistent for all six sector-
fuel combinations:

      Develop baseline forecast: A baseline forecast is created based on end use consumption
       estimates, calibrated to each utility’s base year sales and official forecast. This provides
       accurate estimates of consumption by utility, fuel, sector, customer segment, end use, and
       year.

      Compile measure lists: All measures applicable to Iowa’s climate and customers were
       analyzed to accurately depict the potential for each utility over the 10-year planning
       horizon. When expanded by utility, fuel, customer segment, end use, and vintage, this list
       totaled nearly 8,000 measures (as discussed above).

      Estimate technical potential: An alternate forecast was created where all technically
       feasible measures were assumed to be installed. The difference between this forecast and
       the baseline represents the technical potential in each year.

      Estimate economic potential: A second alternate forecast was created where all
       technically feasible and cost-effective measures were assumed to be installed. The
       difference between this forecast and the baseline represents the technical potential in each
       year. As noted above, the application of economic screens in this study was based solely
       on incremental costs of identified measures, including only direct capital and installation
       labor costs, while benefits were derived from avoided electric and gas costs.16 Additional
       benefits, particularly those from non-energy benefits often “bundled” with energy-
       efficient products, were not considered.17

As noted above, a detailed discussion of the methodology for estimating energy-efficiency
potential is presented in Volume II, Appendix C.




16
     Measures that could result in both electric and gas savings (e.g., shell measures) were screened based on
     expected savings from both fuels (i.e., there were dual-fuel benefits from a single set of incremental costs).
17
     Note that other jurisdictions have examined these non-energy benefits and considered their influence on the
     benefit-to-cost ratios.



Iowa Utility Association – Joint Assessment Study                                                               20
Summary of Resource Potential – Electricity
Table 15 and Table 16 show 2018 baseline sales and potential by utility and sector, respectively.
As shown, the results of this study indicate 9,767 GWh of technically feasible electric energy-
efficiency potential by 2018, the end of the 10-year planning horizon. Approximately
6,800 GWh of these resources are cost-effective at an average levelized per-unit cost of
3 cents/kWh. The identified economic potential amounts to 17% of forecast load in 2018 and
over 1,500 MW of peak demand reduction.

These savings are based on forecasts of future consumption absent any utility program activities.
While consumption forecasts account for the past savings each utility has acquired, the estimated
potential is inclusive of—not in addition to—current or forecasted program savings.

As shown in Table 15, technical and economic potential are a function of baseline sales, but are
roughly comparable when analyzing in percentage terms. Differences in technical potential as a
percent of baseline sales are driven by differences in the distribution of customers by segment
and other utility-specific customer characteristics. In addition to these differences, the economic
potential varies due to differences in utility avoided costs.

            Table 15. Technical and Economic Electric Energy-Efficiency Potential
                                  (GWh in 2018) by Utility
                                       Technical                Economic
                                     Potential as              Potential as   Economic    Economic      Average
             Baseline     Technical         % of    Economic          % of      as % of    Potential   Levelized
Utility         Sales      Potential    Baseline     Potential    Baseline    Technical       (MW)         Cost
Alliant        18,250          4,453         24%        3,304         18%          74%          662       $0.03
MidAm          21,329          5,314         25%        3,473         16%          65%          875       $0.03
Total          39,580          9,767         25%        6,777         17%          69%        1,537       $0.03


Each sector’s technical and economic potentials are provided in Table 16. The residential sector
represents the largest portion of both the technical and economic potential at 51% and 47%,
respectively. The commercial sector is the second largest contributor to the technical potential,
but because industrial improvements are highly cost-effective, it becomes the smallest
contributor to the economic potential at about 23% (Table 16).




Iowa Utility Association – Joint Assessment Study                                                             21
              Table 16. Technical and Economic Electric Energy-Efficiency Potential
                       (GWh in 2018) by Sector (Alliant and MidAmerican)
                                           Technical                Economic
                                         Potential as              Potential as     Economic     Economic      Average
                Baseline      Technical         % of    Economic          % of        as % of     Potential   Levelized
Sector            Sales        Potential    Baseline     Potential    Baseline      Technical        (MW)         Cost
Residential       10,819          4,937         46%         3,215         30%            65%           997       $0.04
Commercial         9,086          2,695         30%         1,563         17%            58%           270       $0.03
Industrial        19,675          2,136         11%         1,999         10%            94%           270       $0.01
Total             39,580          9,767         25%         6,777         17%            69%          1,537      $0.03


Table 17 shows the technical and economic potential by sector and resource type, which refers to
whether the resources are discretionary or represent phased-in potential. Discretionary resources
are opportunities existing in current building stock (retrofit opportunities in existing
construction), while phased-in resources are those reliant on equipment burnout and new
construction. In all sectors, these discretionary resources represent the vast majority of both the
technical and economic electric potential. Overall, discretionary resources represent 91%
(6,154 GWh) of the economic potential.

                   Table 17. Technical and Economic Energy-Efficiency Potential
                            (GWh in 2018) by Sector and Resource Type
                                               Technical Potential            Economic Potential
                         Sector
                                          Discretionary    Phased-in     Discretionary   Phased-in
                Residential                  4,345            592           2,990               225

                Commercial                   2,479            216           1,485                78

                Industrial                   1,794            342           1,679               320

                Total                        8,618          1,150           6,154               623



The distinction between discretionary and phased-in resources becomes important in the context
of timing of resource availability and acquisition planning. Phased-in resources are timing-
driven: when a piece of equipment fails, there is an opportunity to install a high-efficiency model
in its place. If standard equipment is installed in the absence of early replacement, the high-
efficiency equipment could not be installed until the new equipment reaches the end of its
normal life cycle. The same is true for new construction, where resource acquisition
opportunities become available only when a home or building is built. On the other hand,
discretionary resources are not subject to the same timing constraints. Though program planning
is outside the scope of this study, these considerations are vital for setting accurate annual
program and portfolio goals.




Iowa Utility Association – Joint Assessment Study                                                                   22
  Summary of Resource Potential – Natural Gas
  Table 18 and Table 19 show 2018 baseline sales and potential by sector and utility, respectively.
  As shown, the results of this study indicate over 40,000,000 decatherms of technically feasible
  gas energy-efficiency potential by 2018, the end of the 10-year planning horizon. Approximately
  28,500,000 decatherms of these resources are cost-effective at an average levelized per-unit cost
  of 44 cents/therm. The identified economic potential amount to 27% of forecast load in 2018 and
  over 1,500 peak day decatherms.

  As with electric potential, technical, and economic potential are a function of baseline sales, but
  they are roughly comparable across utilities when analyzing in percentage terms. Differences are
  again driven by utility customer characteristics and avoided costs.

                    Table 18. Technical and Economic Gas Energy-Efficiency Potential
                                (Thousand decatherms in 2018) by Utility
                                                                      Economic                     Economic
                                           Technical                 Potential as     Economic Potential (Peak      Average
              Baseline       Technical Potential as       Economic          % of        as % of            day     Levelized
 Utility        Sales         Potential % of Baseline      Potential    Baseline      Technical  decatherms)           Cost
 Alliant        27,484          10,600          39%           7,683          28%           72%          88,822        $0.45
 Aquila         16,307           6,556          40%           4,842          30%           74%          58,990        $0.55
 MidAm          61,704          23,497          38%          16,039          26%           68%         197,144        $0.40
 Total         105,495          40,653          39%          28,564          27%           70%         344,855        $0.44


  Each sector’s technical and economic potentials are provided in Table 19. As with electric
  potential, the residential represents the largest portion of both the technical and economic
  potential (about 65% of each). Almost all the remaining potential lies in the commercial sector,
  with a small portion (897,000 decatherms) in industrial (Table 19).

                   Table 19. Technical and Economic Gas Energy-Efficiency Potential
              (Thousand decatherms in 2018) by Sector (Alliant, Aquila, and MidAmerican)
                                             Technical                  Economic                     Economic
                                           Potential as                Potential as     Economic Potential (Peak    Average
                 Baseline       Technical         % of      Economic          % of        as % of            day   Levelized
Sector             Sales         Potential    Baseline       Potential    Baseline      Technical  decatherms)         Cost
Residential         65,968          26,532         40%          18,654         28%           70%         248,713       $0.44
Commercial          34,475          13,224         38%           9,013         26%           68%          93,784       $0.48
Industrial           5,052               897       18%             897         18%          100%           2,459       $0.07
Total             105,495           40,653         39%          28,564         27%           70%         344,955       $0.44


  Because of the opportunities available in high-efficiency space and water heating for natural gas
  equipment, phased-in resources represent a substantially larger portion of the gas potential than




  Iowa Utility Association – Joint Assessment Study                                                                     23
the electric. As shown in Table 20, resources account for 17% of the technical and 16% of the
economic (compared to 91% of electric potential) .

                Table 20. Technical and Economic Gas Energy-Efficiency Potential
                  (Thousand decatherms in 2018) by Sector and Resource Type
                                                Technical Potential                  Economic Potential
                          Sector
                                           Discretionary    Phased-in           Discretionary   Phased-in
                Residential                  21,491               5,041            15,669           2,985

                Commercial                   11,505               1,719               7,571         1,442

                Industrial                        798               99                 798            99

                Total                        33,794               6,859            24,039           4,525




Detailed Resource Potential
Residential Sector - Electric
Residential customers in Iowa account for about one-quarter of baseline electricity retail sales.
The single-family, manufactured, multifamily, and low-income dwellings that comprise this
sector present a variety of potential savings sources, including equipment efficiency upgrades
(e.g., air conditioning, refrigerators), improvements to building shells (e.g., insulation, windows,
air sealing), and increases in lighting efficiency (e.g., compact fluorescent light bulbs, LED
interior lighting).

Based on resources included in this assessment, electric economic potential in the residential
sector is expected to be 3,215 GWh over 10 years, corresponding to a 30% reduction (32% for
Alliant and 28% for MidAmerican) of 2018 residential consumption at an average levelized cost
of 4 cents/kWh (Table 21).

Table 21. Residential Sector Electric Energy-Efficiency Potential by Utility (GWh in 2018)
                                                     Technical                        Economic
                                                   Potential as                      Potential as   Economic       Average
                        Baseline     Technical            % of            Economic          % of      as % of     Levelized
  Utility                  Sales      Potential       Baseline             Potential    Baseline    Technical         Cost
  Alliant                    4,441       2,043            46%                 1,426           32%           70%      $0.04
  MidAmerican                6,379       2,894            45%                 1,790           28%           62%      $0.04
  Total                   10,819         4,937            46%                 3,215           30%           65%      $0.04


As shown in Figure 3, single-family homes represent 74% of the total economic residential
potential, followed by low-income, multifamily, and manufactured homes. The main driver of
these results is each home type’s proportion of baseline sales, but other factors, such as heating



Iowa Utility Association – Joint Assessment Study                                                                             24
fuel sources, play an important role in determining potential. For example, multifamily homes
typically have more electric heating than other home types, which increases their relative share
of the potential. On the other hand, the lower use per customer for multifamily units serves to
decrease this potential as some measures may not be cost-effective at lower consumption levels.
A comprehensive list of the specific factors affecting the results are included in the segment-
specific data, provided in Volume II, Appendix C.

              Figure 3. Residential Sector Electric Economic Potential by Segment




             Total: 3,215 ,35 8 M W h

                                 S ingle Fam ily
                                      7 4%




                                                                                    O ther
                                                                                    9%

                                                                 Low Incom e
                                                                    17 %


           No te: "Oth er" inc lu des:
           M u lti-fam ily: 5 .3 % , M an u fac tu red : 3 .9%




The largest portion (35%) of economic potential by end use (Figure 4) in the residential sector
comes from lighting measures, specifically compact fluorescent lighting.18 Air conditioning
(central and room) accounts for the next largest slice (27%), followed by HVAC auxiliary
(ventilation), and space heating. The remaining potential is in refrigerators, freezers, water
heating, plug load, and other appliances (see Table 22).




18
     As noted earlier, the current energy bill (signed in December 2007) includes a provision that, by 2012 to 2014,
     all light bulbs must use 25% to 30% less energy than today's products. Note that because the legislation was not
     signed until after a draft copy of this report had been produced, potential estimates do not account for these
     federal requirements.



Iowa Utility Association – Joint Assessment Study                                                                 25
            Table 22. Residential Sector Electric Energy-Efficiency Potential by End Use
                                           (GWh in 2018)
 End Use                                                     Baseline Sales        Technical Potential     Economic Potential
 Central AC                                                            1,451                     1,141                   796
 Central Heat                                                            428                      159                    114
 Cooking Oven                                                            316                          34                   0
 Cooking Range                                                           362                      120                      0
 Dryer                                                                   537                          16                   0
 Freezer                                                                 333                      254                    251
 HVAC Auxiliary                                                          657                      426                    257
 Heat Pump                                                               226                      127                     94
 Lighting                                                              1,947                     1,658                 1,140
 Plug Load                                                             2,756                      208                     81
 Pool Pump                                                                 19                         14                   9
 Refrigerator                                                            643                      298                    218
 Room AC                                                                 188                          97                  61
 Room Heat                                                               303                      177                    152
 Water Heat                                                              654                      209                     43
 Total                                                                10,819                     4,937                 3,215

                 Figure 4. Residential Sector Electric Economic Potential by End Use




                Total: 3,215 ,35 8 M W h

                                                                                Lighting
                                                                                  35%

                           C ooling
                              27 %
                                                                                               O ther
                                                                                               7%
                                                                                           H eating
                                                                                           8%
                                               A ppliances          H V A C A ux iliary
                                                  15%                      8%


              No te: "Oth er" inc lu des:
              Heat P u m p : 2 .9 % , P lu g L oads: 2.5 % , W ater H eatin g: 1.3 %




Iowa Utility Association – Joint Assessment Study                                                                           26
Additional details regarding the savings associated with specific measures assessed within each
end use are provided in Volume II, Appendix C.

Residential Sector – Natural Gas
Based on resources included in this assessment, gas economic potential in the residential sector
is expected to be about 18,600,000 decatherms over 10 years, corresponding to a 28% reduction
(30% for Alliant, 31% for Aquila, and 27% for MidAmerican) of 2018 residential consumption
at an average levelized cost of 44 cents/therm (Table 23).

     Table 23. Residential Sector Gas Energy-Efficiency Potential by Utility (Thousand
                                   decatherms in 2018)
                                                Technical                Economic
                                              Potential as              Potential as   Economic     Average
                      Baseline     Technical         % of    Economic          % of      as % of   Levelized
     Utility            Sales       Potential    Baseline     Potential    Baseline    Technical       Cost
     Alliant            14,738         6,230         42%         4,411         30%          71%       $0.44
     Aquila              9,350         3,875         41%         2,889         31%          75%       $0.56
     MidAmerican        41,880        16,427         39%        11,354         27%          69%       $0.41
     Total              65,968        26,532         40%        18,654         28%          70%       $0.44


As shown in Figure 5, single-family homes represent 72% of the total economic residential
potential, followed by low-income, multifamily, and manufactured homes. These results are
extremely similar to the electric potential, with manufactured homes representing a smaller
percentage due to lower saturations of gas heating equipment.




Iowa Utility Association – Joint Assessment Study                                                              27
                    Figure 5. Residential Sector Gas Economic Potential by Segment




      Total: 18 ,65 4,0 0 1 dec ath erm s

                                    S ingle Fam ily
                                         7 2%




                                                                                           O ther
                                                                                           9%

                                                                        Low Incom e
                                                                           19%


              No te: "Oth er" inc lu des:
              M an u fac tu red : 4.5 % , M u lti-fam ily: 4.0 %




Because there are far fewer gas-fired end uses than electric, the potential is mainly confined to
space (94%) and water heating (6%). A small amount of economic potential exists in gas dryers
(Table 24 and Figure 6).

    Table 24. Residential Sector Gas Energy-Efficiency Potential by End Use (Thousand
                                    decatherms in 2018)
      End Use                                    Baseline Sales      Technical Potential            Economic Potential
      Central Heat - Boiler                                 2,620                   978                           773
      Central Heat - Furnace                               47,185                21,459                         16,701
      Cooking - Oven                                           625                   68                              0
      Cooking - Range                                          766                     0                             0
      Dryer                                                    659                   19                              3
      Other                                                 3,584                      0                             0
      Pool Heat                                                146                   12                              0
      Water Heat                                           10,382                 3,997                          1,177
      Total                                                65,968                26,532                         18,654




Iowa Utility Association – Joint Assessment Study                                                                        28
                  Figure 6. Residential Sector Gas Economic Potential by Segment




          Total: 18 ,65 4,0 0 1 dec ath erm s




                   H eating
                      94%
                                                                             W ater H eating
                                                                             6%




Commercial Sector - Electricity
Based on resources included in this assessment, electric economic potential in the commercial
sector is expected to be just over 1,500 GWh over 10 years, corresponding to a 17% reduction
(19% for Alliant and 15% for MidAmerican) of forecasted 2018 commercial consumption at an
average levelized cost of 3 cents/kWh (Table 25). The composition of the commercial sector
varies more than the residential sector in terms of percent of customers and sales by segment,
which partially accounts for the difference in technical and economic potential as a percent of
2018 sales.

          Table 25. Commercial Sector Energy-Efficiency Potential by State (GWh in 2018)
                                                                          Economic
                                                    Technical              Potential Economic Average
                   Baseline       Technical     Potential as % Economic     as % of    as % of Levelized
Utility              Sales         Potential      of Baseline Potential    Baseline Technical      Cost
Alliant                4,940           1,454             29%        924        19%        64%      $0.03
MidAmerican            4,146           1,240             30%        638        15%        51%      $0.02
Total                  9,086           2,695             30%      1,563        17%        58%      $0.03


As shown in Figure 7, miscellaneous buildings and offices represent the largest shares (22% and
20%, respectively) of economic potential in the commercial sector. The miscellaneous segment
is a combination of customers that do not fit into one of the other categories (e.g., agriculture)



Iowa Utility Association – Joint Assessment Study                                                    29
and those that would, but did not have enough information to be classified. Considerable savings
opportunities are also expected in the commercial sector’s warehouse (14%), grocery (11%), and
retail (10%) segments. Moderate savings amounts are expected to be available in education,
health, restaurants, and lodging facilities.

                      Figure 7. Commercial Sector Economic Potential by Segment



               Total: 1,5 62,5 68 M W h

                                                  O ffice
                                                  20%                               M iscellaneous
                                                                                    22%
                     W arehouse
                           14%
                                                                                     O ther
                                                                                     7%
                                    R etail                                       H ealth
                                     10%                                          8%
                                                        Grocery   E ducation
                                                         11%         9%


              No te: "Oth er" inc lu des:
              R estau rant: 3 .5% , Lo dg in g: 3.1 %




As in the residential sector, lighting efficiency represents by far the largest portion of economic
potential in the commercial sector (65%), followed by HVAC auxiliary (8%), cooling (6%), and
refrigeration (6%), as shown in Table 26 and Figure 8. The large lighting potential includes both
bringing existing buildings to code and exceeding code in new and existing structures.

        Table 26. Commercial Sector Electric Energy-Efficiency Potential by End Use
                                     (GWh in 2018)
      End Use                                 Baseline Sales       Technical Potential        Economic Potential
      Cooking                                               88                       3                         0
      Cooling - Chillers                                    244                   114                         43
      Cooling - DX                                          838                   394                         43
      Dryer                                                 274                      0                         0
      Exterior Lighting                                     90                       0                         0
      HVAC Auxiliary                                      1,083                   375                       124




Iowa Utility Association – Joint Assessment Study                                                                  30
      End Use                          Baseline Sales     Technical Potential   Economic Potential
      Heat Pump                                     507                  202                    74
      Lighting                                  3,729                  1,189                 1,017
      Other                                         18                      0                    0
      Plug Load                                 1,190                     82                    77
      Refrigeration                                 511                  149                    91
      Space Heat                                    402                  149                    69
      Water Heat                                    109                   37                    24
      Total                                     9,086                  2,695                 1,563



                      Figure 8. Commercial Sector Economic Potential by End Use




Commercial Sector – Natural Gas
The commercial sector represents about a third of both technical and economic gas energy-
efficiency potential. The 9,000,000 decatherms of economic potential over 10 years, corresponds
to a 26% reduction (28% for Alliant and Aquila and 24% for MidAmerican) of forecasted 2018
commercial consumption at an average levelized cost of 48 cents/therm
(Table 27).




Iowa Utility Association – Joint Assessment Study                                                    31
        Table 27. Commercial Sector Gas Energy-Efficiency Potential by Utility (Thousand
                                     decatherms in 2018)
                                            Technical
                                          Potential as                                             Economic      Average
                       Baseline Technical        % of    Economic Economic Potential as %            as % of    Levelized
Utility                   Sales Potential    Baseline     Potential           of Baseline          Technical        Cost
Alliant                  10,007     3,892         39%        2,794                         28%          72%            $0.54
Aquila                    6,733     2,639         39%        1,911                         28%          72%            $0.54
MidAmerican              17,735     6,693         38%        4,308                         24%          64%            $0.41
Total                    34,475    13,224         38%        9,013                         26%          68%            $0.48


As in the residential sector, there are far fewer gas-fired end uses than electric. Both the technical
and economic potential are almost entirely heating (96% of the economic potential). Small
amounts of potential exist for water heating, cooking, and pool heating (Table 28 and Figure 9).

