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Research Opportunities for Chemical Engineers in Building

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					Process Energy Systems:
 Control, Economic, and
Sustainability Objectives

      Jeffrey J. Siirola
      Thomas F. Edgar

       FOCAPO/CPC 2012
         Savannah, GA

                            1
                Outline
• Elements of sustainability
• New emphasis on greenhouse gas emissions
• Carbon management by energy reduction
• Smart manufacturing, process control, and
  operations optimization
• Dynamic energy minimization
• Next generation power systems (smart grids)
• Thermal energy storage and process control

                                           2
       Elements of Sustainability
•   Health and safety
•   Environmental protection
•   Materials and energy efficiency
•   Product stewardship
•   Corporate citizenship
•   Triple bottom line


                                      3
    Sustainability Issues Addressed
            During Design
•   Inherent safety principles
•   High yield reaction chemistries
•   Material recovery and recycle
•   Heat integration
•   Multi-effect separation

• Carbon management remains particularly
  difficult and expensive
                                           4
  Proposed Legislatively
Mandated US GHG Reductions




http://www.wri.org/climate/topic_content.cfm?cid=4265
                                                        5
      CO2 Policy Alternatives
• Regulated CO2
   – Recent EPA announcement on reporting
     requirements
• Cap and Trade
  – Establishes firm but decreasing limits on CO2 emissions
  – Auctioning/trading of emissions permits
• Carbon Tax
  – Price predictability
  – Favored by large chemical companies
  – Apply to all carbon sources

                                                              6
CO2 Absorption/Stripping of
  Power Plant Flue Gas
           Use 30% of
         power plant output
    Flue Gas
  With 90% CO2
    Removal
                                                            CO2 for
                                                           Transport
                                                           & Storage




                                            Stripper
                 Absorber




                                                       LP Steam



     Flue                    Rich      Lean
     Gas In                 Solvent   Solvent


                                                                       7
  Base Case Carbon Capture and
    Sequestration Technology
• Post combustion monoethanolamine
  absorption
  – 30% parasitic energy requirement for coal-fired
    powerplant
  – >70% increase in electric power cost
• Chilled ammonia alternative
• DOE Carbon Capture Simulation Initiative to
  address and reduce commercialization risks

                                                  8
U.S. Industrial/Building Sector

• Industrial energy usage = 35 quads (total = 100
  quads)
• This sector accounts for about one-third of total
  U.S. GHG emissions
• By 2030, 16% growth in U.S. energy consumption,
  which will require additional 200 GW of
  electrical capacity (EIA)
• Energy efficiency goals of 25% reduction in
  energy use by 2030 (McKinsey and National
  Academies Press reports)
                                                 9
 Reducing Carbon Footprint in
       Process Plants
• Fuel swapping (natural gas for coal)
• Conversion to non-fossil energy sources (nuclear,
  solar, or biomass)
• Reduce energy requirements
  – Use less energy-intensive chemistry/unit operations
  – Increase heat and power integration
  – Retrofits difficult to justify economically unless
    accompanied by capacity expansion

  – Operate processes with additional objective to
    minimize energy consumption                           10
 Perspective of this Presentation

• Most carbon dioxide emission comes from
  fossil fuel combustion
• Maximize energy efficiency ≡ minimize
  carbon footprint
• Focus on process operation and control (not
  design)
• Assume use of existing infrastructure to
  maximize thermal efficiency
• Progress requires a systems approach
                                            11
    Optimization of Operations

•   Reduce energy consumption
•   Improve yields
•   Reduce pollutants
•   Increase processing rates
•   Increase profitability



                                 12
          Some Observations
• Most plants do not monitor energy consumption
  on an individual unit operations basis, but only
  total plant usage for accounting purposes
• Processes may be designed for energy efficiency,
  but do not include degrees of freedom and
  manipulated variables to minimize energy
  utilization during operations
• Schemes control for desired throughput and
  product fitness-for-use attributes (composition,
  purity, color, etc.), but use utilities (energy) to
  achieve these goals and to reject disturbances
                                                        13
21st Century Business Drivers for
  Process Control (Edgar, 2004)
• Deliver a product that meets customer specifications
  consistently
• Maximize the cost benefits of implementing and
  supporting control and information systems
• Minimize product variability
• Meet safety and regulatory (environmental) requirements
• Maximize asset utilization and operate the plant flexibly
• Improve the operating range and reliability of control and
  information systems and increase the operator’s span of
  control

                                                               15
16
 Transformation of Variation from the
Temperature to Flow for a Reactor Feed
     Preheater (Downs et al., 1991)