                  Table 28. Commercial Sector Gas Energy-Efficiency Potential by End Use
                                     (Thousand decatherms in 2018)
          End Use                                Baseline Sales      Technical Potential         Economic Potential
          Cooking                                         1,688                     178                         164
          Dryer                                            132                        0                           0
          Other                                             28                        0                           0
          Pool Heat                                         35                        5                           5
          Space Heat - Boiler                             9,358                   5,199                        3,724
          Space Heat - Furnace                           20,710                   7,430                        4,917
          Space Heat - Other                              1,747                       0                           0
          Water Heat                                       777                      411                         201
          Total                                          34,475                  13,224                        9,013




Iowa Utility Association – Joint Assessment Study                                                                        32
                 Figure 9. Commercial Sector Gas Economic Potential by End Use




        Total: 9 ,0 12,618 dec ath erm s
                                                     H eating
                                                       55%




                                                                                        O ther
                                                                                        4%


                                                         Boiler
                                                         41%


            No te: "Oth er" inc lu des:
            W ater Heating : 2 .2 % , Co ok in g: 1.8%




Industrial Sector - Electricity
Technical and economic energy-efficiency potential were estimated for major end uses within
16 major industrial sectors.19 Across all industries, economic potential totals approximately
2,000 GWh over 10 years, corresponding to a 10% reduction (11% for Alliant and 10% for
MidAmerican) of forecasted 2018 industrial consumption at an average levelized cost of
1 cent/kWh (Table 29). Note that in the industrial sector, most of the technical potential is
economic. Because of tight cost margins in the industrial sector, available measure data focuses
on technologies that are currently cost-effective. As such, the universe of available measures
examined is less than for the other sectors, possibly influencing the technical potential
downward. Furthermore, the industrial potential estimates relied largely on energy audits that
primarily examined individual measures and not on a systems approach; thus the actual
economic potential is likely higher than that presented in this report. For a more complete
description of the methodology used, please see Volume II, Appendix C-1.




19
     Industries analyzed varied by utility, based on customer and sales distributions



Iowa Utility Association – Joint Assessment Study                                                33
 Table 29. Industrial Sector Energy-Efficiency Potential by State (GWh in 2018)
                                                                                Economic
                                                       Technical               Potential as   Economic     Average
              Baseline                          Potential as % of   Economic          % of      as % of   Levelized
Utility          Sales      Technical Potential         Baseline     Potential    Baseline    Technical       Cost
Alliant          8,870                     956               11%          954         11%         100%        $0.01
MidAmerican     10,805                    1,180              11%        1,045         10%          89%        $0.01
Total           19,675                    2,136              11%        1,999         10%          94%        $0.01


 In examining these aggregate results for the industrial sector, there should be some caution in
 associating summary potential information for a particular facility type to individual utilities.
 While all residential and commercial customer segments were present for each utility, some of
 the facility types shows in Figure 10 applied to only one utility. For example, the electronics
 industry in MidAmerican’s service territory was not large enough to be modeled.

                    Figure 10. Industrial Sector Economic Potential by Segment




 The majority of electric economic potential in the industrial sector (70%) are attributable to
 efficiency gains in process efficiency (heating, cooling, compressed air, etc.), followed by
 HVAC improvements (14%) and motor system improvements (mainly fans and pumps). A small
 amount of additional potential exists for lighting and other facility improvements (Table 30 and
 Figure 11).




 Iowa Utility Association – Joint Assessment Study                                                             34
Table 30. Industrial Sector Electric Energy-Efficiency Potential by End Use (GWh in 2018)
         End Use                                Baseline Sales   Technical Potential Economic Potential
         Fans                                           1,180                    60                 52
         HVAC                                           1,621                   287                270
         Indirect Boiler                                  146                     6                   6
         Lighting                                       1,269                    99                 99
         Motors - Other                                 4,019                   202                172
         Other                                            896                    85                 85
         Process – Air Compressors                      1,252                   278                271
         Process - Cooling                              1,674                   224                224
         Process - Electro-Chemical                     2,089                     0                   0
         Process - Heating                              2,598                   620                557
         Process - Other                                   85                    14                 12
         Process - Refrigeration                        1,004                   168                167
         Pumps                                          1,843                    93                 84
         Total                                         19,675                  2,136              1,999



                 Figure 11. Industrial Sector Electric Economic Potential by End Use




            Total: 1,9 9 9 ,164 M W h

                                      Process
                                       7 0%




                                                                                  O ther
                                                                                  9%
                                                                     M otors
                                                         HVAC          7%
                                                         14%


           No te: "Oth er" inc lu des:
           Ligh ting : 4.9 % , Oth er: 4.3 %




Iowa Utility Association – Joint Assessment Study                                                         35
Industrial Sector – Natural Gas
Most industrial processes and end uses use electricity, and, therefore, the industrial sector
represents an extremely small portion of natural gas baseline sales and potential. Across all
industries, economic potential totals approximately 900,000 decatherms over 10 years,
corresponding to an 18% reduction (17% for Alliant, 19% for Aquila, and 18% for
MidAmerican) of forecasted 2018 industrial consumption at an average levelized cost of
8 cents/therm (Table 31).

          Table 31. Industrial Sector Gas Energy-Efficiency Potential by Utility (Thousand
                                        decatherms in 2018)
                                      Technical                 Economic
                                    Potential as               Potential as   Economic
                 Baseline Technical        % of     Economic          % of      as % of
Utility             Sales Potential    Baseline      Potential    Baseline    Technical   Average Levelized Cost
Alliant             2,740       478           17%         478         17%         100%                     $0.06
Aquila               224         42           19%          42         19%         100%                     $0.07
MidAmerican         2,088       377           18%         377         18%         100%                     $0.08
Total               5,052       897           18%         897         18%         100%                     $0.07


Due to the nature of industries using natural gas in Iowa, over 75% of the economic potential lies
in chemical manufacturing (40%) and food processing (38%). As Figure 12 shows, there are also
substantial savings opportunities in minerals (7%) and machinery (6%, ).




Iowa Utility Association – Joint Assessment Study                                                            36
                   Figure 12. Industrial Sector Gas Economic Potential by Segment




        Total: 8 9 7,38 1 dec ath erm s
                                                                        C hem icals
                                                                           40%




                                                                                               O ther
                                                                                               8%
                                 Food                                                      M achinery
                                 38%                                                       6%
                                                                           M inerals
                                                                              7%


           No te: "Oth er" inc lu des:
           M etals: 3 .4% , M isc ellan eo u s: 1.6 % , P ap er: 1.1% , P rin ting : 1 .1 % , T ran spo rtation : 1 .0%




Almost all (85%) of baseline consumption is in boilers and process heating, thus these end uses
account for almost 90% of the economic potential. The remaining potentials are in HVAC
improvements and other (non-heating) process improvements (Table 32 and Figure 13).)

            Table 32. Industrial Sector Gas Energy-Efficiency Potential by End Use
                                (Thousand decatherms in 2018)
           End Use                               Baseline Sales      Technical Potential            Economic Potential
           HVAC                                               364                        89                               89
           Indirect Boiler                                  2,406                      195                            195
           Other                                               91                         0                               0
           Process - Heat                                   1,960                      603                            603
           Process - Other                                    231                        11                               11
           Total                                            5,052                      897                            897




Iowa Utility Association – Joint Assessment Study                                                                              37
                 Figure 13. Industrial Sector Gas Economic Potential by End Use



        T ota l: 8 9 7 ,3 8 1 d e c a th e rm s

                                    P rocess
                                      6 8%




                                                                   HVAC
                                                                   1 0%

                                                    Boiler
                                                    22 %




Iowa Utility Association – Joint Assessment Study                                 38
4.      Demand Response

Scope of Analysis
Demand response (DR) or load reduction programs focused on reducing a utility’s capacity
needs are comprised of flexible, price-responsive loads, which may be curtailed or interrupted
during system emergencies or when wholesale market prices exceed the utility’s supply cost.
These programs are designed to help reduce peak demand, promote improved system reliability,
and, in some cases, may lead to the deferment of investments in delivery and generation
infrastructure. Objectives of DR may be met through a broad range of price-based (e.g., time-
varying rates and interruptible tariffs) or incentive-based (e.g., direct load control) strategies. In
this assessment, the following demand-response strategies were analyzed:
     1. Direct Load Control (DLC) programs allow a utility to remotely interrupt or cycle
        electrical equipment and appliances at a customer’s facility. In this study, the assessment
        of DLC program potential is analyzed for central electric cooling programs (including
        heat pumps) and for central cooling and electric water heating combination programs.
        Each of these programs are modeled for residential and small commercial customers
        separately. Large commercial customer DLC is also modeled, which, using integration
        with existing energy management systems (EMS), have additional controls on lighting,
        HVAC, and plug loads.
     2. Thermal Energy Storage (TES) programs are designed to reduce demand associated with
        cooling during on-peak periods through load-shifting. For most common TES
        applications, ice is made during off-peak periods (unoccupied times at night) using the
        existing cooling system. This ice is saved and used to cool the building during peak
        demand periods, which mitigates customer high demand and energy charges during on-
        peak periods. This program is often targeted at large commercial customers with rooftop
        cooling units.
     3. Interruptible Tariffs refer to contractual arrangements between the utility and its
        customers who agree to curtail or interrupt their loads in whole or part for a
        predetermined period when requested. In most cases, mandatory participation is required
        once the customer enrolls in the program; however, these programs may include
        provisions for customers to exercise an economic buy-through of a curtailment event.
        Incentives are paid regardless of the quantity of events called each year (less any
        penalties associated with an event buy-through). This analysis assumes such programs
        target commercial and industrial (C&I) customers with average monthly loads greater
        than 200 kW.
     4. Demand-Bidding or Demand Buy-Back programs offer payments to customers for
        voluntarily reducing their demand when requested by the utility. The buyback amount
        generally depends on market prices published by the utility ahead of the event, coupled
        with the customer’s ability to curtail use during the hours load curtailment is requested.
        The reduction level achieved is verified using an agreed-upon baseline usage level
        specific to the participating customer. As with interruptible tariffs, this analysis assumes
        such programs target C&I customers with loads greater than 200 kW.



Iowa Utility Association – Joint Assessment Study                                                  39
     5. Time-of-Use (TOU) programs are generally based on two- or three-tiered time-
        differentiated tariff structures that charge fixed prices for usage during different blocks of
        time (typically on- and off-peak prices by season). TOU rates are designed to more
        closely reflect the marginal cost of generating and delivering power. This study analyzes
        the potential for TOU rates only for the residential sector; C&I TOU rates are typically
        considered a standard tariff and not a capacity-focused program option.
     6. Critical Peak Pricing (CPP) or extreme-day pricing refers to programs aiming to reduce
        system demand by encouraging customers to reduce their loads for a limited number of
        hours during the year. During such events, customers have the option of curtailing their
        usage or paying substantially higher-than-standard retail rates. CPP programs integrate a
        pricing structure similar to TOU with the distinction of more extreme pricing signals for
        the critical events. For residential and small commercial sectors, it is assumed enabling
        technology is installed (such as smart thermostats); for larger commercial customers
        (greater than 30kW), interval meters would be installed.
     7. Real-Time Pricing (RTP) is a tariff structure for customers to pay electric rates tied to
        market prices. The prices are typically posted by the utility based on day-ahead hourly
        prices. RTP price structures are most suitable for large C&I customers with flexible
        schedules which may be adjusted on short notice. This analysis assumes an RTP tariff
        would target large C&I customers (greater than 200 kW). Since MidAmerican does not
        have the infrastructure to give customers a day’s notice for the price structure, this
        program is only run for Alliant.

Program options listed above are based on a thorough review of literature, cataloging and
classifying DR strategies offered by utilities and regional transmission organizations across the
country. For each program offering, data were collected on the offerings’ main features, such as
objectives, program periods, eligibility criteria, curtailment event triggers, incentive structures,
and technology requirements. These program options are described in more detail later in this
section.

Estimate Demand Response Resource Potentials
The Quantec Team’s methodology for estimating DR potentials is based on a combined “top-
down/bottom-up” approach. Quantec’s DRPro® Model provided the basic framework for this
analysis. As shown schematically in Figure 14, the approach begins with the utility system loads
and disaggregates them into sector, segment, and applicable end uses. For each DR program (or
program component), potential technical impacts are then calculated for all applicable end uses.
The end-use load impacts are then aggregated to obtain estimates of technical potentials. Market
factors such as probabilities of program and event participation are then applied to technical
potentials to obtain estimates of market potentials. The methodology for calculating technical
and market potential are described in greater detail below.20




20
     Note the study does not examine changes in energy use that may occur from demand response programs. Some
     programs are expected to reduce energy use, while others may primarily lead to load shifting.



Iowa Utility Association – Joint Assessment Study                                                         40
       Figure 14. Schematic Overview of Demand Response Assessment Methodology




Estimating Demand Response Technical Potential
DR technical potentials are first estimated at the end-use level, then aggregated to market
segment, sector, and system levels. This approach was implemented in four steps, as follows.
    1. Define customer sectors, market segments, and applicable end uses. The first step in the
       process involved defining appropriate sectors, market segments, and end uses within each
       segment for each utility. The Quantec team used the following classification scheme for
       demand response:
        o Customer classes/sectors: residential, commercial, and industrial.
        o Market segments:
          a. Residential: single-family, low-income single-family, multifamily, low-income
             multifamily, and manufactured homes.
          b. Commercial: education, grocery, health, lodging, large offices, small offices,
             restaurants, large retail, small retail, warehouses, and other commercial.
          c. Industrial: food manufacturing, primary metal manufacturing, paper
             manufacturing, plastics rubber manufacturing, chemical manufacturing,
             instruments, nonmetallic mineral products, industrial machinery, fabricated metal
             products, printing related support, transportation equipment manufacturing,



Iowa Utility Association – Joint Assessment Study                                           41
               electronic equipment manufacturing, lumber wood manufacturing, furniture
               manufacturing, and miscellaneous manufacturing.
       o Large accounts: the largest C&I customers are researched for each utility and unique
           segments are created as necessary to appropriately account for their characteristics.
       o End uses: cooling, water-heating, lighting, plug loads, process (industrial), pumping
           (agriculture), etc.
    2. Screen customer segments and end uses for eligibility. This step involved screening end
       uses for applicability of specific DR strategies. For example, hot water loads in hospitals
       or cooking loads in restaurants were excluded (if no backup generation is available).
    3. Compile utility-specific sector/end-use loads. Reliable estimates of DR potential depend
       on the correct characterization of sector and end-use loads. Load profiles were developed
       for each end use within various market segments of each utility. Contributions to system
       peak for each end use were estimated based on end-use load shapes for each utility
       jurisdiction.
    4. Estimate technical potential. Technical potential for each DR program is assumed to be a
       function of customer eligibility in each class, affected end uses in that class, and the
       expected impact of the strategy on the targeted end uses. Analytically, technical potential
       (TP) for a demand-response program (s) is calculated as the sum of impacts at the end-
       use level (e), generated in customer class (c), by the program; that is:

              
        TPs  TPsce
        and
        TPsce LEcs EUScs  se
                            LI

        where,
        LEcs (load eligibility) represents the percent of customer class loads that are eligible for
        strategy s
        EUScse represents the share of end use e in customer class c eligible for DR strategies
        LIse (load impact) is percent reduction in end-use load e resulting from programs
Load eligibility thresholds was established by calculating the percent of load by customer class
and market segment that meets minimum (or maximum) load criterion for each program based
on program filings.

Estimate Demand Response Market Potential
As discussed above, estimates of expected load impacts resulting from various DR programs
(LIse) are based on data available from evaluations of existing programs offered by Alliant and
MidAmerican, as well as a comprehensive review and assessment of DR program impacts
offered by utilities throughout the United States. Program participation indicates the percent of
participating customers, while event participation summarizes the percent of program
participation that will participate in any one event.




Iowa Utility Association – Joint Assessment Study                                                42
Develop Demand Response Resource Supply Curves
Market potentials were determined based on applicable program costs that generally fall into two
categories along with event participation and program participation:

To add additional perspective on market potentials, we developed supply curves by combining
market potentials for each DR program strategy with its per-unit resource costs to produce
“cumulative” resource supply curves. The supply curves show price/quantity relationships for
each utility at the aggregate level. Interactive program impacts were not taken into consideration.

Program implementation costs were researched and documented by our senior engineering staff.
All categories of costs were considered, generally falling into two categories:
         Fixed program expenses such as program infrastructure, administration, maintenance,
          and communication.
         Variable costs such as incentive payments to participants, customer-site hardware,
          customer specific marketing/recruiting, and metering.

Summary of Demand Response Resource Potential
Table 33 and Table 34 report estimated resource potential for all DR resources for the residential,
commercial, and industrial sectors for Alliant and MidAmerican. Market potential is highest in
the industrial sector due to the interruptible program. As noted above, however, the analysis does
not account for program interactions and overlap, and thus the total technical and market
potential estimates are provided as examples only, but are not fully attainable.

                                          Table 33. Alliant Energy
                               Technical and Market Potential (MW in 2018)
                                                                                                            Market
                                                         2018 Technical           2018 Market           Acceptance as
               Sector            2018 Sector Peak
                                                            Potential              Potential           % of 2018 Sector
                                                                                                             Peak
        Residential                        988                     590                     71                   9%
        Commercial                         970                     602                     70                   9%
        Industrial                        1475                    1195                    262                  21%
        Total                             3434                    2388                    403                  14%
        Note: Individual results may not sum to total due to rounding.
        Note: Interactions between programs has not been taken into account.
        Note: DLC RES AC has been eliminated from these potential results to account for complete overlap with DLC RES AC
              and water heating.




Iowa Utility Association – Joint Assessment Study                                                                           43
                                     Table 34. MidAmerican Energy
                               Technical and Market Potential (MW in 2018)
                                                                                                   Market
                                                          2018 Technical       2018 Market     Acceptance as
               Sector            2018 Sector Peak
                                                             Potential          Potential     % of 2018 Sector
                                                                                                    Peak
        Residential                     1,367                    809                 97                9%
        Commercial                        964                    388                 38                5%
        Industrial                      1,516                    868                159               13%
        Total                           3,846                  2,065                295               10%
        Note: Individual results may not sum to total due to rounding
        Note: Interactions between programs has not been taken into account



Resource Costs and Supply Curves
Costs for DR program options vary significantly by category and actual amounts. Applicable
resource acquisition costs generally fall into two categories:
         Fixed program expenses such                               as    program   infrastructure,   administration,
          maintenance, and communication.
         Variable costs such as incentive payments to participants, customer-site hardware,
          customer specific marketing/recruiting, and metering. Variable costs may vary based
          on the number of customers (e.g., hardware) or kW (primarily incentives).

Where possible, costs estimates were developed for each program option based on data available
from Alliant and MidAmerican directly or comparable programs. In certain cases, this level of
specificity was difficult to establish as many utilities did not track or report program costs with
sufficient detail. For example, development of a new DR program can be a significant effort for a
utility, requiring enrollment, call centers, program management, load research, development of
evaluation protocols, changes to billing systems, and marketing. Background research on utilities
across the indicated large variations in direct program costs. Based on the experiences of Alliant,
MidAmerican, and other utilities, this analysis assumed $400,000 as a “typical” first cost for
program development. No first-cost ($0) was assumed in cases where preexisting programs or
infrastructure existed.

Marketing costs can also vary widely, largely based on the sector and level of utility
involvement. Based on interviews with program managers, this analysis assumes $30 for each
new residential participant ($25 in the case of TOU) and $500 for each commercial or industrial
participant based on the difficulty of getting large C&I sites to participate in these programs.

In developing estimates of per-unit costs, program expenses were allocated annually over the
expected program life cycle (10 years), then discounted by a real cost of capital to estimate the
total discounted cost (actual Alliant and MidAmerican values were used). The ratio of this value
and the average annual kW reduction produces the levelized per-kW cost for each resource.
Additionally, attrition rates are used to account for program turnover due to changes in electric
service (i.e., housing stock turnover) and program drop-outs. The basic assumption for this
analysis is 3%, based on averaged values experienced by Alliant and MidAmerican. Attrition


Iowa Utility Association – Joint Assessment Study                                                                 44
requires reinvestment of new customer costs, including technology, installation, and marketing.
In addition, the analysis assumes a measure life for the installed technology, and all costs are
adjusted upward by 15% or $60,000 to account for administrative expenses.21 Table 35 displays
the per-unit ($/kW-year) costs by service territory for the estimated market potential.

Real-time pricing and critical peak pricing (both C&I programs) are estimated to be the least
expensive options, with a levelized cost of $11/kW-year for Alliant, while critical peak pricing
and demand bidding are the least expensive options for MidAmerican, with a levelized cost of
$19/kW-year and $17/kW-year, respectively (real-time pricing was not run for MidAmerican).

                   Table 35. Levelized Costs and Market Potential (MW in 2018)
                                                  Alliant Energy               MidAmerican Energy
                Levelized Cost             Market             Levelized      Market         Levelized
                                        Potential (MW)      Cost ($/kW)   Potential (MW)   Cost ($/kW)
          Direct Load Control (DLC)
            Residential (A/C only)             48               $55            66              $56
            Residential (A/C and WH)           53               $62            72              $63
            Small Commercial (A/C)              1               $96            1               $81
            Medium to Large                     1              $119            1              $169
            Commercial
          Thermal Energy Storage                1              $135            1              $150
          (TES)
          Interruptible Tariffs               291               $45            170             $26
          Demand Bidding                       18               $14            15              $17
          TOU Rates                             7               $38            10              $87
          Critical Peak Pricing (CPP)
            Residential                        11               $95            15              $95
            C&I                                11               $11             9              $19
          Real-Time Pricing (RTP)               9               $11            ---             ---


Service territory supply curves are constructed from quantities of estimated market resource
potential and per-unit costs of each resource option. The capacity-focused supply curves, shown
in Figure 15 and Figure 16, represent the quantity of each resource (cumulative market MW) that
can be achieved at or below the cost at any point. Cumulative MW is created by summing the
market potential along the horizontal axis sequentially, in the order of their levelized costs. For
Alliant, the CPP program for C&I has 11 MW available, and the second lowest cost of the DR
resources. Its quantity, therefore, is added to the 9 MW of RTP program, showing that, in total,
20 MW of resources are available at prices equal to or less than $11/kW-year. Program
interactions are not taken into account for this study. Measure’s highlighted in red are existing
utility programs.




21
     All resource classes in this study include a 15% or $60,000 administrative adder to account for ongoing
     program expenses.



Iowa Utility Association – Joint Assessment Study                                                        45
                                                        Figure 15. Alliant Energy Territory Supply Curve
                                                                    (Cumulative MW in 2018)



                                            Levelized Cost ($/kW-year)
                                                     $160
                                                     $140                                                                 TES
                                                     $120                                                                 DLC - Com
                                                                                                          DLC - Small Com -
                                                     $100
                                                                                                                   AC
                                                                                                                          CPP- RES
                                                      $80                                            DLC - Res - AC
                                                      $60                                                                DLC - Res - AC &
                                                                                                                                WH
                                                      $40               TOU                           Interruptible
                                                                RTP                                       Loads
                                                      $20           Demand Bidding
                                                                  CPP - C&I
                                                       $0
                                                            -            100.00        200.00         300.00          400.00       500.00

                                                                                   Cumulative Savings (MW)




                                                     Figure 16. MidAmerican Energy Territory Supply Curve
                                                                   (Cumulative MW in 2018)


                                          $180
                                                                                                                                 DLC - Com
                                          $160
                                                                                                                                 TES
           Lev elized Cost ($/kW-ye ar)




                                          $140

                                          $120
                                          $100                                                                                  CPP - Res
                                                                                                       DLC-Small Com -
                                          $80                                                                                  Time Of Use Rates
                                                                                                            AC
                                          $60                                                                              DLC - RES - AC and
                                                                                           DLC - Res - AC
                                                                                                                              Water Heat
                                          $40
                                                        CPP - C&I                               Interruptible Loads
                                          $20
                                                     Demand Bidding
                                           $0
                                                 -              50.00   100.00    150.00    200.00   250.00    300.00     350.00    400.00
                                                                                  Cumulative Savings (MW)




Iowa Utility Association – Joint Assessment Study                                                                                                  46
Resource Acquisition Schedule
Each program option has its own ramping rate; the general logic is that it requires three years to
grow a new program from inception to full potential, and the first few years have relatively slow
growth. After year three, the program levels increase at the rate of sales growth, by sector. For
current program offerings from Alliant or MidAmerican (e.g., residential DLC, interruptible
tariffs, etc.), ramping begins with the existing program quantity under contract and increases
with load growth. The assumption, therefore, is that mature programs – in the absence of any
substantial changes in incentive structures – are unlikely to see any changes in impacts other than
from increases in load growth.

Demand Response Resource Results by Program Option
Direct Load Control Results
DLC programs are designed to interrupt specific end-use loads at customer facilities through
utility-directed control. When deemed necessary, the utility is authorized to cycle or shut off
participating appliances or equipment for a limited number of hours on a limited number of
occasions. Customers do not have to pay for the equipment or installation of control systems and
are given incentives that are usually paid through monthly credits on their utility bills. For this
type of program, receiver systems are installed on the customer equipment to enable
communications from the utility and to execute controls. Historically, DLC programs have been
mandatory once a customer elects to participate; however, voluntary participation is now an
option for some programs with more intelligent control systems and override capabilities at the
customer facility. 22

Recently, DLC of air-conditioning has emerged as the most common load management program
type. A recent FERC report indicates, as of August 2006, 234 entities offer DLC programs, and
most of these offer residential air-conditioning load control. 23 In addition to reviewing meta-
studies on DLC, the research team conducted in-depth interviews and researched many key
utility programs, including those from Alliant and MidAmerican, as well as those sponsored by
utilities such as Florida Power and Light, Nevada Power, Sacramento Municipal Utility District,
Southern California Edison, Pacific Gas and Electric, Puget Sound Energy, Austin Energy,
Consolidated Edison, Long Island Power Authority, Idaho Power, Xcel-MN, and Wisconsin
Public Service.24,25

This analysis covers residential and commercial DLC programs and reviewed multiple types of
available end uses, with four program options:




22
     Typically, penalties are associated with non-compliance or opt-outs
23
     FERC, Assessment of Demand Response and Advanced Metering, August 2006
24
     DOE, Benefits of Demand Response in Electricity Markets and Recommendations for Achieving Them, Report
     to Congress, February 2006
25
     E Source, EDRP-F-8, Best Practices in Residential Direct Load Control Programs, November 2006.



Iowa Utility Association – Joint Assessment Study                                                       47
               Residential air-conditioning only
               Residential air-conditioning with water heating
               Small commercial air-conditioning only
               Medium to large commercial programs

  Values used in modeling have been standardized based on DR program research or, where
  appropriate, have been averaged between or taken directly from the MidAmerican and Alliant
  DLC programs.

  Air-Conditioning Only (Residential). Currently, MidAmerican reports approximately 50 MW of
  savings from its SummerSaver program, which targets only residential customers with eligibility
  specific to central cooling systems (including heat pumps).26 On average, MidAmerican calls
  between eight to ten events per season, which is consistent with most of the researched utility
  programs mentioned above. Based on the number of residential customers with central air-
  conditioning, as well as a 50% cycling strategy, technical potential is estimated as 231 MW for
  Alliant and 316 MW for MidAmerican.

  Market potential, however, depends largely on the expected rate of program sign-up. Across the
  country, participation rates vary widely, from as little as 1% to 40% of residential customers.
  MidAmerican had a program participation rate of 19%, while Alliant had a slightly higher
  participation rate of 23%. An average of 21% is used in the analysis.

  Table 36 shows the technical and market results for Alliant and MidAmerican territories, by
  customer class. The difference in potential is largely attributed to MidAmerican having more
  residential customers with central air-conditioning. Alliant and MidAmerican have a levelized
  cost of $55/kW-year and $56/kW-year, respectively.

              Table 36. Residential DLC Air-Conditioning: Technical and Market Potential
                                            (MW in 2018)
                                     Alliant Energy                                 MidAmerican Energy
       Sector         Technical          Market       Market as % of    Technical        Market       Market as % of
                      Potential       Potential27      2018 Peak        Potential       Potential      2018 Peak
Residential             231                49                6%           316              66                6%


  In terms of costs, technology selection is one of the most historically important factors:
  thermostats (which raise the temperature set-point) versus switches (which utilize a duty cycling
  strategy). While equipment costs can vary considerably, the price differences between two-way
  thermostats and simple one-way switches are diminishing as technology costs fall, although


  26
        The Alliant residential DLC program also includes the option for electric water heat, and thus is discussed
        below.
  27
        An impact evaluation of the Alliant residential DLC program found that a significant number (nearly 50%) of
        the load control receivers (LCRs) were not properly functioning. The program is currently installing newer
        LCRs, however, so this failure rate is not expected to continue going forward.



  Iowa Utility Association – Joint Assessment Study                                                             48
installation costs remain significantly different. A range of other issues emerge in choosing the
appropriate technology for a given program, including selection of a communications medium
(FM, paging, other) and the length of the control period. Installed hardware costs range from
about $150 for a simple switch to $450 for a two-way thermostat. This study assumes a one-way
switch (similar to the current Alliant and MidAmerican programs) at a cost of $175.

Utility incentives for residential DLC programs can also vary widely, from only the free
programmable thermostat, to a set incentive amount per month, to a 15% discount on customers’
summer electric bills, which can sum to $50-$60 annually for many participants. Currently,
MidAmerican pays $40 for the first year of participation and $30 each subsequent year;
incentives for Alliant’s DLC program are set at $32/year for only air conditioner cycling, with an
additional $8/year for including water heater cycling. Incentives for this analysis are set at
$32/year for residential A/C cycling. Additional costs are assessed for this program, including:
$30 per new customer of marketing (based on Alliant data); $7 for each existing customer for
communications, replacement of technology every ten years; $400,000 for program start-up, and
an attrition rate (requiring reinvestment of new-customer costs) of 3% based on an average of
1.5% from MidAmerican and 4% from Alliant.28 Detailed assumptions are provided in Table 37.




28
     Other programs researched indicate a 7% attrition rate is common, which is based on a 5% rate of electric
     service turnover plus 2% program removals.



Iowa Utility Association – Joint Assessment Study                                                          49
                    Table 37. Assumptions for DLC Residential Air-Conditioning Potential
                                     Program Concept                               Assumptions
                         Customer Sectors Eligible                 All Residential
                         End Uses Eligible for Program             Central Cooling or Air-Source Heat Pump
                         Customer Size Requirements, if any        N/A
                         Summer Load Basis                         Top 40 Summer Hours
                         Winter Load Basis                         No Winter

                       Inputs                      Model Values                            Model Assumptions
Annual Attrition (%)                                   3%          1.5% (MidAm) and 4% (Alliant) were determined based on data
                                                                   available from the two utilities. Other studies have found 7%
                                                                   (composed of 5% change of service and 2% removals) from
                                                                   utilities, including RMP, Xcel, Eon US, SMUD, PSE&G, FP&L
                                                                   (removals range from 1%–3%).
Per Customer Impacts (kW)                               0.85       Alliant reports 0.8 for A/C controls and 0.2 for WH, while MidAm's
                                                                   savings are calculated to be 0.89 (total reduction of load divided
                                                                   by total number of customers). For consistency, the average
                                                                   value is used in the model.
Total kW reduction per program                         50,660      MidAm Data
Annual Administrative Costs (% of First-year            15%        An administrative adder of 15% was typically assumed for all
Cost)                                                              program strategies (assuming that since 15% will be taken from a
                                                                   first cost of $400,000, the annual administrative cost will be
                                                                   $60,000).
Technology Cost                                         $175       Alliant reports $190 (from EE plan), while $175 is indicated in the
                                                                   CEC report from 2004 (for the installed cost of ratio frequency
                                                                   load control devices). WH controls will require another switch and
                                                                   result in doubling this cost.
Marketing Cost                                          $30        Marketing costs are set at $30 based on data available from
                                                                   Alliant.
Incentive (annual costs)                                $32        MidAm reports $40 for first year and $30 each year after. Alliant
                                                                   reports $32 for A/C only, and up to $40 including WH. For
                                                                   consistency, the average value is used in the model.
Communication Costs (per Customer Per                    $7        This value accounts for annual per-customer communication of a
Year)                                                              one-way transmission system.
Overhead: First Costs                                    $0        MidAm and Alliant both currently offer DLC programs; therefore
                                                                   no first costs are necessary.
Per Customer First Cost                                 $205       MidAm and Alliant both currently offer DLC programs; therefore,
                                                                   no first costs are necessary beyond technology and marketing up
                                                                   front, per participant.
Per Customer Ongoing                                    $57        Ongoing costs are calculated from summing annual customer
                                                                   incentives, annual communication costs, and 10% of Technology
                                                                   costs for repair and/or replacement of equipment.
Eligible Load (%)                                   100% of the    Eligible load is the percentage of customers with this specific end
                                                    Cooling Load   use.
Technical Potential (as % of Gross)                    100%        The assumption is made that all central AC units can be retrofit.
Program Participation (%)                               21%        MidAm participation is set at 19% and is calculated from the
                                                                   number of 2006 participants divided by the total number of
                                                                   eligible participants. Alliant participation is set at 23% of total
                                                                   residential customers.
Event Participation (%)                                100%        It is assumed all customers signed up for the program will be
                                                                   called on during an event.
Average # Events per Season                              8         MidAm indicates eight events per season, and Alliant indicates
                                                                   six to eight events.
Cycling Strategy                                        50%        Both MidAm and Alliant indicate 50% cycling strategies.




    Iowa Utility Association – Joint Assessment Study                                                                         50
  Residential Air-Conditioning and Water Heating. There are several program examples of
  utilities combining residential air-conditioning DLC programs with other end uses. The most
  common program option (with examples from Alliant, as well as other utilities such as Xcel
  Energy, E.ON US, and Florida Power & Light) is to offer customers the opportunity to add hot
  water heating control to their air-conditioning control program. This study estimates the potential
  for this combination using the same air-conditioning assumptions shown in the cooling-only
  program, but adding water heat as an option and including a separate incentive level of $8/year
  (consistent with the current Alliant program). The installed costs for water heat control are
  assumed to be the same as the air-conditioning control, as a similar one-way switch would be
  used. The technical potential for the water heating portion includes only customers with both
  central cooling and electric hot water heating.29

  The results in Table 38 show that adding hot water heating leads to a slight increase in the
  amount of market potential (additional 4 MW for Alliant and additional 6 MW for
  MidAmerican), yet raises the average levelized cost of the program (as the hot water heaters
  have the same costs as air-conditioning, but provide less per-unit demand reductions). Alliant’s
  levelized costs increases from $55/kW-year to $62/kW-year, while MidAmerican increased from
  $56/kW-year to $63/kW-year. This is particularly true in the summer, when the value of capacity
  is highest for Alliant and MidAmerican.

       Table 38. DLC Air-Conditioning and Water Heating: Technical and Market Potential
                                        (MW in 2018)
                                           Alliant Energy                               MidAmerican Energy
         Sector              Technical         Market       Market as %       Technical      Market        Market as %
                             Potential        Potential     of 2018 Peak      Potential     Potential     of 2018 Peak
Residential                    266                53              6%            364             72              7%


  Detailed assumptions providing values and sources that derived the potential and levelized costs
  are shown in Table 39.




  29
       DLC of electric hot water only is generally not considered cost effective, so is only analyzed as an add-on to the
       central air-conditioning DLC program.



  Iowa Utility Association – Joint Assessment Study                                                                   51
      Table 39. Assumptions for DLC Residential Air-Conditioning and Water Heating Potential
                           Program Concept                                           Assumptions
            Customer Sectors Eligible                          All Residential
            End Uses Eligible for Program                      Central Cooling (including Heat Pump) and Electric Hot
                                                               Water Heating
            Customer Size Requirements, if any                 N/A
            Summer Load Basis                                  Top 40 Summer Hours

                 Inputs                 Model Values                                     Model Assumptions
Annual Attrition (%)                   3%                 1.5% (MidAm) and 4% (Alliant) were determined based on data available from
                                                          the two utilities. Other studies have found 7% (composed of 5% change of
                                                          service and 2% removals) from utilities, including RMP, Xcel, Eon US, SMUD,
                                                          PSE&G, FP&L (removals range from 1%–3%).
Per Customer Impacts (kW)              A/C = 0.85kW       Alliant reports 0.8 for A/C controls and 0.2 for WH, while MidAm's savings are
                                       and WH = 0.2kW     calculated to be 0.89 (total reduction of load divided by total number of
                                       Res                customers). For consistency, the average value is used in the model.
Total kW reduction per program         24,430             Alliant Data
Annual Administrative Costs            15%                An administrative adder of 15% was typically assumed for all program
                                                          strategies (assuming that since 15% will be taken from a first cost of
                                                          $400,000, the annual administrative cost will be $60,000).
Technology Costs                       $175 for A/C       Alliant reports $190 (from EE plan), while $175 is indicated in the CEC report
                                       control switch,    from 2004 (for the installed cost of ratio frequency load control devices). WH
                                       $175 for WH        controls will require another switch and result in doubling this cost.
                                       control switch
Marketing Cost (Recruitment Cost)      $30                Marketing costs are set at $30 based on data available from Alliant.
Incentive (annual cost)                $32 for Central    MidAm reports $40 for first year and $30 each year after. Alliant reports $32
                                       AC; $8 for Water   for A/C only, and up to $40 including WH.
                                       Heater
Communication Costs (per Customer      $7                 This value accounts for annual per-customer communication of a one-way
Per Year)                                                 transmission system.
Overhead: First Costs                  $0                 MidAm and Alliant both currently offer DLC programs; therefore, no first costs
                                                          are necessary.
Per Customer First Costs               $205 for A/C and   MidAm and Alliant both currently offer DLC programs; therefore, no first costs
                                       $175 for WH        are necessary beyond technology and marketing up front, per participant.
Per Customer Ongoing Costs             $57 for Central    Ongoing costs are calculated from summing annual customer incentives,
                                       AC; $33 for        annual communication costs, and 10% of Technology costs for repair and/or
                                       Water Heating      replacement of equipment.
Eligible Load (%)                      100%               Eligible load is the percentage of customers with this specific end use.
Technical Potential                    100%               The assumption is made that all central AC units can be retrofit.
(as % of Load Basis)
Program Participation (%)              21% for Central    It is assumed 21% of the participating cooling load will sign up for the program
                                       AC; 12% for        (which is the same as for DLC AC only program). By subsector, program
                                       Water Heating      participation is assumed to be the same rate of program sign-up, but accounts
                                                          for the saturation of electric hot water heating of customers with central AC. It
                                                          is calculated as the percent of customers with electric hot water and central
                                                          cooling, divided by the percent of customers with electric hot water heating,
                                                          which is multiplied by the participation rate of central AC customers. The
                                                          saturations of end uses are taken from RASS survey results.
Event Participation (%)                100%               It is assumed all customers signed up for the program will be called on during
                                                          an event.
Average # Events per Season            8                  MidAm indicates eight events per season, and Alliant indicates six to eight
                                                          events.
Cycling Strategy                       50% for A/C;       Both MidAm and Alliant indicate 50% AC cycling strategies. We also assume
                                       100% for WH        the water heating tank can be shut off during the event.




     Iowa Utility Association – Joint Assessment Study                                                                            52
  Air-Conditioning Only (Small Commercial). Some DLC programs around the nation are also
  including small commercial customers (less than 30 kW) into their existing residential DLC
  programs (PacifiCorp–Utah Cool keeper program is one example). Many of the cost assumptions
  (e.g., switches) are the same as the residential DLC program. Some key differences are an
  increase in the kW/per customer impact due to larger-sized units, as well as significantly lower
  customer participation rate due to concerns about impacts on business activity (typically about
  5% for commercial compared to approximately 21% for residential).

  Table 40 below shows the technical and market results for Alliant and MidAmerican territories
  for a small commercial air-conditioning DLC program. The market potential for air-conditioning
  in either territory is around 1 MW (<1% of 2018 territory peak). Alliant and MidAmerican have
  a levelized cost of $96/kW-year and $81/kW-year, respectively.30

                   Table 40. DLC Air-Conditioning: Technical and Market Potential
                                          (MW in 2018)
                                       Alliant Energy                                 MidAmerican Energy
       Sector            Technical         Market       Market as %       Technical        Market        Market as %
                         Potential        Potential     of 2018 Peak      Potential       Potential      of 2018 Peak
Small Commercial            17                 1             <1%             23                1              <1%


  Detailed assumptions providing values and sources that derived the potential and levelized costs
  are shown in Table 41.




  30
       Note that some cost factors, including administration first costs and ongoing costs, would not be considered if
       the program were to be run as an extension of a current residential DLC project.



  Iowa Utility Association – Joint Assessment Study                                                                53
             Table 41. Assumptions for DLC Small Commercial Air-Conditioning Potential
                            Program Concept                                      Assumptions
               Customer Sectors Eligible                    Small Commercial (<30kW) market segments
               End Uses Eligible for Program                Central Cooling or Air-Source Heat Pump
               Customer Size Requirements, if any           N/A
               Summer Load Basis                            Top 40 Summer Hours
               Winter Load Basis                            No Winter

                   Inputs                    Model Values                              Model Assumptions
Annual Attrition (%)                             3%         1.5% (MidAm) and 4% (Alliant) were determined based on data
                                                            available from the two utilities. Other studies have found 7% (composed
                                                            of 5% change of service and 2% removals) from utilities, including RMP,
                                                            Xcel, Eon US, SMUD, PSE&G, FP&L (removals range from 1%–3%).
Per Customer Impacts (kW)                           1.5     We assume an increased impact for small commercial customers
                                                            (calculated by: 5/3 * 0.89 kW). The calculation accounts for the
                                                            difference in demand for an average-sized unit (e.g.. ratio of a
                                                            residential 3 ton unit and a small commercial 5 ton unit).
Total kW reduction per program                      N/A
Annual Administrative Costs (% of First-            15%     An administrative adder of 15% was typically assumed for all program
year Cost)                                                  strategies (assuming that since 15% will be taken from a first cost of
                                                            $400,000, the annual administrative cost will be $60,000).
Technology Cost                                     $175    Alliant reports $190 (from EE plan), while $175 is indicated in the CEC
                                                            report from 2004 (for the installed cost of ratio frequency load control
                                                            devices). WH controls will require another switch and result in doubling
                                                            this cost.
Marketing Cost                                      $30     Marketing costs are set at $30 based on data available from Alliant.
Incentive (annual costs)                            $48     While commercial customers will have a larger impact than residential,
                                                            they will also be more difficult to get to participate in the program.
                                                            Therefore, we assume the $48 for small commercial customer
                                                            incentives, calculated from the residential incentive (1.5 * $32).
Communication Costs (per Customer Per                $7     This value accounts for annual per-customer communication of a one-
Year)                                                       way transmission system.
Overhead: First Costs                                $0     MidAm and Alliant both currently offer DLC programs; therefore, no first
                                                            costs are necessary.
Per Customer First Cost                             $205    MidAm and Alliant both currently offer DLC programs; therefore, no first
                                                            costs are necessary beyond technology and marketing up front, per
                                                            participant.
Per Customer Ongoing                                $73     Ongoing costs are calculated from summing annual customer
                                                            incentives, annual communication costs, and 10% of Technology costs
                                                            for repair and/or replacement of equipment.
Eligible Load (%)                              Varies by    Eligible load is the percentage of customers with this specific end use.
                                                Sector
Technical Potential (as % of Gross)              50%        The assumption is made that all central AC units can be retrofit.
Program Participation (%)                        5%         We assume commercial participation to be approximately 25% of
                                                            residential participation.
Event Participation (%)                             100%    It is assumed all customers signed up for the program will be called on
                                                            during an event.
Average # Events per Season                          8      MidAm indicates eight events per season, and Alliant indicates six to
                                                            eight events.
Cycling Strategy                                    50%     Both MidAm and Alliant indicate 50% cycling strategies.




    Iowa Utility Association – Joint Assessment Study                                                                        54
Large Commercial DLC Programs. Direct control of commercial customers is an enticing
option for utilities due to the large size of loads and the reliability of direct control. Yet, this
option requires significant technological investment in coordination with the existing EMS and is
generally not favored by customers.

Recently, the International Energy Agency (IEA) released a study that included a survey of
40 major utilities with capacity-focused programs, revealing that fewer than one-quarter of those
surveyed offered DLC programs to their commercial customers. Participation rates were
extremely low, and the majority of these were offered to small commercial customers (as
covered in the air-conditioning program above). Utilities offering programs to large C&I
customers include: Florida Power and Light, Xcel Energy, Otter Tail Power and Light, Madison
Gas and Electric, Wisconsin Electric, and Wisconsin Public Service.

Although the program history is limited, this study estimates potential for large commercial
customers, requiring a size threshold of 200 kW to increase likelihood of existing EMS systems.
The following end uses are assessed by customer segment: cooling, hot water, lighting, plug
load, and refrigeration. It is assumed this program option would be called at similar frequency to
the air-conditioning program: approximately 40 hours per summer.