                                         17
            More Observations
• Most multivariable algorithms (like MPC or LQG) do not
  assign an economic value to the manipulated variable
  moves, although some research efforts have been oriented
  towards “economic” MPC
• Energy reuse adding heat and power integration will
  create unit and control loop interactions and new
  disturbance patterns, making control strategies more
  complex. Integer (on-off) variables for equipment such as
  chillers will need to be optimized
• Swapping thermal and electrical forms of energy can have
  unexpected utilities systems impacts (dynamics and
  control)
• Attempting to control carbon emissions as well as energy
  usage will require new research investigations in PSE     18
 Addition of Sensors and Manipulated
Variables to Minimize Dynamic Energy
                 Use
• In a distillation column, maximize efficiency
  by operating near the flooding point
• Balance yield improvement vs. energy use
• Add MV’s with multiple feed points,
  bypasses
• Add hard and soft sensors for improved real
  -time modeling (e.g., Dzyacky flooding
  predictor based on pressures, temperatures,
  levels, flow rates)
Predictive Modeling Needed to Manage
Dynamic Energy Use – Refinery Example
• Increased throughput to a crude distillation unit
  must consider operating variables for crude
  tankage, pumps, preheat trains, and distribution of
  cuts from the tower
• Open up valves and let all equipment ramp up? Is
  there an optimum way that incorporates energy
  use? Perhaps a given ramp rate will result in more
  energy efficient performance of downstream units
• If an abundance of fuel gas will be available in one
  hour, will that facilitate a much more energy
  efficient ramp up, rather than sending the excess to
  flare?
        What is a Smart Grid?
• Delivery of electric power using two-way digital
  technology and automation with a goal to save
  energy, reduce cost, and increase reliability
• Power will be generated and distributed optimally
  for a wide range of conditions either centrally or
  at the customer site, with variable energy pricing
  based on time of day and power supply/demand
• Permits increased use of intermittent renewable
  power sources such as solar or wind energy and
  increases need for energy storage

                                                   21
              Electricity Demand Varies
                 throughout the Day




Source: ERCOT Reliability/Resource Update 2006   22
Today’s Grid
                Smart
               Grid 1.0




                      23
Tomorrow’s Grid
                   Smart
                  Grid 2.0




                             24
 Three Types of Utility Pricing
• Time-of-use (TOU) – fixed pricing for set periods
  of time, such as peak period, off peak, and
  shoulder
• Critical peak pricing (CPP) – TOU amended to
  include especially high rates during peak hours on
  a small number of critical days; alternatively, peak
  time rebates (PTR) give customers rebates for
  reducing peak usage on critical days
• Real time pricing (RTP) – retail energy price tied
  to the wholesale rate, varying throughout the day
                                                     25
26
Future Industrial Environment
• Stronger focus on energy use(corporate
  energy czars?)
• Increased energy efficiency and decreased
  carbon footprint
• Energy use measured and optimized for each
  unit operation
• Increased use of renewable energy(e.g., solar
  thermal and biomass) and energy storage
• Interface with smart grids
                                             27
28
       Thermal Energy Storage
• Thermal energy storage (TES) systems heat or cool a
  storage medium and then use that hot or cold medium for
  heat transfer at a later point in time
• Using thermal storage can reduce the size and initial cost
  of heating/cooling systems, lower energy costs, and reduce
  maintenance costs; if electricity costs more during the day
  than at night, thermal storage systems can reduce utility
  bills further
• Two forms of TES systems are currently used
   – A material that changes phase, most commonly steam, water or ice
     (latent heat)
   – A material that just changes the temperature, most commonly
     water (sensible heat)

                                                                    29
 TES Economics are Attractive
• High utility demand costs
• Utility time-of-use rates (some utilities
  charge more for energy use during peak
  periods of day and less during off-peak
  periods)
• High daily load variations
• Short duration loads
• Infrequent or cyclical loads
                                              30
Energy flows in a combined heat and power system with thermal storage
                          (Wang, et al. 2010)
    Thermal Energy Storage Operating
       Strategy with Four Chillers




      (a)                                              (b)
-Chillers 1& 4 are most efficient, 3 is least
       efficient
-Chiller 1 is variable frequency
(a) Experience-based (operator-initiated)
    -No load forecasting
    -Uses least efficient chiller (Chiller 3)
(b) Load forecasting + optimization
    -Uses most efficient chillers (avoids Chiller 3)
(c) Load forecasting + TES + optimization              (c)
    -Uses only two most efficient chillers                   32
                  Conclusions
• Many opportunities to improve energy efficiency in the
  process industries
• Energy efficiency ≡ sustainability (carbon footprint)
• Smart grids and energy storage will change the power
  environment for manufacturing
• Development of new real-time modeling, control, and
  optimization tools will be critical to deal with this
  dynamic environment
• A focus on energy comparable to the current emphasis
  on safety would yield significant improvements in energy
  efficiency

				
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posted:5/9/2014
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