Technically, only a small portion of the total end-use loads could be curtailed (Table 42). To
estimate the market, the most uncertain factor is program participation. Findings from the IEA
survey indicated C&I DLC program participation rates are generally quite low (less than 1% of
load), excepting Xcel Energy and Otter Tail Power, which achieved participation rates greater
than 10% at a cost of about $250/kW. This study assumes a program participation rate of 2%.
Event participation is assumed at 90% based on other national programs. As shown in Table 42,
although approximately 83 MW and 53 MW are technically available for the Alliant and
MidAmerican territories, respectively, there is essentially no market potential for this program
option due to a lack of interest among customers.

               Table 42. DLC Large Commercial: Technical and Market Potential
                                      (MW in 2018)
                                   Alliant Energy                              MidAmerican Energy
      Sector         Technical         Market       Market as %    Technical        Market        Market as %
                     Potential        Potential     of 2018 Peak   Potential       Potential     of 2018 Peak
 Commercial             83                1             <1%           53               1             <1%


In terms of costs, the analysis estimates interfacing with existing EMS controls for each end use,
reflecting a hierarchy of measures: (1) cooling, (2) lighting, (3) hot water, (4) process, and
(5) plug load. Controls are assumed to last 10 years. Customer incentives are assumed at $6/kW
per month ($72/kW-year) based on the need to pay customers relatively high incentives to have
direct control over loads.

Detailed assumptions providing values and sources that derived the potential and levelized costs
are shown in Table 43.




Iowa Utility Association – Joint Assessment Study                                                               55
                           Table 43. Assumptions for DLC Large Commercial Potential
                                  Program Concept                                Assumptions
                     Customer Sectors Eligible                    All Commercial subsectors
                     End Uses Eligible for Program                Cooling, hot water, lighting, plug load,
                                                                  refrigeration
                     Customer Size Requirements, if any           Loads greater than 200 kW due to EMS
                                                                  system requirements
                     Summer Load Basis                            Top 40 Summer
                     Winter Load Basis                            No Winter

                  Inputs                       Model Values                              Model Assumptions
Annual Attrition (%)                               3%            1.5% (MidAm) and 4% (Alliant) were determined based on data
                                                                 available from the two utilities. Other studies have found 7%
                                                                 (composed of 5% change of service and 2% removals) from utilities
                                                                 including RMP, Xcel, Eon US, SMUD, PSE&G, FP&L (removals
                                                                 range from 1%–3%).
Per Customer Impacts (kW)                     Varies by Sector   This value is a product of technical potential and average kW of
                                                                 eligible customers.
Total kW reduction per program                       N/A
Annual Administrative Costs                          15%         An administrative adder of 15% was typically assumed for all
                                                                 program strategies (assuming that since 15% will be taken from a
                                                                 first cost of $400,000, the annual administrative cost will be
                                                                 $60,000).
Technology Cost                               Varies by Sector   Cost estimates assume the sites have centralized EMS systems
                                                                 and are based on costs Nexant has reviewed for participants in
                                                                 PG&E's Auto Critical Peak Pricing Program. These costs reflect a
                                                                 hierarchy of DR measures that goes: (1) Cooling; (2) Lighting;
                                                                 (3)Hot Water; (4) Process; and (5) Plug load. DLC projects require
                                                                 a costly interface with existing EMS controls. It is assumed these
                                                                 controls will be linked to facilitate cooling DR measures initially with
                                                                 additional measures, most often lighting, added on once the system
                                                                 is connected (i.e., lighting measures cannot be implemented at the
                                                                 lower cost without first incurring the costs associated with cooling
                                                                 measures).
Marketing Cost (per new participant)               $500          Alliant reports $500 per customer for marketing (based upon 10
                                                                 hours of effort by program staff at $50/hr).
Incentive (annual cost per participant)       $72/kW annually    We have observed $6/kW per month based upon other studies. We
                                                                 arrive at $72/kW annually through multiplying the $6/kW
                                                                 assumption by 12 months.
Communication Costs (per Customer Per                N/A
Year)
Overhead: First Costs                            $400,000        We assume $400,000 overhead as a standard program
                                                                 development assumption, which includes costs for internal labor,
                                                                 research, and IT/billing system changes ($200,000 for labor and
                                                                 $200,000 for IT).




    Iowa Utility Association – Joint Assessment Study                                                                             56
                Inputs                      Model Values                                 Model Assumptions
Per Customer First Cost                    Varies by Sector    Our cost estimate assumes each site has a centralized EMS
                                                               system and is based on costs Nexant has reviewed for participants
                                                               in PG&E's Auto Critical Peak Pricing Program. These costs reflect a
                                                               hierarchy of DR measures that goes: (1) Cooling; (2) Lighting;
                                                               (3)Hot Water; (4) Process; and (5) Plug load. DLC projects require
                                                               a costly interface with existing EMS controls. It is assumed these
                                                               controls will be linked to facilitate Cooling DR measures initially with
                                                               additional measures, most often lighting, added on once the system
                                                               is connected (i.e., lighting measures cannot be implemented at the
                                                               lower cost without first incurring the costs associated with cooling
                                                               measures).
Per Customer Ongoing                            Varies         Ongoing costs are calculated from summing annual customer
                                                               incentives and 5% of technology costs for repair and/or
                                                               replacement of equipment.
Eligible Load (%)                          Varies by Sector    We assume full eligibility of loads greater than 200 kW.
Technical Potential (as % of Load Basis)   Varies by Sector    These assumptions are based on detailed engineering audits of DR
                                                               potential of C&I customers throughout California by Nexant, with
                                                               third-party verification of results. Findings are amalgamated by
                                                               sector and end-use category and supported by senior engineering
                                                               analysis.
Program Participation (%)                        2%            Survey results indicate zero market potential when combined with
                                                               other programs (10% is the high stand-alone potential). We are
                                                               assuming participation is more likely 2% (a range of participation
                                                               levels are observed nationally (0.1% to 30.5% - Xcel, Otter Tail
                                                               Power).
Event Participation (%)                          90%           This assumption is based on Xcel Energy Peak Controlled Rates
                                                               and is consistent with other similar programs.
Average # Events per Season                Varies by Sector    This value is a product of technical potential and average kW of
                                                               customers greater than 200 kW.
Cycling Strategy                                 N/A



    Thermal Energy Storage
    For C&I customers, it is possible to use TES systems for cooling; these systems produce ice
    during off-peak periods, which is then used during on-peak periods to cool buildings during pre-
    specified times (typically six hours per day, from April to October).31

    Few investor-owned utilities currently offer TES programs to their customers. Information on
    three such programs was obtained as a result of discussions with a major manufacturer of TES
    equipment. PG&E and SCE initiated RFP processes for TES programs in early 2007, and very
    little information is available about the status of these programs. Xcel Energy (Minnesota) has
    offered incentives for TES systems in one form or another for about 20 years, currently doing so
    as part of its Custom Solutions energy-efficiency program, with modest program results (one or
    two installations each year).



    31
         At this time, there is a commercialized application for small commercial applications (5–20 tons of cooling), for
         which two pilot programs exist in the country.



    Iowa Utility Association – Joint Assessment Study                                                                           57
TES systems require rooftop cooling units, typically found on medium to large commercial sites.
Therefore, this analysis assumes only commercial sector customers with greater than 30 kW in
total site demand would be eligible for participation, and the technical feasibility of participating
is reduced to account for only customers with DX cooling units. Program participation is
assumed to be quite low, about 1.5% of eligible load, based on the experience of existing
programs.

Table 44 displays the results for TES potential for the Alliant and MidAmerican territories.
Technically, the Alliant territory has 89 MW of potential, but, due to low participation rates, it is
likely only 1 MW is available (representing less than 1% of the 2018 territory peak). Similarly,
the MidAmerican territory has 67 MW of potential but only 1 MW of market potential.

              Table 44. Thermal Energy Storage: Technical and Market Potential
                                       (MW in 2018)
                                    Alliant Energy                       MidAmerican Energy
       Sector             Technical      Market    Market as %    Technical    Market    Market as %
                          Potential     Potential  of 2018 Peak   Potential   Potential  of 2018 Peak
 Commercial                  89            1           <1%           67          1           <1%


Detailed assumptions providing values and sources that derived the potential and levelized costs
are shown in Table 45.




Iowa Utility Association – Joint Assessment Study                                                   58
                                      Table 45. Assumptions for TES Potential
                                 Program Name                                     Assumptions
                    Customer Sectors Eligible                   All Commercial Market Segments
                    End Uses Eligible for Program               Electric Cooling Loads
                    Customer Size Requirements, if any          All Commercial Customers with Load >30kW
                    Summer Load Basis                           Average On-Peak Summer
                    Winter Load Basis                           No Winter



                  Inputs                      Model Value                                 Model Assumption
Annual Attrition (%)                             3%             1.5% (MidAm) and 4% (Alliant) were determined based on data
                                                                available from the two utilities. Other studies have found 7%
                                                                (composed of 5% change of service and 2% removals) from
                                                                utilities, including RMP, Xcel, Eon US, SMUD, PSE&G, FP&L
                                                                (removals range from 1%–3%).
Per Customer Impacts (kW)                    Varies by Sector   This value is a product of technical potential and average kW of
                                                                eligible customers.
Total kW reduction per program                     N/A
Annual Administrative Costs (% of                  15%          An administrative adder of 15% was typically assumed for all
overhead                                                        program strategies (assuming that since 15% will be taken from a
first cost)                                                     first cost of $400,000, the annual administrative cost will be
                                                                $60,000).
Technology Cost                                  $798/kW        We assume 1.33 kW/ton A/C units at $600 per ton will result in
                                                                $798/kW. Cost estimates assume a cost of $600/ton of cooling
                                                                offset, which is less than an estimate from the TES program
                                                                manager at a rural electric utility in N. California ($1,000/ton).
Marketing Cost                                    $500          Alliant reports $500 per customer for marketing (based upon 10
                                                                hours of effort by program staff, at $50/hr).
Incentive (annual costs)                           N/A          The incentive in this program is given with free technology. Most
                                                                customers would also participate in some type of price structure
                                                                program to realize savings associated with shifting cooling load to
                                                                off-peak hours.
Communication Costs (per Customer Per              N/A
Year)
Overhead: First Costs                           $200,000        We assume half of the standard assumption ($400,000) since there
                                                                will be no changes to the billing system.
Per Customer First Cost                           $500
Per Customer Ongoing                               $0           In this case, since the incentive is the cost of technology, ongoing
                                                                costs will not fall on the utility, therefore are not considered.
Eligible Load (%)                            Varies by Sector   We assume all commercial customers can participate that have
                                                                loads greater than 30kW.
Technical Potential (as % of Gross)          Varies by Sector   These assumptions are based on the saturation of DX cooling by
                                                                commercial sub-sector.
Program Participation (%)                         1.5%          This assumption is scaled down from 2.5%, based on information
                                                                from Alliant conversation.
Event Participation (%)                           100%          Full participation is expected given the highly reliable scheduling of
                                                                pre-cooling.
Average # Events per Season                        N/A
Cycling Strategy                                  100%




   Iowa Utility Association – Joint Assessment Study                                                                            59
Interruptible Program
Interruptible programs refer to contractual arrangements between the utility and its customers,
typically C&I customers which agree to curtail or interrupt their operations, in whole or part, for
a predetermined period when requested by the utility. In most cases, mandatory participation or
liquidated damage agreements are required once the customer enrolls in the program; however,
the number of curtailment requests, both in total and on a daily basis, is limited by the terms of
the contracts.

Customers are generally not paid for individual events, but are compensated in the form of a
fixed monthly amount per kW of pledged interruptible load or through a rate discount. Typically,
contracts require customers to curtail their connected load by the greater of a set percentage (e.g.,
15%–20%) or a predetermined level (e.g., 100 kW). Both Alliant and MidAmerican programs
are set up for customers to curtail a predetermined level. These programs often involve long-term
contracts and have non-compliance penalties ranging from simply dropping the customer from
the program to more punitive actions, such as requiring the customer to repay the utility for the
committed (but not curtailed) energy at market rates.

The IEA survey of 40 utilities’ DR programs revealed that slightly more than half of utilities
surveyed offer curtailable or interruptible rate programs to their C&I customers. Utilities offering
programs included almost all the major utilities in California, Illinois, Indiana, Iowa, Minnesota,
and Wisconsin, as well as a variety of other utilities, including Allegheny Energy, Colorado
Springs Utilities, Hydro Quebec, and Kansas City Power and Light. Most utilities require
minimum demand reductions to be eligible for the programs, ranging from 50 kW for Xcel
Energy, up to the more typical level of 250 kW for MidAmerican.

In this study, it is assumed C&I customers with a monthly demand of at least 200 kW would be
eligible for such a program. Technical potential is estimated by customer segment. One key
aspect to the potential savings associated with the interruptible program is backup generators.
Since these participants can turn on a back up generator during these critical peak times, the
burden on a customer who has a backup generator is minimal.

Since both utilities currently have a successful interruptible program, many assumptions for this
program were modeled to resemble the current programs for each utility.

Table 46 shows the Alliant territory has 785 MW of technical potential in the C&I sectors and
290 MW of market potential, totaling 14% of the Alliant territory’s 2018 commercial and
industrial peak loads. The MidAmerican territory has 662 MW of technical potential in the C&I
sectors resulting in 170 MW of market potential and representing 9% of the MidAmerican
territory’s 2018 commercial and industrial peak load. In many utility programs (excluding those
in California), customers are allowed to use backup generators to meet curtailment requirements.
MidAmerican and Alliant interruptible programs already take into account the use of standby
generators to help ease the burden of these interruptible events.




Iowa Utility Association – Joint Assessment Study                                                 60
                  Table 46. Interruptible Program: Technical and Market Potential
                                            (MW in 2018)
                                         Alliant Energy                          MidAmerican Energy
         Sector             Technical        Market     Market as %    Technical      Market      Market as %
                            Potential       Potential   of 2018 Peak   Potential     Potential    of 2018 Peak
Residential                    ---             ---           ---          ---           ---            ---
Commercial                     153              57             7%         109            28              4%
Industrial                     633             234            18%         553           142             12%
Total                          786             291            14%         662           170              9%


One key difference between MidAmerican and Alliant is seen in the incentive offered to
participating customers. MidAmerican offers an incentive level of $35/kW-year, while Alliant
indicates an incentive (starting in 2009) of $62/kW-year. This major difference in incentive level
has a significant impact on the levelized cost; Alliant shows a levelized cost of $45/kW, while
MidAmerican shows a much lower levelized cost of $26/kW.

Detailed assumptions providing values and sources that derived the potential and levelized costs
are shown in Table 47.




Iowa Utility Association – Joint Assessment Study                                                           61
                            Table 47. Assumptions for Interruptible C&I Potential
                              Program Name                                        Assumptions
                 Customer Sectors Eligible                     Non-Residential (Large C/I)
                 End Uses Eligible for Program                 N/A
                 Customer Size Requirements, if any            Customers >200kW
                 Summer Load Basis                             Top 40 Summer Hours
                 Winter Load Basis                             Top 40 Winter Hours

                  Inputs                     Model Value                                  Model Assumption
Annual Attrition (%)                            3%              1.5% (MidAm) and 4% (Alliant) were determined based on data
                                                                available from the two utilities. Other studies have found 7%
                                                                (composed of 5% change of service and 2% removals) from utilities,
                                                                including RMP, Xcel, Eon US, SMUD, PSE&G, FP&L (removals
                                                                range from 1%–3%).
Per Customer Impacts (kW)                  Varies by Sector     This value is a product of technical potential and average kW of
                                                                eligible customers.
Total kW reduction per program                   N/A
Annual Administrative Costs                      15%            An administrative adder of 15% was typically assumed for all program
                                                                strategies (assuming that since 15% will be taken from a first cost of
                                                                $400,000, the annual administrative cost will be $60,000).
Technology Cost                                 $1,400          Technology costs include communication, connectivity and meters, if
                                                                necessary; these are based on California spending $32 M for 23,000
                                                                large C&I hardware after the energy crisis.
Marketing Cost                                   $500           Alliant reports $500 per customer for marketing (based upon 10 hours
                                                                of effort by program staff at $50/hr).
Incentive                                       $35/kW          These values ($35/kW for MidAm, $62/kW for Alliant) were
                                                $62/kW          determined based on data available from the two utilities.
Communication Costs (per Customer                 N/A
Per Year)
Overhead: First Costs                             $0            MidAm and Alliant both currently offer the program; therefore, no first
                                                                costs are necessary.
Per Customer First Cost                         $1,900          MidAm and Alliant both currently offer DLC programs; therefore, no
                                                                first costs are necessary beyond technology and marketing up front,
                                                                per participant.
Per Customer Ongoing                         $400 + Tech        Based on information from Alliant, ongoing customer costs include
                                          repair/replacement    time spent renewing contracts ($100/hr for 4 hours), in addition to
                                                 ($70)          annual customer incentives and 5% of technology costs for repair
                                                                and/or replacement of equipment.
Eligible Load (%)                          Varies by Sector     We assume full eligibility of loads greater than 200 kW.
Technical Potential (as % of Gross)        25% commercial;      These assumptions are based on detailed engineering audits of DR
                                            50% industrial      potential of C&I customers throughout California by Nexant, with
                                                                third-party verification of results.
Program Participation (%)                  40% Alliant; 30%     These assumptions are based on information available from the
                                               MidAm            utilities.
Event Participation (%)                    86% MidAm; 50%       Figures based on average participation from recent program years.
                                               Alliant
Average # Events per Season                     N/A
Cycling Strategy                                N/A




   Iowa Utility Association – Joint Assessment Study                                                                             62
Demand Buyback
Under DBB or demand bidding arrangements, the utility offers payments to customers for
reducing demand when requested by the utility. Under these programs, the customer remains on
a standard rate but is presented with options to bid or propose load reductions in response to
utility requests. The buyback amount generally depends on market prices published by the utility
ahead of the curtailment event, and the reduction level is verified against an agreed-upon
baseline usage level.

DBB is a mechanism enabling consumers to actively participate in electricity trading by offering
to undertake changes in their normal consumption patterns. Participation requires the flexibility
to make changes to their normal electricity demand profile, install the necessary control and
monitoring technology to execute the bids, and demonstrate bid delivery. One of several
Internet-based programs is generally used to disseminate information on buyback rates to
potential customers, who can then take the appropriate actions to manage their peak loads during
requested events. The program option in this analysis targets the large C&I customers (>200kW),
consistent with national programs.

Unlike curtailment programs, customers have the option to curtail power requirements on an
event-by-event basis. Incentives are paid to participants for energy reduced during each event,
based primarily on the difference between market prices and utility rates. DBB products are
common in the United States and are being offered by many major utilities. The use of DBB
offerings as a means of mitigating price volatility in power markets is especially common among
independent system operators (ISOs), including ISOs, in California (CAISO), New York
(NYISO), and New England (ISO-NE). However, DBB options are not currently being exercised
regularly due to relatively low power prices. The IEA survey of 40 utilities’ DR programs
revealed that about half of the utilities surveyed offered DBB programs to their C&I customers.
Investor-owned utilities offering programs include almost all of the major utilities in California,
Illinois, Indiana, Minnesota, and Wisconsin, as well as a variety of other utilities, including
Allegheny Energy, KCP&L, and Portland General Electric.

Six utilities that reported larger DBB program impacts as part of the previous IEA survey were
reinterviewed. Utilities generally restrict eligibility for DBB programs to large customers who
can reduce their loads by at least 500 kW – 1,000 kW during peak periods. Of the six utilities
interviewed, only Commonwealth Edison has a low minimum load reduction criterion of 10 kW.
Program participation has also been significantly influenced by the minimum load reduction
required, and Commonwealth Edison consequently has 3,700 participants.

Some utilities, however, have captured significant demand reduction potential from just a few
program participants. Minnesota Power estimates that it could realize about 100 MW of demand
reduction – about 9% of their C&I peak demand – from their five participants in this program if
spot market prices again reach the heights of 1999–2000. Commonwealth Edison claims the
second largest peak reduction potential of the utilities interviewed, at about 5% of their C&I peak
demand. The other utilities’ estimated their potential peak demand reduction impacts from this
program at 0%–2% of their C&I peak demands. These programs have not resulted in large peak
demand impacts for utilities in the past five years due to the relatively low level of spot market
prices during this period.



Iowa Utility Association – Joint Assessment Study                                               63
Table 48 shows that in the Alliant territory, of more than 378 MW of technical potential, an
average of 18 MW can be expected during any one event. In the MidAmerican territory,
308 MW of technical potential results in an average of 15 MW expected during any one event.

         Table 48. Demand Buyback: Technical and Market Potential (MW in 2018)
                                      Alliant Energy                            MidAmerican Energy
         Sector          Technical        Market     Market as %    Technical        Market      Market as %
                         Potential       Potential   of 2018 Peak   Potential       Potential    of 2018 Peak
  Residential                ---              ---          ---          ---              ---           ---
  Commercial                 123                5           <1%          87                4            <1%
  Industrial                 255               13           <1%         221               11            <1%
  Total                      378               18           <1%         308               15            <1%


Because participants are paid based on market energy rates, the cost of this program is relatively
low and passes all economic screens. The levelized cost shows the resulting $14/kW-year and
$17/kW-year in Alliant and MidAmerican territories, respectively. New customer costs include
hardware ($1,400 for communications, connectivity, and any necessary metering), marketing
($500), and program development ($400,000). New participant costs must be reinvested due to
3% annual attrition rates (based on averaged value for Alliant and MidAmerican) and a hardware
life of 20 years.

Detailed assumptions providing values and sources that derived the potential and levelized costs
are shown in Table 49.




Iowa Utility Association – Joint Assessment Study                                                               64
                                      Table 49. Assumptions for DBB Potential
                                 Program Name                                    Assumptions
                 Customer Sectors Eligible                     All C&I Market Segments
                 End Uses Eligible for Program                 Total Load of All End Uses
                 Customer Size Requirements, if any            Customers >200kW
                 Summer Load Basis                             Top 40 Summer Hours
                 Winter Load Basis                             Top 40 Winter Hours

                  Inputs                    Model Value                            Model Assumptions
Annual Attrition (%)                           3%         1.5% (MidAm) and 4% (Alliant) were determined based on data
                                                          available from the two utilities. Other studies have found 7%
                                                          (composed of 5% change of service and 2% removals) from utilities,
                                                          including RMP, Xcel, Eon US, SMUD, PSE&G, FP&L (removals
                                                          range from 1%–3%).
Per Customer Impacts (kW)                    Varies by    This value is a product of technical potential and average kW of
                                              Sector      eligible customers.
Total kW reduction per program                 N/A
Annual Administrative Costs                 15% (60000    An administrative adder of 15% was typically assumed for all
                                             per year)    program strategies (assuming that since 15% will be taken from a
                                                          first cost of $400,000, the annual administrative cost will be $60,000).
Technology Cost                                $1,400     Technology costs include communication, connectivity, and meters, if
                                                          necessary; these are based on California spending $32 M for 23,000
                                                          large C&I hardware after the energy crisis.
Marketing Cost                                  $500      Alliant reports $500 per customer for marketing (based upon 10
                                                          hours of effort by program staff at $50/hr).
Incentive                                      $10/kW     We assume the estimate of $10 per kW, which is taken from 2000–
                                                          2002 Demand Exchange Program, based on average market prices
                                                          of $100/MWh.
Communication Costs (per Customer               N/A
Per Year)
Overhead: First Costs                         $400,000    We assume $400,000 overhead as a standard program development
                                                          assumption, which includes costs for internal labor, research and
                                                          IT/billing system changes ($200,000 for labor and $200,000 for IT).
Per Customer First Cost                        $1,900     This value is calculated from the technology cost and the marketing
                                                          cost per new participant.
Per Customer Ongoing                       $10/kW + $70   Ongoing costs are calculated from summing annual customer
                                                          incentives and 5% of technology costs for repair and/or replacement
                                                          of equipment.
Eligible Load (%)                             Varies by   We assume full eligibility of loads greater than 200 kW.
                                               Sector
Technical Potential (as % of Gross)             20%       These assumptions are based on detailed engineering audits of DR
                                                          potential of C&I customers throughout California by Nexant, with
                                                          third-party verification of results.
Program Participation (%)                     Varies by   This assumption is based on internal survey results, with an average
                                               Sector     of 20% participation.
Event Participation (%)                         25%       Event participation is based on 2006 PacifiCorp results of 25% event
                                                          participation (based on average price of $130/MWh at 12 MW per
                                                          event).
Average # Events per Season                     N/A
Cycling Strategy                                N/A




 Iowa Utility Association – Joint Assessment Study                                                                           65
Residential Time of Use Rates
Information on TOU rates was obtained from tariffs from 60 U.S. utilities, promotional materials
used by utilities offering new TOU (or TOU with CPP) programs during the past five years, and
several interviews with utility staff members.32 TOU rates have been offered by U.S. utilities
since at least the 1970s, but the historic impacts have been quite low.

The TOU rates developed in recent years typically differ from those of the past in several
important ways. First, most new TOU rates contain three price tiers as opposed to the two-tier
rates common in many long-standing TOU programs, including those offered by Alliant and
MidAmerican. This allows utilities to set high prices during their highest peak periods and offer
exceptionally low off-peak prices overnight when the cost is at its lowest and supply is plentiful.
The majority of hours are assigned a “mid-peak” price that is typically a slightly discounted
version of the standard rate. Another change is that the duration of the peak period is typically
shorter than in the past.

Finally, the price differentials between peak and off-peak prices tend to be greater than in the
past to encourage load shifting away from the peak period. For long-standing TOU rates, this
differential averaged about 7.6 cents/kWh, whereas newer programs tend to have a differential of
greater than 10 cents/kWh.

TOU rates are assumed to be available only to the residential customer segments, and the
potential is based on the total load rather than individual end uses. The technically feasible
portion of the load basis expected to be reduced during peak hours is 5% based on results from
California and Puget Sound Energy. 33 The participation rate of the top ten highest-enrolled TOU
programs in the country34 is on average 16%, yet these programs do not represent the experience
of all national programs, many of which have participation rates of <1%. For this analysis,
program participation will be modeled at 8%, the approximate average of all programs.

Table 50 shows there is 92 MW of technical potential and 7 MW of market potential in the
Allaint territory. In the MidAmerican territory, there is 127 MW of technical potential and
10 MW of market potential, both representing less than 1% of 2018 territory peak.




32
     Includes: Gulf Power, Alabama Power, Ameren, Pacific Gas and Electric, Southern California Edison, San
     Diego Gas and Electric, and Teco Energy. Interviews with utility staff: Arizona Public Service, Salt River
     Project, and Florida Power and Light.
33
     Charles River Associates, “Impact Evaluation of the California Statewide Pricing Pilot, Final Report,” March
     16, 2005. See also, Piette, Mary Ann and David S. Watson, “Participation through Automation: Fully
     Automated Critical Peak Pricing in Commercial Buildings,” 2006, Lawrence Berkeley National Laboratory.
     Linkugel, Eric, Proceedings of the 2006 ACEEE Summer Study on Energy Efficiency in Buildings, Pacific
     Grove, CA, August 2006.
34
     FERC, 2006 and R. Gunn, “North American Demand Response Survey Results” (Association of Energy
     Services Professionals, Phoenix, AZ, February 2006).



Iowa Utility Association – Joint Assessment Study                                                             66
          Table 50. Time of Use Rates: Technical and Market Potential (MW in 2018)
                                     Alliant Energy                            MidAmerican Energy
        Sector          Technical        Market     Market as %    Technical        Market      Market as %
                        Potential       Potential   of 2018 Peak   Potential       Potential    of 2018 Peak
   Residential               92                7           <1%         127               10            <1%


The difference in levelized cost between Alliant and MidAmerican is attributable to the
programs’ first costs. Since Alliant currently has a TOU program, the overhead first costs have
been removed, while MidAmerican has a program first cost of $400,000. Alliant has a levelized
cost of $38/kW, while MidAmerican has a significantly higher levelized cost of $87/kW.
Because of the low participation rate for this program (8%), the overhead first cost has a
substantially higher impact on the total levelized cost for the program than most successful
programs.

Detailed assumptions providing values and sources that derived the potential and levelized costs
are shown in Table 51.




Iowa Utility Association – Joint Assessment Study                                                              67
                            Table 51. Assumptions for Residential TOU Potential
                             Program Concepts                                    Assumptions
              Customer Sectors Eligible                         All Residential Market Segments
              End Uses Eligible for Program                     Total Load of All End Uses
              Customer Size Requirements, if any                Residential
              Summer Load Basis                                 Average On-Peak Summer
              Winter Load Basis                                 Average On-Peak Winter

                  Inputs                  Model Value                              Model Assumption
Annual Attrition (%)                         3%          1.5% (MidAm) and 4% (Alliant) were determined based on data
                                                         available from the two utilities. Other studies have found 7%
                                                         (composed of 5% change of service and 2% removals) from utilities,
                                                         including RMP, Xcel, Eon US, SMUD, PSE&G, FP&L (removals
                                                         range from 1%–3%).
Per Customer Impacts (kW)                     0.60       This value is a product of technical potential and average kW of
                                                         eligible customers.
Total kW reduction per program                N/A
Annual Administrative Costs               15% ($60000)   An administrative adder of 15% was typically assumed for all program
                                                         strategies (assuming that since 15% will be taken from a first cost of
                                                         $400,000, the annual administrative cost will be $60,000).
Technology Cost                               $300       This value reflects the cost of meter ($200) and installation ($100).
Marketing Cost                                $25        This cost assumes the same marketing price for DLC residential
                                                         ($30) with the absence of the $5 mailer.
Incentive (annual costs)                       N/A       Bill savings may accrue for some customers, equating to lost
                                                         revenues for the utility. This analysis assumes revenue neutrality for
                                                         the utility.
Communication Costs (per Customer per          N/A
Year)
Overhead: First Costs                          $0        Alliant currently has a TOU program, so no overhead first costs are
                                            $400,000     modeled. MidAmerican currently does not have a TOU program,
                                                         therefore the standard program development assumption of $400,000
                                                         is used, which includes costs for internal labor, research, and
                                                         IT/billing system changes ($200,000 for labor and $200,000 for IT).
Per Customer First Cost                       $325       This value is calculated from the technology cost and the marketing
                                                         cost per new participant.
Per Customer Ongoing                           $15       Ongoing costs are calculated based on 5% of technology costs for
                                                         repair and/or replacement of equipment (no customer incentives for
                                                         TOU).
Eligible Load (%)                             100%       All residential customers are eligible.
Technical Potential (as % of Gross)            15%       This value is based on results from California residential pricing
                                                         programs (CA SPP); fixed TOU shows 15% average peak demand
                                                         reduced (Charles River Associates, 2005). These results are similar
                                                         to those from the now discontinued Puget Sound Energy TOU
                                                         program.
Program Participation (%)                      8%        Alliant indicates 6% to 8% for program participation.
Event Participation (%)                       100%       There are no "events" with TOU rates. Participation can be viewed as
                                                         100%.
Average # Events per Season                    N/A
Cycling Strategy                               N/A




 Iowa Utility Association – Joint Assessment Study                                                                        68
Critical Peak Pricing
Under a CPP program, customers receive a discount on their normal retail rates during non-
critical peak periods in exchange for paying premium prices during critical peak events.
However, the peak price is determined in advance, providing customers with some degree of
certainty about the participation costs. The basic rate structure is a TOU tariff where the rate has
fixed prices for usage during different blocks of time (typically on- and off-peak prices by
season, occasionally including a mid-peak price). During CPP events, the normal peak price
under a TOU rate structure is replaced with a much higher price, generally set to reflect the
utility’s avoided cost of supply during peak periods.

CPP rates only take effect a limited number of times during the year, with a cap typically set on
the number of CPP event hours that can be implemented. In times of emergency or high market
prices, the utility can invoke a critical peak event, where customers are notified and rates become
much higher than normal, encouraging customers to shed or shift load. Most CPP programs
provide advance notice along with event criteria, such as a threshold for forecasted weather
temperatures, to help customers plan their operations. One of the attractive features of the CPP
program is the absence of a mandatory curtailment requirement; however, both incentives and
penalties lie within the pricing structure.

The benefit of a CPP rate over a standard TOU rate is an extreme price signal can be sent to
customers for a limited number of events. Utilities have found that demand reductions during
these events are typically greater than during TOU peak periods for several reasons:
         Customers under CPP rates are often equipped with automated controls triggered by a
          signal from the utility.
         The higher CPP rate serves as an incentive for customers to shift load away from the
          CPP event period.
         The relative rarity of CPP events may encourage short-term behavioral changes,
          resulting in reduced consumption during the events.

Since the CPP rate only applies on select days, it raises a number of questions about when a
utility can call an event, for how long, and how often. The rules governing utility dispatch of
CPP events varies widely by utility and by program, with some utilities reserving the right to call
an event any time, while others must provide notice one day prior to the event.




Iowa Utility Association – Joint Assessment Study                                                69
Currently, peak pricing is being offered through experimental pilots or full-scale programs by
several organizations in the United States,35 notably Southern Company (Georgia Power), Gulf
Power, Niagara Mohawk, California utilities (SCE, PG&E, SDG&E), PJM Interconnection, and
New York ISO (NYISO). Adoption of CPP has not been as widespread in the Western states as it
has been in the East.

Residential CPP. The most common national CPP programs are offered to the residential
customer class. Recently, significant literature has shown the value of a technology-enabled CPP
program, which essentially provides customers with smart thermostats that can be programmed
to change temperature settings and even control other end uses, such as lighting and water
heating, depending on the pricing period (e.g., critical peak period, on-peak, or off-peak).36 This
combination of pricing and technology has shown to be an effective combination in improving
per-customer load impacts.

More recently, process-oriented appliances, such as dishwashers and washing machines, have
incorporated technologies to respond to external CPP signals. During critical events when a rate
increase occurs, these “energy-managed appliances” receive notification on the appliance
interface, giving customers direct notification and the option of delaying usage of the appliance.
These appliances also have the capability to temporarily reduce their energy consumption during
moments of grid instability. For example, a clothes dryer with this technology will reduce power
upon receipt of a remote signal from the utility, then correct for the momentary reduction
through extending the drying time. In both situations of signal response, the customer has the
ability to override the signaled reduction.




35
     See Wolak, Frank, “Residential Customer Response to Real-Time Pricing: The Anaheim Critical-Peak Pricing”
     September 2006. See FERC, Assessment of Demand Response and Advanced Metering, August 2006. See
     Energy & Environmental Economics, A Survey of Time-of-Use Pricing and Demand-Response Programs, July
     2006. See Charles River Associates, “Impact Evaluation of the California Statewide Pricing Pilot, Final
     Report,” March 16, 2005. See also, Piette, Mary Ann and David S. Watson “Participation through Automation:
     Fully Automated Critical Peak Pricing in Commercial Buildings,” 2006, Lawrence Berkeley National
     Laboratory. Linkugel, Eric Proceedings of the 2006 ACEEE Summer Study on Energy Efficiency in Buildings,
     Pacific Grove, CA, August 2006. See staff CPUC testimony at
     http://www.sdge.com/regulatory/tariff/A_05_03_015_%20Gaines_redline.pdf.
36
     Dynamic Pricing, Advanced Metering and Demand Response in Electricity Markets, Severin Borenstein,
     Michael Jaske, and Arthur Rosenfeld, October 2002, FERC. DOE



Iowa Utility Association – Joint Assessment Study                                                           70
Technically, national studies have shown that 13% – 40%37 of peak demand can be reduced for
participating customers; this study assumes a 27% result for the California pricing pilot. 38 In
2006, Gulf Power’s CPP program had 2.5% of customers and a goal of reaching 10%
penetration. Event participation is estimated to be 95%, based on opt-outs being typically less
than 5% now that utilities require customers to use the Internet or the call center to opt out of a
CPP event.

Table 52 shows that technically, 232 MW and 318 MW are available for Alliant and
MidAmerican territories, respectively. These figures are reduced by the program and event
participation rates, resulting in 11 MW (Alliant) and 15 MW (MidAmerican).

                     Table 52. Residential CPP : Technical and Market Potential
                                            (MW in 2018)
                                        Alliant Energy                              MidAmerican Energy
            Sector          Technical       Market     Market as %      Technical        Market      Market as %
                            Potential      Potential   of 2018 Peak     Potential       Potential    of 2018 Peak
     Residential               232              11            1%           318               15              1%


The levelized cost calculated at a rate of $95/kW for both Alliant and MidAmerican. Detailed
assumptions providing values and sources that derived the potential and levelized costs are
shown in Table 53.




37
       Charles River Associates (CRA), Impact Evaluation of the California Statewide Pricing Pilot, March 16, 2005;
       California Energy Commission (CEC), Statewide Pricing Pilot load reduction data for
       Zone 4 (desert and inland climate), provided in MS Excel by Pat McAuliffe, CEC staff, via e-mail November 3,
       2006; Demand Response Research Center (DRRC), Ameren Critical Peak Pricing Pilot, Presentation by Rick
       Voytas, Manager of Corporate Analysis at Ameren Services, at the Demand Response Town Hall Meeting,
       Berkeley, CA, June 26, 2006; International Energy Agency, Demand-Side Management Programme, Task XI:
       Time of Use Pricing and Energy Use for Demand Management Delivery, Subtask 2: Time of Use Pricing for
       Demand Management Delivery, April 2005. Rocky Mountain Institute, Automated Demand Response System
       Pilot, Final Report Volume 1: Introduction and Executive Summary, March 2006. Summit Blue Consulting,
       Interim Report for the myPower Pricing Segment Evaluation, prepared for PSEG, December 27, 2006.
       University of California Energy Institute (UCEI), Dynamic Pricing, Advanced Metering and Demand Response
       in Electricity Markets, S. Borenstein et al., October 2002.
38
       See Charles River Associates, 2005.



Iowa Utility Association – Joint Assessment Study                                                               71
                              Table 53. Assumptions for Residential CPP Potential
                              Program Concepts                                   Assumptions
                Customer Sectors Eligible                     All Residential Market Segments
                End Uses Eligible for Program                 Total Load of All End Uses
                Customer Size Requirements, if any            All
                Summer Load Basis                             Top 40 Summer Hours

                Inputs                   Model Value                                Model Assumptions
Annual Attrition (%)                        3%          1.5% (MidAm) and 4% (Alliant) were determined based on data available
                                                        from the two utilities. Other studies have found 7% (composed of 5%
                                                        change of service and 2% removals) from utilities, including RMP, Xcel,
                                                        Eon US, SMUD, PSE&G, FP&L (removals range from 1 %–3%).
Per Customer Impacts (kW)                    0.60       This value is a product of technical potential and average kW of eligible
                                                        customers.
Total kW reduction per program
Annual Administrative Costs                  15%        An administrative adder equivalent to 15% of program cost was typically
                                                        assumed for all program strategies (assuming that, since 15% would be
                                                        taken from a first cost of $400,000, the annual administrative cost will be
                                                        $60,000).
Technology Cost                              $300       This value reflects the cost of meter ($200) and installation ($100).
Marketing Cost                               $35        This cost assumes an increase from the TOU marketing cost.
Incentive (annual costs)                     N/A
Communication Costs (per Customer             $7        This value accounts for annual per-customer communication of a one-
Per Year)                                               way transmission system.
Overhead: First Costs                      $200,000     Since the setup of CPP will build upon the existing TOU residential
                                                        program, the first costs will be 50% of the standard assumption of
                                                        $400,000.
Per Customer First Cost                      $335       This value is calculated from the technology cost and the marketing cost
                                                        per new participant.
Per Customer Ongoing                          $22       Ongoing costs are calculated from summing annual customer incentives
                                                        and 5% of technology costs for repair and/or replacement of equipment.
Eligible Load (%)                            100%       All residential customers are eligible.
Technical Potential (as % of Gross)          27%        The assumption is based on results from California residential pilot CPP
                                                        programs for statewide average (Charles River Associates, 2005).
Program Participation (%)                     5%        Gulf Power has the only full-scale residential CPP program. The
                                                        company reported 8,500 participants as of October 2006, out of 350,000
                                                        residential customers (2.4%). (Sources: Jim Thompson presentation to
                                                        PURC Energy Policy Roundtable, October 31, 2006; and FERC Form
                                                        861 data, 2005.) They expect to reach at least 10% penetration. (Source:
                                                        Dynamic Pricing, Advanced Metering and Demand Response in
                                                        Electricity Markets, Severin Borenstein, Michael Jaske, and Arthur
                                                        Rosenfeld, October 2002.)
Event Participation (%)                      95%        Opt-outs are typically less than 5% now that utilities are requiring
                                                        customers to use the Internet or call center to opt out of a CPP event.
                                                        (Source: Conversation with Tom Van Denover, VP Comverge March
                                                        2007.) With 2-way communications (through AMI or Zigbee gateway, for
                                                        example) utilities can identify and replace malfunctioning thermostats, so
                                                        event participation is much higher than in older one-way, switch-based
                                                        DLC programs.
Average # Events per Season                  N/A
Cycling Strategy                             N/A




    Iowa Utility Association – Joint Assessment Study                                                                       72
Commercial and Industrial CPP. There have been very few C&I CPP programs for medium-to-
large customers, and the pilots tested in California have typically linked the CPP rate with
“enhanced automation” technologies that facilitate load curtailment. This implies the CPP rate
itself and the price incentive it creates may not be the main driver of load reductions.

In FERC’s 2006 survey of utilities offering DR programs, roughly 25 entities reported offering at
least one CPP tariff. However, many of the tariffs were only pilot programs, and almost all the
11,000 participants were residential customers. The top five utilities (by number of participants
enrolled) accounted for 96% of the total number of participants reported to be on CPP rates. Gulf
Power had the largest number (about 8,000 participants), which were entirely residential. Cass
Country Electric Cooperative came in next at nearly 3,000 residential-only participants. The
other three in the “top five” were the three major California investor-owned utilities. Of those,
only SCE included commercial customers in its pilot, and it had 270 commercial participants.
The lack of commercial CPP programs is supported by a 2006 survey of pricing and DR
programs commissioned by the U.S. Environmental Protection Agency, which found only four
large-customer CPP programs, all of them in California.39

Table 54 shows there is 166 MW of technical potential in the Alliant territory, with 11 MW
market potential (representing nearly 1% of 2018 territory peak). The MidAmerican territory has
143 MW of technical potential and 9 MW of market potential. The majority of market potential
is in the industrial sector.

                  Table 54. C&I CPP: Technical and Market Potential (MW in 2018)
                                       Alliant Energy                             MidAmerican Energy
         Sector           Technical        Market     Market as %     Technical        Market      Market as %
                          Potential       Potential   of 2018 Peak    Potential       Potential    of 2018 Peak
  Residential                ---             ---           ---           ---             ---            ---
 Commercial                   61                4           <1%           49               3             <1%
 Industrial                  105                7           <1%           93               6             <1%
 Total                       166               11           <1%          143               9             <1%



The levelized cost was calculated at a rate of $11/kW for Alliant and $19/kW for MidAmerican.
Detailed assumptions providing values and sources that derived the potential and levelized costs
are shown in Table 55.




39
     See “Participation through Automation: Fully Automated Critical Peak Pricing in Commercial Buildings,”
     Mary Ann Piette, David S. Watson, Naoya Motegi, Sila Kiliccote, Lawrence Berkeley National Laboratory,
     Eric Linkugel, Pacific Gas and Electric Company, Proceedings of the 2006 ACEEE Summer Study on Energy
     Efficiency in Buildings, Pacific Grove, CA, August 13-18, 2006. See also, Charles River Associates, Impact
     Evaluation of the California Statewide Pricing Pilot, Final Report, March 16, 2005.



Iowa Utility Association – Joint Assessment Study                                                             73
                                      Table 55. Assumptions Used for C&I CPP
                              Program Concept                                       Assumptions
               Customer Sectors Eligible                          All C&I Market Segments
               End Uses Eligible for Program                      Total Load of All End Uses
               Customer Size Requirements, if any                 C&I greater than 30kW
               Summer Load Basis                                  Top 40 Summer Hours

                  Inputs                   Model Value                                 Model Assumption
Annual Attrition (%)                          3%             1.5% (MidAm) and 4% (Alliant) were determined based on data
                                                             available from the two utilities. Other studies have found 7%
                                                             (composed of 5% change of service and 2% removals) from utilities,
                                                             including RMP, Xcel, Eon US, SMUD, PSE&G, FP&L (removals
                                                             range from 1%–3%).
Per Customer Impacts (kW)                 Varies by Sector   This value is a product of technical potential and average kW of
                                                             eligible customers.
Total kW reduction per program                 N/A
Annual Administrative Costs                    15%           An administrative adder of 15% was typically assumed for all
                                                             program strategies (assuming that since 15% will be taken from a
                                                             first cost of $400,000, the annual administrative cost will be $60,000).
Technology Cost                               $1,400         Technology costs include communication, connectivity, and meters, if
                                                             necessary; these are based on California spending $32 M for 23,000
                                                             large C&I hardware after the energy crisis.
Marketing Cost                                 $500          Alliant reports $500 per customer for marketing (based upon 10
                                                             hours of effort by program staff at $50/hr).
Incentive (annual costs)                        N/A          There are no customer incentives, but the utility may not design the
                                                             rate to be revenue neutral, which could prove to be a cost in terms of
                                                             lost revenues.
Communication Costs (per Customer               N/A
Per Year)
Overhead: First Costs                        $200,000        Since the setup of CPP will build upon the existing TOU program, the
                                                             first costs will be 50% of the standard assumption of $400,000.
Per Customer First Cost                       $1,900         This value is calculated from the technology cost and the marketing
                                                             cost per new participant.
Per Customer Ongoing                            $70          Ongoing costs are calculated from summing annual customer
                                                             incentives and 5% of technology costs for repair and/or replacement
                                                             of equipment.
Eligible Load (%)                         Varies by Sector   We assume all commercial customers can participate that have loads
                                                             that are greater than 30kW.
Technical Potential (as % of Gross)             8%           These assumptions are based on detailed engineering audits of DR
                                                             potential of C&I customers throughout California by Nexant, with
                                                             third-party verification of results. Studies of CPP results show that 8%
                                                             was saved on average (LBNL Fully Automated CPP study, 2006).
Program Participation (%)                      12%           This assumption is based on internal survey results (excluding
                                                             participation for Health and Lodging building types).
Event Participation (%)                        56%           The assumption is based on the results of the 2006 California C&I for
                                                             pilot CPP programs.
Average # Events per Season                     N/A
Cycling Strategy                                N/A




 Iowa Utility Association – Joint Assessment Study                                                                              74
Real-Time Pricing
Commercial and Industrial RTP. Under RTP programs, electricity prices vary each hour
according to the expected marginal cost of supply and are typically established one day ahead of
the time the prices are in effect. Where CPP utilizes pre-set pricing, RTP utilizes electricity
wholesale prices, which change throughout the day. Programs vary from day-ahead to hour-
ahead notification. Notification occurs via the Internet or technology-enabled devices (Internet-
or radio-based devices).

At least 24 utilities offer RTP programs for commercial customers, although 13 are pilot
programs. In states where the wholesale market is run by an Independent System Operator (e.g.,
MISO, PJM, ISO-NE, NYISO), prices typically reflect the hourly spot market price, either on a
day-ahead or closer to a true real-time basis. For vertically integrated utilities such as Georgia
Power, which has an RTP rate program, prices are set by the marginal cost of generation.

The most commonly cited reason for introducing RTP is to build customer satisfaction and
loyalty by providing an opportunity for customers to realize bill savings. A two-part rate, where
a Customer Baseline Load (CBL) is established and compared to actual loads, is used by Niagara
Mohawk and Georgia Power, and was common in early program designs. Only the difference in
actual versus expected usage is subject to real-time prices. Many newer programs have
unbundled the electricity commodity from transmission and distribution services, and the
electricity component is priced according to hourly energy prices. Additionally, Georgia Power
offers Price Protection Products that enable RTP customers to manage their exposure to volatile
prices.

One important thing to note in C&I RTP programs is, while a few programs have been very
successful, it can be difficult to attract participants. A survey conducted by Lawrence Berkeley
National Laboratory of 40 of 42 voluntary C&I RTP programs found just three programs had
more than 100 customers enrolled in 2003, which accounted for the majority of all non-
residential RTP participants identified in the survey. For example, half of the programs in the
study had fewer than ten customers enrolled, and one-third had no participants.

The program modeled in this analysis requires a minimum threshold of 200 kW, which is
consistent with other programs nationally.

Table 56 shows there is 279 MW of technical potential for the Alliant territory, with 9 MW of
market potential. The MidAmerican is not part of MISO and currently does not have the
capability to receive advanced notice of electricity price structure in time to relay to customers
and therefore this study did not evaluate RTP for MidAmerican.




40
     Barbose, Galen et al., A Survey of Utility Experience with Real Time Pricing, LBNL, December 2004.
     See also Neenan Associates, “Customer Adaptation to RTP as Standard Offer Electric Service: A Case Study of
     Niagara Mohawk's Large Customer RTP Tariff,” LBNL 2004.



Iowa Utility Association – Joint Assessment Study                                                            75
                   Table 56. RTP: Technical and Market Potential (MW in 2018)
                                          Alliant Energy                            MidAmerican Energy
         Sector            Technical           Market    Market as %    Technical         Market     Market as %
                           Potential         Potential   of 2018 Peak   Potential        Potential   of 2018 Peak
   Residential                 ---                ---          ---          ---              ---           ---
   Commercial                   76                  1           <1%         ---              ---           ---
   Industrial                  203                  8           <1%         ---              ---           ---
   Total                       279                  9           <1%         ---              ---           ---
   Note: RTP – C&I has not been modeled for MidAmerican.


The levelized cost calculated at a rate of $11/kW for Alliant. Detailed assumptions providing
values and sources that derived the potential and levelized costs are shown in Table 57.




Iowa Utility Association – Joint Assessment Study                                                                   76
                                      Table 57. Assumptions for C&I RTP
                             Program Concept                                     Assumptions
              Customer Sectors Eligible                       All C&I Market Segments
              End Uses Eligible for Program                   Total Load of All End Uses
              Customer Size Requirements, if any              Greater than 200kW
              Summer Load Basis                               Average On-Peak Summer

                  Inputs                  Model Value                             Model Assumptions
Annual Attrition (%)                         3%         1.5% (MidAm) and 4% (Alliant) were determined based on data
                                                        available from the two utilities. Other studies have found 7%
                                                        (composed of 5% change of service and 2% removals) from utilities,
                                                        including RMP, Xcel, Eon US, SMUD, PSE&G, FP&L (removals range
                                                        from 1%–3%).
Per Customer Impacts (kW)                  Varies by    This value is a product of technical potential and average kW of eligible
                                            Sector      customers.
Total kW reduction per program               N/A
Annual Administrative Costs              15% ($60000)   An administrative adder of 15% was typically assumed for all program
                                                        strategies (assuming that since 15% will be taken from a first cost of
                                                        $400,000, the annual administrative cost will be $60,000).
Technology Cost                              $1,400     Technology costs include communication, connectivity, and meters, if
                                                        necessary; these are based on California spending $32 M for 23,000
                                                        large C&I hardware after the energy crisis.
Marketing Cost                                $500      Alliant reports $500 per customer for marketing (based upon 10 hours
                                                        of effort by program staff at $50/hr).
Incentive (annual costs)                      N/A       There are no customer incentives, but the utility may not design the
                                                        rate to be revenue neutral, which could prove to be a cost in terms of
                                                        lost revenues.
Communication Costs (per Customer Per         N/A
Year)
Overhead: First Costs                       $400,000    We assume $400,000 overhead as a standard program development
                                                        assumption, which includes costs for internal labor, research and
                                                        IT/billing system changes ($200,000 for labor and $200,000 for IT).
Per Customer First Cost                      $1,900     This value is calculated from the technology cost and the marketing
                                                        cost per new participant.
Per Customer Ongoing                          $70       Ongoing costs are calculated from summing annual customer
                                                        incentives and 5% of technology costs for repair and/or replacement of
                                                        equipment.
Eligible Load (%)                           Varies by   We assume full eligibility of loads greater than
                                             Sector     200 kW.
Technical Potential (as % of Gross)         Varies by   These assumptions are based on detailed engineering audits of DR
                                             Sector     potential of C&I customers throughout California by Nexant, with third-
                                                        party verification of results. Studies of CPP results show 8% was saved
                                                        on average (LBNL Fully Automated CPP study, 2006), which is
                                                        comparable to taking this technical potential and the event participation
                                                        combined.
Program Participation (%)                   Varies by   This assumption is based on internal survey results.
                                             Sector
Event Participation (%)                      100%
Average # Events per Season                   N/A
Cycling Strategy                              N/A




  Iowa Utility Association – Joint Assessment Study                                                                        77
Residential Real-Time Pricing. At this point, residential RTP is not widespread, but interest is
reported to be increasing.41 In Illinois in 2006, after a four-year pilot program run by the
Community Energy Cooperative in Chicago with ComEd customers, the General Assembly
unanimously passed legislation requiring large investor-owned utilities to offer residential RTP
to all customers. New programs offered by ComEd and Ameren launched in Spring 2007. In this
study, however, the program history was judged to be inadequate to provide a reliable basis for
effectively modeling this program option.




41
     Anthony Star presentation, “Why Residential Real-Time Pricing is the Real Deal!” presented at Innovations in
     Retail Pricing, Association of Energy Services Professionals, May 18, 2006.



Iowa Utility Association – Joint Assessment Study                                                               78
5.      Renewable Resources

Scope
In addition to traditional energy-efficiency resources, this report includes an analysis of two
classes of renewable resources: active (dispersed generation) and passive (energy-efficiency)
resources. Active resources, loosely defined as “dispersed generation” (DG), include energy-
based resources of biomass and three “clean generation” (non-combustion) resources: building
photovoltaics (on-site solar), small hydro, and small wind. Passive resources fall into two broad
categories: passive solar building design and renewable efficiency measures.

Active Resources
Active (or DG) resources are used to produce electricity and offset electric loads. As such, they
were only considered for the two electricity-delivering utilities, Alliant and MidAmerican
Energy. For clean generation resources, only resources less than the net metering limit (500 kW)
were considered. There is, therefore, additional potential from clean renewable resources over
500 kW, but, as these are considered supply-side options, they are not considered in this study.
Larger installations over 500 kW, however, are included for biomass since they often are
operated in large industrial facilities that consume all electricity produced. The analysis
examined four active resources:
         Biomass Energy refers to energy generated from any plant- or animal-based material.
          Biomass can be directly combusted (i.e., industrial biomass) or fed into an anaerobic
          digester to produce biogas, which can then be combusted to produce electricity.
          Although biomass energy is based on a renewable resource, this combustion process
          is not considered “clean” as it does produce combustion products (e.g., carbon
          dioxide, NOx, etc.).
         Building Photovoltaics are from rooftop-based photovoltaic (PV) panels that convert
          sunlight to electricity.
         Small Hydro is sometimes known as run-of-river hydroelectric power generation as
          dams need not be built to regulate water flow. Four basic types of installations are
          included in this study: small hydro, micro hydro, low-power conventional, and low-
          power unconventional.
         Small Wind encompasses small, electricity-generating wind turbines, installed at the
          customer site.

Passive Efficiency Resources
Passive efficiency resources offset gas or electric requirements similar to other energy-efficiency
resources. Passive efficiency measures include: solar water heaters, solar attic fans, corn pellet
stoves, and passive solar design techniques (e.g., eaves on south facing windows, Trombe walls
[thermal walls], tree planting, and smart siting).



Iowa Utility Association – Joint Assessment Study                                               79
Methodology
The overall methodology used to calculate the potential from renewable resources included three
steps:
          Technical potential was calculated separately for each resource categories, using the
           following key data inputs:
           o Biomass Energy: utility’s industrial customer database for size and count of
               biomass-producing industrial facilities and service territory demographics for
               biogas-producing (anaerobic digester) facilities.
           o Building PV: customer counts and building square footage assumptions.
           o Small Hydro: potential river sites for turbines from Hydro Prospector42 by county
               and installation type, including stream flow data from representative streams to
               determine availability factors.
           o Small Wind: energy output estimated using the Wind Turbine Output Calculator
               provided by the Iowa Energy Center,43 factoring wind power density, population
               density, proximity to airports, and sensitive land areas.
           o Passive Efficiency Resources: technical feasibility factors, similar to other
               energy-efficiency resources.
          Various technology costs were calculated based on literature searches, available
           databases, and other states’ programs. Installed costs included capital costs, planning,
           installation, and other adders.
          Market potential was determined for each resource class based on other
           programmatic successes. Note that not all market potential is economic and,
           therefore, may not be achievable. For passive efficiency resources, market potential
           given was equivalent to the economic potential, calculated similarly to other energy-
           efficiency resources.

Summary of Findings
This section presents a summary of the key findings for renewable potentials. More detail
regarding each resource follows these highlights.

Resource Potential
To correctly estimate the quantity of potential in the market, it is essential to know the current
penetration of renewable technologies currently found in the marketplace. The installed
renewable nameplate capacity, presented in Table 58, was obtained from existing
databases,44 ,45,46 net metering data, and the Wind Energy Manual (published by the Iowa Energy


42
     http://hydropower.id.doe.gov/prospector/index.shtml
43
     http://www.energy.iastate.edu/renewable/wind/maps-index.html
44
     http://www.eea-inc.com/chpdata/index.html



Iowa Utility Association – Joint Assessment Study                                               80
Center).47 This capacity excluded large “central-station” generation facilities and the large
utility-owned generation facilities (e.g., wind farms). A full list of each site is provided in
Volume II, Appendix E. Insufficient data existed for an accurate assessment of installed capacity
of passive efficiency resources.

                  Table 58. Installed DG Renewable Capacity by Resource (2006)
                                           Resource               Capacity (MW)
                                  Biomass Energy                         58.4
                                  Building Photovoltaics                 0.02
                                  Small Hydro                             7.3
                                  Small Wind                              6.0
                                  Total                                  71.7



Technical Potential
The technical potential from active DG resources (Biomass Energy, PV, Small Hydro and Small
Wind), not including existing capacity, is 62,886 GWh in 2018 (Table 59). More than half of the
technical potential for DG renewables comes from PV (52%), followed by small wind (30%),
and biomass energy (16%). It should be recognized that technical potential for the DG resources
is significantly higher than what can be achieved, primarily due to high upfront costs required for
these resources and, particularly for small wind, feasibility constraints.

Passive resources, which offset energy usage for cooling, space heating, or water heating, can
account for an additional 469 GWh of electric savings, plus 732,466 decatherms of savings
(Table 60), not including estimates for currently installed measures. In total, technical electric
potential from DG and passive renewable resources in 2018 is 63,355 GWh.

                Table 59. Technical Potential for DG Renewable Resources (2018)
                                  Resource                   GWh                  Percent
                        Biomass Energy                       10,134                    16%
                        Building Photovoltaics               32,888                    52%
                        Small Hydro                           1,156                     2%
                        Small Wind                           18,708                    30%
                        Total                                62,886                   100%




45
     http://www.epa.gov/lmop/proj/index.htm gives waste-in-place data for eligible landfills. If waste-in-place is not
     specified, a 500 kW generation potential is assumed.
46
     http://www.chpcenternw.org/ and http://www.intermountainchp.org/
47
     Available at http://www.energy.iastate.edu/renewable/wind/wem-index.html.



Iowa Utility Association – Joint Assessment Study                                                                  81
             Table 60. Technical Potential for Passive Renewable Resources (2018)
                                              Resource                        Potential
                        Electric passive efficiency resources                  469 GWh
                        Gas passive efficiency resources                     732,466 Dth



Market and Economic Potential
For DG resources, market potential represents the portion of technical potential that might
actually be installed. It should be realized that not all these resources are economic, but,
nonetheless, may be installed by customers willing to accept long payback times. For passive
efficiency measures, the economic potential is provided, as determined for other energy-
efficiency resources.

Note that the market potential also considered current incentives for these resources. Other than
incentives shown in Volume II, Appendix E for wind and PV, no direct rebates are currently
offered to Iowa customers (i.e., no $/W rebates is offered). Despite the lack of direct rebates, the
Federal Production Tax Credit48 is available to commercial and industrial projects, and the
Federal Renewable Energy Production Incentive49 is available to non-taxable entities (e.g.,
municipal projects) for clean energy options.

The market potential for all renewable resources is shown in Table 61 for DG renewable
resources savings and in Table 62 for passive resources. Compared to the technical potential of
DG resources (Table 59), this potential is significantly less due to economic considerations, low
awareness of technologies, and other permitting or interconnection concerns (details are provided
in the results sections, below).

Among the DG resources, biomass energy composes the largest percentage of market potential
(155 GWh), followed by small wind (103 GWh), and PV (25 GWh). The percentage of technical
potential economic for passive efficiency resources is 97% of electric (453 GWh) and 88% of
gas (644 thousand DTh).

                 Table 61. Market Potential for DG Renewable Resources (2018)
                                   Resource                Potential (GWh)    Percent
                         Biomass Energy                           155             54%
                         Building Photovoltaics                     25             8%
                         Small Hydro                                  7            2%
                         Small Wind                               103             36%
                         Total                                    290            100%




48
     Production Tax Credit is 1.9 cents/kWh available through December 31, 2008 and applies to the first 10 years
     of production (http://www.dsireusa.org).
49
     Renewable Energy Production Incentive is 1.5 cents per kWh (indexed for inflation) with a 10 year term.
     (http://www.dsireusa.org).



Iowa Utility Association – Joint Assessment Study                                                             82
        Table 62. Economic Potential for Passive Renewable Resources by Fuel (2018)
                                                                    Resource                       Potential
                                           Electric passive efficiency resources                      453 GWh
                                           Gas passive efficiency resources                         643,806 Dth


Figure 17 presents the cumulative supply curve for all DG resources. Biomass Energy is broken
into potential from Industrial Biomass (direct combustion) and Anaerobic Digesters (biogas
combustion). Further details on these and all renewable potentials are discussed below.

     Figure 17. Cumulative Supply Curve for Dispersed Generation Renewable Resources
                                          (2018)

                                   $0.70
                                                                                                                  PV
                                   $0.60
          Levelized Cost ($/kWh)




                                   $0.50

                                   $0.40

                                   $0.30

                                   $0.20
                                                                                     Anaerobic                     Hydro
                                   $0.10                                             Digesters               Wind
                                                                  Ind Biomass
                                   $-
                                            0           50,000       100,000       150,000   200,000   250,000         300,000
                                                                             Cummulative MWh




Biomass Energy
Biomass is combusted within an on-site generator at a customer’s facility. Generally, power
generated through these technologies is expected to contribute to the utility’s base load resources
rather than peak load requirements. Peak load reduction with an on-site generator or dispatchable
standby generation is not addressed here. 50 In addition, a program by the Iowa Department of
Natural Resources (DNR) promotes community-scale digesters.51 This specialized application is



50
     Dispatchable standby generation is generally considered a demand response resource.
51
     For more information on these community-scale digesters, please see “Anaerobics for Iowa Communities;”
     BioCycle, July 2007.



Iowa Utility Association – Joint Assessment Study                                                                                83
not considered here as it is large scale and requires coordination between multiple parties,
including city or county governments.

The three primary generator technologies available in the market are: (1) reciprocating engines
(either spark-ignition or compression-ignition); (2) turbines (gas or steam for larger capacity
[>1 MW] or microturbines for smaller capacity [<1 MW]); and (3) fuel cells, primarily those
using phosphoric acid (PAFC) or molten carbonate (MCFC) as the electrolyte, although other
types of fuel cells are now becoming commercially viable.52

The source of biomass can be either industrial-produced biomass or biogas fuel produced from
anaerobic digesters. This biomass can be consumed in one of the above generators for on-site
electricity usage. Industrial biomass includes waste product from industries such as chemical
plants (including ethanol production) or pulp and paper manufacturing, which is combusted in
place of natural gas or other fuel to produce steam for use in a steam turbine. Industrial biomass
systems are generally large scale, usually greater than 1 MW.

Anaerobic digesters create methane gas (biogas fuel) by breaking down liquid or solid biological
waste. The waste used can be derived from farm manure, landfills, or wastewater treatment
facilities. Anaerobic digesters for farms, smaller landfills, and wastewater treatments facilities
are coupled with smaller-scale generators, such as reciprocating engines, microturbines, or fuel
cells. Larger landfills, with capacities over 1 MW, can use either reciprocating engines or gas
turbines

As anaerobic digesters require high temperatures to operate, a combined heat and power unit
(CHP) is usually used instead of a standard generator. A CHP unit includes a standard electrical
generator, such as a reciprocating engine, but the generator’s waste heat is captured and used for
other processes. For example, a typical spark-ignition engine has an electrical efficiency of about
only 35%; the “lost” energy is primarily waste heat. A CHP unit will capture much of this waste
heat and use it for maintaining the temperature of an anaerobic digester.53

Biomass fuels from the agricultural sector (e.g., crop waste such as bagasse from sugar, rice
hulls, and rice straw) are not considered in this study. Due to high moisture content and varying
availability, crop residues are not a viable fuel alternative for most generation applications.54 In
addition, the prime energy-producing crops (sugar cane and rice) are largely not present in Iowa.

This study only considers on-site biomass generation primarily used for building energy and heat
needs. Large “central-station” generation facilities operating to sell the majority (or all) of their
power to the grid are outside the scope of this work.




52
     Note that not all types of fuel cells available operate at a high enough temperature to be applicable for an
     anaerobic digester. Only those types that are viable are considered here.
53
     The waste heat can also be used to create steam and run a steam turbine, commonly referred to as cogeneration,
     or a combined cycle turbine with HSRG. These are not considered here as they requires large gas turbines not
     frequently needed for the “behind-the-meter” resource recovery market.
54
     “Combined Heat & Power Market for Opportunity Fuels,” Resource Dynamics Corp, 2004.



Iowa Utility Association – Joint Assessment Study                                                               84
Biomass Energy Generation Background Data
The primary resource for the installed cost of CHP technologies is the California’s Self-
Generation Incentive Program (SGIP).55 This program, funded by the main investor-owned
utilities of California, provides varying levels of incentives for individual customers to install
various dispersed generation technologies, including CHP, with a maximum capacity of 5 MW.
The program has been in effect since 2001 and has a publicly available database of all
installations, including generation technology, capacity, fuel, and total cost. For this assessment,
nameplate capacity is based on the average of the units installed through California’s SGIP for
anaerobic digesters.

Typical nameplate capacities for steam turbines vary widely. Although larger or smaller capacity
units can be installed for any of these technologies, a 4.8 MW unit is used as a proxy based on a
study for the Energy Trust of Oregon.56 . Different-sized units would have the same measure life
and capacity factors, but they may have different costs. Generally, smaller units are more
expensive on a $/kW basis. These values are summarized in Table 63. Note that no fuel costs are
used as it is assumed that fuel is generated and combusted on site. The measure life and capacity
factors were obtained from the literature.57 These values are assumed to be equivalent for Alliant
and MidAmerican.

                     Table 63. Biomass Energy Prototypical Generating Units
                                                    Capacity      Measure Life         Capacity
                       Technology
                                                      (kW)          (years)             Factor
             Anaerobic Digesters
             Reciprocating Engine                        662               20              0.9
             Microturbine                                206               15              0.9
             Fuel Cell                                   420               10              0.95
             Gas Turbine                               3,174               20              0.95
             Industrial Biomass
             Steam Turbine                             4,800               20              0.9


With these prototypical generating units, associated costs are determined from the SGIP database
or, for industrial biomass, literature searches.56 Installed costs include: planning and feasibility,
engineering and design, permitting, generator equipment costs, waste heat recovery costs,
construction, installation, interconnection, and service contracts. SGIP database costs were
reduced by 17% to remove included sales tax (7%) as well a 10% reduction based on higher
costs typical of the California market. 58




55
     http://www.cpuc.ca.gov/static/energy/electric/051005_sgip.htm
56
     “Sizing and Characterizing the Market for Oregon Biopower Projects,” prepared for Energy Trust of Oregon, by
     CH2MHill, 2005.
57
     “Gas-Fired Distributed Energy Resource Technology Characterization,” National Renewable Energy
     Laboratory, NREL-TP-620-34783, 2003.
58
     Based on general cost comparisons given in RS Means, 2007.



Iowa Utility Association – Joint Assessment Study                                                             85
It should be noted that, for generators used with anaerobic digesters, any of the four CHP
technologies could be used; thus, costs can vary widely. These costs are reported in Table 64. A
nominally constant installed cost is assumed, and no administration costs are included in total
cost. Together with the discount rate, this allows a full life-cycle cost analysis of the resource.

                    Table 64. Costs for Technologies Considered (2007 Dollars)
                                                      Installed Cost     Annual O&M
                                Technology
                                                          ($/kW)        Costs ($/kW/yr)
                        Anaerobic Digesters
                        Reciprocating Engine (RE)        $1,761               $79
                        Microturbine (MT)                $3,402               $71
                        Fuel Cell (FC)                   $6,829               $17
                        Gas Turbine (GT)                 $2,022               $58
                        Industrial Biomass
                        Steam Turbine (ST)               $1,800               $39



Biomass Energy Technical Potential
The technical potential for biomass and biogas assumes all technologies will be adopted in all
available customer sites to meet their average annual electric demands, regardless of cost or
other market barriers. This applies to all sites that may use anaerobic digesters and all industrial
biomass-producing facilities. These two sectors, however, need to be treated separately. To
derive this potential, each utility’s 2006 customer database was used; as such, the 2018 technical
potential given was ramped up from the first-year load. Details on the technical inputs (cost,
capacity factors, etc.) can be seen in Table 63 and Table 64. Technical potential by resource
category at generation is given in Table 65.

Anaerobic Digesters. The best candidates for anaerobic digesters include animal farms (dairy or
swine), landfills, and wastewater treatment facilities. For farms, the amount of biogas that can be
generated is directly related to the number and type of animals on site. Based on typical
collection systems, a study by the Environmental Protection Agency (EPA) assumes that one
cow will generate 2.5 kWh/day and that one pig will generate 0.25 kWh/day. 59 Given size
constraints, it is likely that only farms with more than 500 head of cattle or 2,000 head of swine
will install a generator. Based on the number and average size of farms within each utility’s
territory, overall potential is calculated.60,61

For wastewater treatment facilities, the population served by a particular facility will determine
the expected generation output. The EPA maintains a database of all wastewater treatment
facilities and their current and future design flows. A study by Federal Energy Management
Program assumes approximately 1 million gallons of waste per day (1 MGD) can produce about


59
     “Market Opportunities for Biogas Recovery,” EPA-430-8 -06-004, http://www.epa.gov/agstar
60
     http://www.nass.usda.gov/Census_of_Agriculture/index.asp
61
     “Sizing and Characterizing the Market for Oregon Biopower Projects,” CH2MHill for Energy Trust of Oregon,
     2005.



Iowa Utility Association – Joint Assessment Study                                                          86
35 kW of energy; as such, generally 3 MGD is the minimum waste flow before an anaerobic
digester will be installed.62 Thus, only wastewater treatment facilities with at least 3 MGD flow
(current or future) are included in the potential.

Finally, for landfills, the EPA Landfill Methane Outreach Program (LMOP) encourages the
implementation of generators at landfills. As part of this program, a database of participating and
candidate landfills, based on waste-in-place and throughput, is available by state (with zip code
resolution).45

Industrial Biomass. Industrial biomass potential is based on customers in the four key biomass-
producing industries: wood products, food, paper, and chemical manufacturing. The utility
customer database was used to determine the overall load associated with these industries. For
simplicity, the electric load for each customer was grouped into a bin (e.g., 200 kW – 499 kW or
500 kW – 999 kW average annual electric load). For buildings with a load between 1 MW and
5 MW, an average load of 2.5 MW is assumed; for those with average annual load larger than
5 MW, the actual customer load was taken from the customer database.

                  Table 65. Biomass Energy Technical Potential (GWh in 2018)
                                     by Resource Category
                         Technology            Alliant     MidAmerican         Total
                     Anaerobic Digesters          2,874        2,420             5,294
                     Industrial Biomass           3,190        1,650             4,840
                     Total                        6,064        4,070            10,134



Biomass Energy Market Potential
The market potential provides an analysis of what the market may accept, but not all of this is
necessarily economically feasible. Market potential is based on adoption rates within other
programs. This analysis is fairly independent of technical potential, but produces reasonable
results based on adoption rates through other programs.

Anaerobic digesters. The market potential for anaerobic digesters was based on the adoption rate
within SGIP, approximately 1% overall of program implementation. 63 Separate adoption rates
were calculated for the different generation technologies. For small generators (<1 MW,
reciprocating engines, microturbines, and fuel cells) the adoption rate is assumed to be the same
as that seen in California, while for large generation (>1 MW) the adoption rate is assumed to be
equal between reciprocating engines and gas turbines. The estimated total market potential for
anaerobic digesters is about 44 GWh in 2018.



62
     http://www1.eere.energy.gov/femp/pdfs/bamf_wastewater.pdf
63
     Note this is less than the ~4% of technical potential (after 20 years) that was estimated in “CHP Market
     Potential in the Western United States,” Energy and Environmental Analysis, Inc, ORNL Report:
     B-REP-05-5427-013, 2005. However, this adoption includes non-renewable CHP and large-scale generators
     (>20 MW), which would increase the overall percentage.



Iowa Utility Association – Joint Assessment Study                                                         87
Industrial Biomass. This potential as a fraction of technical (2%) is expected to be about twice
that as for anaerobic digesters, based on greater familiarity, lower cost, and ease of
implementation of industrial biomass. The projected growth in U.S. electricity generation from
industrial biomass was used as the basis for growth in generation by biomass within each
utility’s industrial sector.64 The industrial biomass growth is normalized by the ratio of the
utility’s industrial electrical load to the U.S. industrial load. The potential is based on the four
key biomass-producing industries (lumber, food, pulp and paper, and chemical manufacturing).
The estimated total market potential for industrial biomass is about 110 GWh in 2018.

Resource Potentials

The results of this analysis indicate a cumulative market potential of 155 GWh from all biomass
and biogas by 2018, with slightly higher potential for Alliant (81 GWh) compared to
MidAmerican (74 GWh). Levelized costs ($/kWh) are shown in Table 66 for each technology,
calculated using costs from Table 64 and a nominal discount rate of 4.81%. As evident by their
levelized costs, not all these technologies are necessarily cost effective. Total market potential is
around 1.5% of the technical potential.

                Table 66. Biomass Energy Market Potential (GWh) by Sector in 2018
                                          Industrial
                                                                        Anaerobic Digesters
                                          Biomass
               Utility                                                                                        Total
                                            Steam            Gas        Recip.       Micro-
                                                                                                 Fuel Cell
                                           Turbine         Turbines     Engine      turbine
 Alliant                                          55              0.3          10           13          3.2         81
 Mid-American                                     55              0.0           7            9          2.3         74
 Total                                          110               0.3          16           22          5.6        155
 % of 2018 IUA electric sales                 0.26%            0.00%       0.04%        0.05%        0.01%      0.36%
 Levelized Cost ($/kWh)                        $0.02           $0.03        $0.03        $0.05       $0.11
 Individual results may not sum to total due to rounding



Clean Energy
Clean energy consists of energy generation options that do not consume a hydrocarbon-based
fuel. Namely, photovoltaics, small hydro, and small wind. Each resource is unique and,
consequently, the technical and market potentials are calculated differently.

Clean Energy Background Data
The installed costs and operation and maintenance costs (O&M) for the three clean energy
technologies are shown in Table 67. Also included are expected measure life and capacity
factors. Capacity factors are an indication of the percentage of the year energy will be produced.
Further details for each technology are given below.



64
     From Energy Information Administration (EIA) 2007 Annual Energy Outlook.



Iowa Utility Association – Joint Assessment Study                                                                     88
       Table 67. Costs, Measure Life and Capacity Factor for Clean Energy Resources
                                  Installed Cost       O&M Cost
             Technology                                                    Measure Life   Capacity Factor
                                      ($/kW)           ($/kW/yr)
      Building PV                      $9,000              $100                    25           0.14 ( res)
                                                                                                0.12 (com)
      Small Hydro 65                   $4,862               $457                   40            0.5
      Small Wind 66                    $3,700                $20                   25            0.21


Building PV

On-site PVs consist of solar electricity-generation from building-mounted photovoltaic panels.
PV systems are weather-dependent and rely on the sun to generate electricity. This study focuses
on renewable-electricity generation potential from rooftop residential and commercial buildings.
PV systems include an array of solar electric modules, an inverter (DC to AC), and a balance of
systems. These systems do not have battery back-up equipment and are completely connected to
the utility (grid-tied). PV generation is a whole-building electricity generation resource and
typically only offsets a portion of baseline loads. In most cases, PV is considered a secondary
source of a building’s energy needs. When excess PV electricity is generated (more than the
building’s loads), it is fed back into the grid. This depends heavily on the PV system size and
current weather and, for residential and commercial customers, generally occurs when the
building is not occupied.

Three primary PV technologies considered are: (1) mono-crystalline (single crystalline cell);
(2) poly-crystalline (multi-crystalline cell); and (3) amorphous thin-film. These three
technologies currently dominate the solar market.67 Efficiencies of these technologies are
improving annually and are accounted for in this study. This study does not include large PV
generation facilities that operate to sell the majority (or all) of their power to the grid and
emerging PV technologies.

The PV Watts performance calculator, developed by the National Renewable Energy Laboratory,
is used to determine the capacity factor. 68 The amount of solar insolation (i.e., the measure of
solar energy received on a given surface area in a given time), based on weather stations,
determines the performance potential for the region. All commercial and multifamily buildings
are fixed with 0.0° array tilt (flat roof), while single-family and manufactured homes are fixed at
18.5° tilt (4/12 pitch). With this variance in array tilt, two resulting capacity factors result. For
the commercial sector, the capacity factor is 0.12, while it is 0.14 for the residential sector.

PV Energy Costs. The primary and secondary resources for PV installed costs are from the
California Energy Commission (CEC), the Energy Trust of Oregon (ETO), the U.S. Department
of Energy (DOE), and other on-line sources. Cost analysis for PV installation of other programs



65
     Average cost. See Appendix E for detailed information.
66
     Average cost. See Appendix E for source information.
67
     EIA, based on photovoltaic cell and module shipments by type, 2005.
68
     http://rredc.nrel.gov/solar/codes_algs/PVWATTS/



Iowa Utility Association – Joint Assessment Study                                                             89
results in an average installation cost in 2006 of $9/W, which is assumed in this analysis.69 Other
technical data have been acquired from multiple primary and secondary resources to determine
measure life, and O&M costs. A PV system has a measure life of 25 years. 70 O&M costs include
inverter replacement every ten years and seasonal module washing.71

Small Hydro

Hydraulic power can be captured wherever a flow of water falls from a higher level to a lower
level. This may occur where a stream runs down a hillside, a river passes over a waterfall or
man-made weir, or where a reservoir discharges water back into the main river. The vertical fall
of the water is known as the “head,” and this, along with the flow rate, determines the power
output.72 The primary resource used in this study to evaluate potential sites for hydro
development was the Virtual Hydropower Prospector (VHP), which is available through the
Idaho National Laboratory.73 This is a GIS-based tool that allows users to identify existing small
hydro sites and additional potential. The focus of this analysis was on Low-Power Hydro, up to
the net metering limit of 500 kW.

One of the main differences between small/micro hydro (< 500 kW) and larger systems is that
small hydro is almost always run-of-river. Run-of-river hydro plants do not require dams. The
water flowing in the stream is channeled into pipes (or a penstock) and then into a turbine, which
generates electricity. The water is then returned to the stream downstream from the turbine.

The environmental footprints of run-of-river facilities are much lower than those of larger hydro
plants, which require large storage reservoirs. No land needs to be flooded to create a reservoir
for the plant, but a small weir may be installed to help regulate flow.

The benefits of small hydro are many and include:
      High efficiency (70% – 90%).
      A high capacity factor (typically 50%).
      A high level of predictability, varying with annual rainfall patterns.
      Slow rate of change for output power, which varies only gradually from day to day (not
       from minute to minute).
      A good correlation with summer cooling demand.




69
     “Solar Trends: California Energy Commission” by SunPower Consulting LLC provided cost analysis, August
     2006, ETO, and DOE.
70
     Data was averaged from the following sources: NREL, NW Power, and Conservation Council, and typical
     warranty periods.
71
     NREL, “A Review of PV Inverter Technology Cost and Performance Projections”, 2006.
72
     Further data on the power calculation is given in Appendix E.
73
     http://hydropower.inl.gov/prospector



Iowa Utility Association – Joint Assessment Study                                                       90
      A long-lasting and robust technology; systems can be engineered to last for 50 years or
       more.
      Environmentally benign; fish and other wildlife are not affected by the installation.

Hydro Energy Costs
Installing a hydro system includes the following costs: Penstock, Intake, Powerhouse, Generating
Equipment, Access Road, Switchyard, and Transmission Line. In addition, a percentage of these
is included for Engineering (20%) and Contingency (30%).

Costs vary considerably according to the size of the system installed, with the cost per kW going
down as the system size increases. For this study, costs were taken from a study prepared for
BC Hydro that included all of the costs listed above.74 Data from sites less than 500 kW in
capacity and with less than three miles of transmission required to be installed were used.
Estimated installed costs were $4,862/kW, with additional O&M costs of $457/kW per year
(calculated as 9.4% of installed cost). Details on the cost analysis are provided in Volume II,
Appendix E.

Small Wind

Wind energy is converted to mechanical or electrical energy through the use of a wind turbine.
Wind energy is an intermittent resource, meaning that the energy output varies and is
unpredictable. Despite the intermittency of the wind, the wind energy industry is growing.

The total installed capacity of small wind (<100 kW) in the U.S. is estimated to be about 62 MW
as of 2006.75 According to the American Wind Energy Association (AWEA), Iowa is ranked
tenth in the U.S. for wind energy potential. In terms of installed wind capacity, Iowa is the third
state, behind Texas and California, with a total installed wind capacity (including utility-scale
wind farms) of 931 MW as of the end of 2006.76

Small wind turbines are generally defined as having an installed capacity of up to 100 kW. As
noted above, however, small wind turbines for this analysis were assumed to have an installed
capacity from 1 kW to 500 kW. In addition to the small wind turbines used in this analysis, many
new small turbines (around 1 kW) have been developed in recent years. Southwest Windpower’s
Skystream 3.7™, with an installed capacity of 1.8 kW, is an all-inclusive wind generator ideal
for homes and small businesses.77 Another small turbine, the Swift Rooftop Wind Energy
System™ by Renewable Devices, is a 1.5 kW generator that produces up to 3,000 kWh of



74
     Green Energy Study for British Columbia Phase 2: Mainland; Small Hydro, October 2002, Prepared for BC
     Hydro by Sigma Engineering Ltd.
75
     Compiled from American Wind Energy Association. Home and Farm Wind Energy Systems: Reaching the
     Next Level. AWEA. June 2005. and American Wind Energy Association. AWEA Small Wind Turbine Global
     Market Study 2007. AWEA. July 2007.
76
     Wiser, R. and M. Bolinger (LBNL). Annual Report on U.S. Wind Power Installation, Cost and Performance
     Trends: 2006. U.S. Department of Energy- Energy Efficiency and Renewable Energy. May 2007.
77
     http://www.skystreamenergy.com/skystream/



Iowa Utility Association – Joint Assessment Study                                                      91
electricity a year.78 It should be noted that small wind rooftop systems can cause issues with
vibrations and turbulence.

The AWEA Small Wind Turbine Global Market Study 2007 conducted a survey with many
players in the small wind industry, including researchers, component vendors, manufacturers,
engineers, consultants, utilities, local government offices, and dealers/distributors/installers. The
survey found that the top market barriers to installing small wind turbines were economics/costs
to the customer. Additional key barriers included restrictive zoning and permitting rules, costs,
and lack of financial incentives. Respondents were also asked about state priorities and the top
two areas of improvement for each state. For Iowa, respondents listed rebates as the first priority
and interconnection as the second. The study also found that the fastest growing market segment
is grid-connected residential scale turbines (1 kW – 10 kW). 79

Multiple incentives are currently available to owners of wind energy systems in Iowa, including
tax credits, tax exemptions, and loan programs. Volume II, Appendix E provides a listing of the
current incentives available.

Small Wind Energy Costs
The cost for a wind turbine varies by the size of the system installed. In general, as the installed
capacity of wind turbines increases, the installed cost per kW decreases. Costs are assumed to be
nominally constant. However, it should be recognized that costs may increase due to tighter steel
supplies. Costs were taken primarily from turbine manufacturer and distributor websites or
discussions with manufacturers. Details on the cost analysis and distribution of turbines
according to size and customer sector are also provided in Volume II, Appendix E.

Clean Energy Technical Potential
The technical potential for all clean energy resources is shown in Table 68. Below are details on
the derivation for this technical potential for each of these technologies.

            Table 68. Technical Potential of Clean Energy Resources by Technology
                                        (GWh in 2018)
                         Technology                 Alliant   MidAmerican     Total
                  Building PV                       17,259         15,629    32,888
                  Small Hydro                           504           652     1,156
                  Small Wind                         9,490          9,218    18,708
                  Total                             27,250         25,499    52,749




78
     http://www.renewabledevices.com/swift/
79
     American Wind Energy Association. AWEA Small Wind Turbine Global Market Study 2007. AWEA.
     July 2007.



Iowa Utility Association – Joint Assessment Study                                                 92
Building PV

Analysis of this technical potential is based on rooftop applications only. This provides a
conservative estimate since other applications such as ground or pole mounted PV, awnings, and
car ports are not considered. This estimate of technical potential considers the physical
limitations due to roof area, shading, orientation, and expected building growth. The PV
methodology is diagrammatically displayed in Figure 18, showing how different inputs are used
to estimate technical potential. Each input will be described in detail below, with further details
available in Volume II, Appendix E.

                                  Figure 18. PV Potential Methodology




Existing Stock and Forecasting. Available square footage of roof area is based on site visits,
surveys, and data mining results performed as part of this study for commercial and residential
buildings in Iowa. The load forecast is used to estimate the growth in the building stock.

PV Commercial Assumptions. The following assumptions are comparable to and consistent with
other studies:
         All commercial rooftops are considered flat (0° pitch).
         30% of all roofs are unavailable (20% due to obstructions and equipment, 10% space
          lost due shading from the equipment).
         All building types are equally distributed across all zip codes.

PV Residential Assumptions. The following assumptions are based on field experience and
remain consistent with other studies:




Iowa Utility Association – Joint Assessment Study                                               93
          Single-family and manufactured households typically have 4/12 (18.5 o) pitch roofs.
          Multifamily structures have flat roofs (0o pitch).
          25% of roofs face south.
          81% of roof areas are unavailable due to shading.
          All building types are equally distributed across all zip codes.

PV Power Density Assumptions. PV cell technology evolves over time, and efficiency
continually improves. According to the DOE, cell efficiency is projected to improve at an
average rate of roughly 2.1% a year across all three classes of technologies. This assumption is
comparable with other studies. Conversely, there is also a performance degradation of 1%
efficiency per year. Both of these assumptions are included in this analysis.

This analysis also takes into account market shares of competing solar cell technologies: mono-
crystalline, poly-crystalline, and amorphous ‘thin-film,’ from which a weighted average is
calculated to determine an overall efficiency. In addition, it is important to account for the space
between modules needed for racking materials and installation requirements for the entire array,
increasing the overall footprint. To adjust for this, the power density (W/sq.ft.) is reduced by
20% to give the total system array efficiency. This result is applied to the projected increase in
cell efficiency to determine the power density annually.

The system power density multiplied by the useable square footage for each building type results
in the total name plate capacity (kW) or the total DC kW installed.

PV Watts Performance Calculator. As noted earlier, the PV Watts performance calculator is
used to determine the capacity factor.80 The amount of solar insolation available is based on
Des Moines’ weather station, which is equivalent to that used in the energy-efficiency building
simulation models. The weighted average capacity factor by commercial and residential
buildings and utility was calculated at 0.13.

Small Hydro

The technical potential for small hydro was calculated based on the potential sites listed in the
Hydropower Prospector. Data were downloaded for all suitable potential small hydro sites in
Iowa. These data included capacity, county, and other information, such as head and stream
flow. They were then analyzed to derive hydro potential by county, adding up the potential for
all four types of installations.
Projects were deemed to be feasible and included in the inventory of potential sites if they
fulfilled the following criteria:




80
     Developed by the National Renewable Energy Laboratory, the PV Watts Performance Calculator uses hourly
     Typical Meteorological Year (TMY) weather data and a PV performance model based on Sandia National
     Laboratories' PVFORM to estimate monthly and annual AC energy production (kWh).



Iowa Utility Association – Joint Assessment Study                                                       94
          Hydropower potential ≥ kW.
                                 10
          Did not lie within a zone in which development was excluded by federal law or
           policy.
          Did not lie within a zone making development highly unlikely because of land-use
           designations.
          Did not coincide with an existing hydroelectric plant.
          Was within 1 mile of a road.
          Was within 1 mile of part of the power infrastructure (power plant, power line, or
           substation) or within a typical distance from a populated area for plants of the same
           power class in the region.

The potential power output for each site was calculated using the following assumptions:
          Project location: optimal based on hydraulic head capture.
          Penstock length: optimal based on capturing 90% of hydraulic head captured with
           longest, typical penstock length, based on existing low-power or small hydro plants in
           the region.
          Flow rate: lesser of the following: half the stream reach flow rate or flow rate
           required to produce an annual average power of 26,280 MWh using hydraulic head
           corresponding to optimal small hydro penstock.

There are several assumptions in this study that indicate that actual potential may be higher than
the study is predicting. Specifically:
          The assumption of using half the stream reach flow rate is very conservative. For
           example, a small hydro potential study produced for BC Hydro estimates 90% of
           stream flow is useable, deeming that only 10% of flow needs to be retained to protect
           fish. Therefore, the actual potential at each site could be as much as 80% higher than
           the potential given in the Hydro Prospector.81
          The study did not include potential for hydrokinetic technologies in cases where there
           is little head available but sufficient velocity and stream depth to support such
           hydrokinetic technologies.
          The study did not include sites with less than 10 kW of capacity as they are not
           included in the Hydropower Prospector. There could be many more small sites with
           potential for development not covered in this study.




81
     Details of the study that produced the site statistics available in the Hydro Prospector are given in the report
     Feasibility Assessment of the Water Energy Resources of the United States for New Low Power and Small
     Hydro Classes of Hydroelectric Plants, January 2006, Prepared for the DOE, Office of Energy Efficiency and
     Renewable Energy by Idaho National Laboratory.



Iowa Utility Association – Joint Assessment Study                                                                 95
Potential from Hydro Prospector
The data for all potential projects in the state of Iowa were taken from the Hydropower
Prospector on-line tool. Sites were included that had more potential than the maximum allowable
size for a behind-the-meter system, but capacity was set to 500 kW, assuming part of the
potential could be utilized. The table below shows the number of sites and the capacity range for
each site category.

                                       Table 69. Potential Hydro Sites
                                                                        Capacity (kW)
                  Technology               No. Sites
                                                          Minimum        Maximum           Average
       Micro Hydro                            1,941            20             200               60
       Small Hydro                               66           500             500             500
       Low Power Conventional                   131           202             500             377
       Low Power Unconventional                 260           200             500             374


The total amount of potential by technology class is provided below:

                  Table 70. Technical Potential by Technology Class (GWh in 2018)
                                                                        Total Feasible   Total Adjusted
                         Low Power         Low Power
        Microhydro                                        Small Hydro   for Applicable     Technical
                        Conventional     Unconventional
                                                                          Counties         Potential
            513                217             426           145             1,300           1,156


The potential for each utility was then calculated by multiplying the potential for each county by
the percentage of that county within the services territories of Alliant and MidAmerican. This
reduced the total potential from 1,300 GWh to 1,156 GWh, accounting for some counties having
areas neither in MidAmerican’s nor Alliant’s service areas.

It should be noted that these percentages may not agree with the distribution of potential hydro
sites within a county as the exact location of the utilities’ operating areas within each county was
not known. Therefore, maps of each county have been provided in Volume II, Appendix E that
show the locations of potential sites for each county. A detailed comparison of each utility’s
operating areas with these maps would determine exactly how much potential exists for each
utility in each county.

To calculate generation per month, stream flow data were taken from the U.S. Geological
Service website.82 These data show the stream flow for each month for different streams in each
county and were used to estimate the proportion of total annual generation for each month in the
year by first calculating the percentage of annual stream flow in each month for the sample




82
     http://waterdata.usgs.gov/ia



Iowa Utility Association – Joint Assessment Study                                                         96
stream in that county, then applying that percentage to the annual generation for the whole
county.83

This analysis showed the share of annual generation is distributed differently depending on in
which part of the state the county lies. In addition, the total potential is much lower in winter
than in summer, reaching a low in January of 19% of the peak output occurring in June. Further
details are given in Volume II, Appendix E.

Small Wind

The technical potential for small wind assumes all technologies will be installed at all available
customer sites, regardless of cost or other market barriers. This applies to all sites under the
following characteristics:
         Sites with a wind resource greater than Class 2.
         Sites with a population density less than 100 persons per square mile.
         Sites greater than 2 miles from an airport.
         Sites not located on National Park lands or wetlands.

All exclusions are subtracted from 100% to gain the percent inclusion for each county. This
percentage is applied to both utilities to gain an estimate of technical potential. Because of the
high level of this study, exclusions for each county apply to both utilities because the high-
exclusion counties primarily belong to one utility or the other (e.g., the majority of Polk County
is under MidAmerican’s service territory). All exclusions are intended to provide a conservative
estimate of technical potential.

Wind Resource. Wind resource maps provide valuable data for assessing wind power density for
a given area. The Iowa Wind Energy Institute (IWEI) has completed a wind energy assessment
for Iowa. Data were collected around the state from 1996 – 2000. Maps of Iowa’s wind resource
were generated as part of an Iowa Energy Center grant.84 The map of the estimated average
annual wind speeds is shown in Figure 19.




83
     The calculation can be represented as: Monthly generation (kWh) = kW potential x 8760 hours/year x
     percentage of annual stream flow in the month.
84
     Grant No. 93-04-02.



Iowa Utility Association – Joint Assessment Study                                                   97
                   Figure 19. Estimated Average Annual Wind Speeds for Iowa




A wind resource of at least DOE Class 2 (corresponding to wind speeds of between
5.6 meters/sec and 6.4 meters/sec at 50 meters above ground) is needed to operate today’s
turbines. The majority of Iowa has at least Class 2 wind speeds; however, some parts of
northeastern Iowa have lower-than-needed wind speeds (corresponding to purple shades on the
map). Therefore, exclusions have been made for the following counties:
          Allamakee (90%)                                               Winneshiek (20%)
          Clayton (90%)                                                 Fayette (10%)
          Dubuque (50%)                                                 Delaware (5%)
          Jackson (40%)                                                 Jones (5%)

These exclusion percentages are an estimation of the area of each county with a wind resource
less than Class 2. This map shows average wind speeds, but it should be recognized that wind
energy is an intermittent resource, and, thus, the estimated output varies by month. Wind energy
output in Iowa is greatest in the spring months (March and April) and lowest in the summer
months (July and August), based on wind resource from the Wind Turbine Output Calculator.

Population Density. Small wind turbines are not a viable option for heavily populated regions
due to the lack of land available for the turbines and the interruption of air flow by tall
buildings.85 Population density was found using the 2000 Population Density by Township and
Place within Counties in Iowa map (see Volume II, Appendix E) from the Office of Social and


85
     Building integrated turbines are gaining greater acceptance in Europe and may be deemed a viable option in the
     US in the future, but have not been included in the analysis here due to insufficient level of acceptance in the
     US and insufficient availability of data.



Iowa Utility Association – Joint Assessment Study                                                                 98
Economic Trend Analysis (SETA).86 Regions within each county that contained more than 100
persons per square mile were excluded from the technical potential. For most on-site wind
turbines, an area of one acre is needed. Therefore, excluding any land area including more than
100 persons per square mile provides a conservative estimate (100 persons per square mile equal
to about 0.2 persons per acre). Because these exclusions were estimated by land area and the
majority of utility customers likely reside in the densely populated areas, a multiplier of 1.2 was
added to the exclusion estimate to be conservative. Counties with the greatest population density
clusters and most affected by this exclusion included (in order of high to low exclusion):
          Polk County, Des Moines city (75%)
          Scott County, Davenport city (50%)
          Black Hawk County, Waterloo and Cedar Falls cities (30%)
          Linn County, Cedar Rapids city (20%)
          Johnson County, Iowa city (20%)
          Pottawattamie County, Council Bluffs city (20%)
          Woodbury County, Sioux city (15%)
          Dubuque County, Dubuque city (15%)

These exclusion percentages estimate of the area of each county with a population density
greater 100 persons per square mile.

Proximity to Airports. Wind turbine sites within 2 miles of an airport may be subject to tower
height regulations by the Federal Aviation Administration (FAA).87 Small wind turbines are
unlikely to be affected by these height restrictions, but this assumption has been made to ensure a
conservative resource estimate. Therefore, some exclusions have been made for land surrounding
airports in Iowa. Because the average county size in Iowa is about 570 square miles, an exclusion
of 3% is added to any county with an airport in its boundaries.

Sensitive Areas. Sensitive areas include National Park land and wetlands. Two National Park
Service areas are located in the state of Iowa: Effigy Mounds National Monument – Harpers
Ferry, IA (Allamakee County) and Herbert Hoover National Historic Site – West Branch, IA
(Cedar County). To account for these sensitive areas and possible buildings located therein,
exclusions were applied to each county based on National Park land area to county area:88
Allamakee County (0.6%) and Cedar County (0.05%). Because this study pertains only to
behind-the-meter applications, no exclusions were made for wetlands under the assumption no
buildings reside on land that consists of 100% wetlands.




86
     http://www.seta.iastate.edu/
87
     AWEA. http://www.awea.org/smallwind/toolbox2/factsheet_visual_impact.html
88
     Effigy Mounds National Monument approximately 2,500 acres; Allamakee County approximately 640 square
     miles (410,000 acres); Herbert Hoover National Historic Site approximately 190 acres; Cedar County
     approximately 580 square miles (371,000 acres).



Iowa Utility Association – Joint Assessment Study                                                     99
Clean Energy Market Potential
Market potential by technology is given in Table 71. The total potential from all resources across
IUA territory is 135 GWh. Note none of the clean energy options are likely to be cost effective,
and the current market potential is purely from customers willing to accept long payback times.
Details on derivation of this market potential are given below for each technology.

                    Table 71. Clean Energy Market Potential (GWh) by Sector in 2018
                                                Building PV                    Small Hydro             Small Wind
                   Sector
                                           Alliant       MidAm            Alliant       MidAm     Alliant        MidAm
    Residential                               5.1           3.7              0.7           0.9         22.0         21.0
    Commercial                                7.8           8.1              2.0           2.6         26.0         26.0
    Industrial                             ---            ---                0.3           0.4          3.7          3.5
    Total                                   12.9           11.8              3.0           3.9         52.0         51.0
    % of 2018 IUA sales                              0.06%                         0.02%                    0.24%
    Levelized Cost ($/kWh)                         $0.62                          $0.16                    $0.15
    Individual results may not sum to total due to rounding


All clean energy options are intermittent resources. For Small Hydro, peak power generation
occurs in late spring; Small Wind has its peak during the winter months; and PV peaks in the
summer. As such, PV and hydro have good coincidence during system peak periods. The
variation in market potential over the year for each technology is shown in Figure 20.

                   Figure 20. Clean Energy Average Monthly Market Potential (2018)

                    16,000


                    14,000


                    12,000


                    10,000
                                          Hydro
             MWh




                     8,000                Wind
                                          PV
                     6,000


                     4,000


                     2,000


                       -
                              Jan    Feb Mar       Apr    May Jun   Jul     Aug Sep    Oct   Nov Dec




Iowa Utility Association – Joint Assessment Study                                                                          100
Although none of the clean energy resources are likely to be considered cost effective, changes
from other factors may affect the payback period, even without the resource becoming economic.
These factors may include government incentives, technological breakthroughs that reduce costs,
and future energy costs. It is difficult to quantify the effect of payback period on adoption, but
decreasing the payback period to less than ten years can have as much as a two- to three-fold
increase in market potential.

Building PV

Market potential for PV is based on solar programs around the country. The following sources
were used to determine the adoption rate of implementing PV installations within their regions:
          New Jersey’s Clean Energy ProgramTM
          Connecticut Clean Energy Fund
          Energy Trust of Oregon
          Florida Energy Office’s Solar Energy Systems Incentives Program
          Massachusetts Technology Collaborative’s Small Renewables Initiative
          California Energy Commission’s Renewable Energy Program with San Diego Gas &
           Electric89

A program’s success is, in part, dependent on the current incentives available. Incentives can be
provided by one or more of the following: federal tax incentives, state tax incentives, utility buy-
downs, production-based incentives, and other rebates. Volume II, Appendix E lists several state
programs from around the country offering PV incentives.90 Incentives have become critical in
promoting and creating a successful PV program. Depending on the type and size of incentive, it
can affect the adoption rate. In most instances, the total incentive is roughly 50% of the installed
cost for the residential market and 75% for the commercial sector. The market potential is based
on existing programs implementing these incentive levels and is calculated from their adoption
rates. The resulting market potential is less than 1% of the technical potential. Iowa has a market
potential of 0.009% of the technical potential.91

It should be noted that the market potential percentage may vary by specific regional areas, as
there are varying degrees of acceptance and political climate. The adoption rate heavily depends
existence of current programs, “green” culture, understanding of technology and meteorological
considerations as well as other economic factors.

The resulting market potential is 25 GWh. The levelized cost for PV is $0.62 /kWh.




89
     “Technical Potential for Rooftop Photovoltaic in the San Diego Region,” by Scott Anders of the Energy Policy
     Initiatives Center, University of San Diego School of Law and Tom Bialek of San Diego Gas & Electric, 2005.
90
     Database of State Incentives for Renewables and Energy Efficiency (DSIRE) www.dsireusa.org.
91
     Similar to Oregon and Connecticut’s market potential.



Iowa Utility Association – Joint Assessment Study                                                            101
Small Hydro

The market potential for small hydro is difficult to analyze because very few utility or state
programs exist promoting hydro as a customer-based renewable resource. Currently in North
America, the Energy Trust of Oregon, BC Hydro, and Holy Cross Energy (Colorado) all have
some sort of program promoting small hydro.92 However, data available on program installations
and potential are sparse, and thus could not be used for this assessment. Instead, a similar market
to technical potential percentage as wind was used (0.6%), applied equivalently across the
service territories. This resulted in a total market potential of 6.9 GWh.

Small Wind

The market potential estimates were based primarily on the two California programs offering
rebates for small wind technologies: the SGIP and the Emerging Renewables Program (ERP).
New Jersey’s Customer On-Site Renewables Program (CORE) was also reviewed to aid in the
market potential estimates. The California ERP began in 1998 and the SGIP began in 2001.
Since their inceptions, the research team estimated the California programs have funded about
0.35% of the small wind technical potential in that state. Because this study is a ten-year
potential study, the technology is likely to see substantial cost decreases and improvements, and
permitting acceptance could also improve during that time. Therefore, this study assumes the
market potential for 2018 is double the market to technical potential percentage for California’s
previous programs, or 0.6% of the estimated technical potential. This value was applied to all
counties in Iowa for both Alliant and MidAmerican.

Passive Efficiency Resources
Passive energy resources were evaluated equivalently to other energy-efficiency resources. For a
full description of methodology, please see Volume II, Appendix C-1. Detailed descriptions of
these measures are provided in Volume II, Appendix A. These passive efficiency measures are
applicable to the residential and commercial sectors, and provide water heating (solar water
heating, residential only) or HVAC savings. Except for deciduous trees, the passive solar
measures are only considered for new construction.

                  Table 72. Passive Efficiency Potentials by Sector (GWh in 2018)
                                                                                        Economic As
                                     2018 Baseline           Technical     Economic
                  Segment                                                               % of Baseline
                                         Sales               Potential      Potential
                                                                                           Sales
               Residential                 10,819                    368         354           3.3%
               Commercial                   9,086                    101          99           1.1%
               Total                       19,905                    469         453           2.3%
               Note: Results may not sum to total due to rounding.




92
     Holy Cross Energy restricts incentives to installations with capacities < 25 kW.



Iowa Utility Association – Joint Assessment Study                                                       102
              Table 73. Passive Efficiency Potentials by Sector (1000 DTh in 2018)
                                                                                                  Economic As
                                     2018 Baseline           Technical            Economic
                  Segment                                                                         % of Baseline
                                         Sales               Potential            Potential
                                                                                                     Sales
               Residential                65,968                     680               595              0.9%
               Commercial                 34,475                      53                49              0.1%
               Total                     100,443                     732               644              0.6%
               Note: Results may not sum to total due to rounding.



Residential Sector
The measures and levelized costs (averaged across all customer segments and vintages) are
provided in Table 74. Solar attic fans, window overhangs and deciduous trees do not offer any
heating savings; thus, their levelized costs are not given.

        Table 74. Levelized Costs of Passive Efficiency Measures in Residential Sector
                                                                 Levelized Cost              Levelized Cost
                                Measure
                                                                    ($/kWh)                     ($/therm)
                 Solar Water Heater                                     $0.67                      $10.42
                 Solar Attic Fan                                        $0.72                       ---
                 Pellet (corn) Stoves                                   $0.00                        $0.00
                 Window Overhangs                                       $0.76                       ---
                 Trombe Walls                                           $0.14                        $2.37
                 Smart Siting                                           $0.33                        $5.45
                 Deciduous Trees                                        $0.05                       ---


The economic potential of passive efficiency measures in the residential sector is expected to be
354 GWh and 595 thousand DTh over ten years, corresponding to a 3.3% reduction of 2018
electrical residential consumption (Figure 21) and a 0.9% reduction in 2018 gas consumption. Of
the total economic potential, 149 GWh and 139,312 DTh are within Alliant’s service territory,
205 GWh and 367,148 DTh are within Mid American’s territory, and 88,574 DTh are within the
Aquila service territory.

Potentials, as split by end use for the residential sector, are shown in Figure 21 for electric. All
economic gas potential is in heating, so no pie chart is given. Additional details regarding
savings associated with specific measures assessed within each end use are provided in Volume
II, Appendix E.




Iowa Utility Association – Joint Assessment Study                                                                 103
                   Figure 21. Residential Sector Passive Renewable Resources:
                             Economic Electric Potential by End Use

                        C ooling
                         7 2%




                                                                      H eat Pum p
                                                                      2%


                                                           H eating
                                                             26%




Commercial Sector
The measures and levelized costs (averaged across all customer segments and vintages) are
shown in Table 75. As window overhangs and deciduous trees do not offer any heating savings,
there are no associated levelized costs.

       Table 75. Levelized Costs of Passive Efficiency Measures in Commercial Sector
                                                     Levelized         Levelized
                               Measure
                                                    Cost ($/kWh)      Cost ($/therm)
                     Window Overhangs                    $0.10            ---
                     Trombe Walls                        $0.01             $0.19
                     Smart Siting                        $0.38             $3.87
                     Deciduous Trees                     $0.01            ---


All passive energy measures in the commercial sector are under the auspices of passive solar
design techniques and impact HVAC usage. The economic potential of passive efficiency
measures in the commercial sector is expected to be 99 GWh and 49 thousand DTh over ten
years, corresponding to an 1.1% reduction of 2018 electrical commercial consumption (Figure
22) and 0.2% reduction in 2018 gas consumption (Figure 23). Of the total economic potential,
49 GWh and 6,384 DTh are within Alliant’s service territory, 50 GWh and 29,640 DTh are
within Mid American’s territory, and 12,747 DTh are within the Aquila service territory.

Potential, split by end use, is shown in Figure 22 and Figure 23 for the commercial sector,
electric and gas fuels, respectively. Additional details regarding the savings associated with
specific measures assessed within each end use are provided in Volume II, Appendix E.



Iowa Utility Association – Joint Assessment Study                                         104
                     Figure 22. Commercial Sector Passive Renewable Resources:
                                Economic Electric Potential by End Use



                          C ooling
                             85%

                                                                                 Heating
                                                                                 2%
                                                                                Heat Pump
                                                                                13%




                     Figure 23. Commercial Sector Passive Renewable Resources:
                                 Economic Gas Potential by End Use 93

                                     H eating
                                      67 %




                                                                       Boiler
                                                                       33%




Emission Reductions
Emissions reduction occur due to clean energy and passive efficiency measure installations. An
estimated emissions savings potential based on the market potential is shown in Table 76. If the
entire market potential of 453 GWh from clean energy and passive efficiency measures was
realized, about 440,463 tons of CO2, 1,462 tons of SO 2, 861 tons of NO x, and 0.01 tons of
mercury (Hg) would be abated annually.




93
     The “Heating” end use is savings for which a furnace is the primary space heating equipment.



Iowa Utility Association – Joint Assessment Study                                                   105
                          Table 76. Estimated Emissions Savings Potential94
                                       Iowa Emissions         Emissions            Emissions
                       Emission             Factor              Savings             Savings
                                          (lbs/MWh)           (Short tons)          (Tonnes)
                 CO2                         1,943.0            440,463.0           399,581.0
                 SO2                             6.45             1,462.0             1,326.0
                 NOx                             3.80               861.0               781.0
                 Hg                              0.0001                0.01               0.01




94
     Values estimated for Iowa from eGrid 2006 v2.1 State File (Year 2004 Data). Available at:
     http://www.epa.gov/cleanenergy/egrid/index.htm.



Iowa Utility Association – Joint Assessment Study                                                106

				
DOCUMENT INFO
Shared By:
Categories:
Tags:
Stats:
views:57
posted:5/11/2010
language:English
pages:126