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					   Climate Forecasts for Improving
Management of Energy and Hydropower
    Resources in the Western U.S.
NOAA CDEP & California Energy Commission

      Scripps Institution of Oceanography
                 T. Barnett, D. Pierce
        University of California, Merced
                    A. Westerling
           University of Washington
       D. Lettenmaier, A. Hamlet, A. Steinemann
                       PNNL
              Ross Gutromson, Ning Lu
      Conjunctive Hydropower
           Management
• streamflow available for western hydropower
  production is dominated by cool season
  precipitation
• the coefficient of variation, autocorrelation, and
  regional synchronicity have all increased
  markedly since about 1975
• these results suggest reduced opportunity for
  conjunctive management of the West’s
  hydropower resources in recent decades
                 Std Anomalies Relative to 1961-1990




       -3
            -2
                      -1
                              0
                                      1
                                              2
                                                         3
1916                                                                    4
1920
1924

                                                  GB
                                                             CA
                                                       CRB
                                                                  PNW



1928
1932
1936
1940
1944
1948
1952
                                                       PRECIP



1956
1960
1964
1968
1972
1976
1980
1984
1988
1992
1996
2000
                                                                            Regionally Averaged Cool Season Precipitation Anomalies
                     Annual hydropower production in the West has become
                     more variable and more regionally synchronous in the
                     period 1976-2002 in comparison with the rest of the 20th
                     century.

                                  Correlation:     Correlation:      Correlation:
                             3    CRB-SSJ = 0.07   CRB-SSJ = 0.14    CRB-SSJ = 0.73
Production (Std Anomalies)
 System Wide Hydropower




                                  CRB-PNW = 0.08   CRB-PNW = -0.14   CRB-PNW = 0.51
                                  SSJ-PNW = 0.36   SSJ-PNW = 0.06    SSJ-PNW = 0.65
                             2


                                                                                      CRB
                             1
                                                                                      SSJ
                                                                                      PNW
                             0



                             -1



                             -2
                                  1917
                                  1919
                                  1921
                                  1923
                                  1925
                                  1927
                                  1929
                                  1931
                                  1933
                                  1935
                                  1937
                                  1939
                                  1941
                                  1943
                                  1945
                                  1947
                                  1949
                                  1951
                                  1953
                                  1955
                                  1957
                                  1959
                                  1961
                                  1963
                                  1965
                                  1967
                                  1969
                                  1971
                                  1973
                                  1975
                                  1977
                                  1979
                                  1981
                                  1983
                                  1985
                                  1987
                                  1989
                                  1991
                                  1993
                                  1995
                                  1997
                                  1999
                                  2001
Modeling Climatic Influences on
 the Western Electricity Grid
   Modeling effects of reduced
streamflow on power generation
• reduce hydropower production on the Grand
  Coulee dam 10% - 30%
• replace lost production via nearby thermal
  generation
Dams along the Columbia River
   An Example of Weather Impacts
• If the hydro generation is
  reduced                             A Summer Case
   – Economically: what is the cost
     of the replacement generation?
   – Technically: will we get more
     power from Canada? Can we
     transport the power into the
     states?
• If the hydro generation is
  increased
   – Economically: who is going to
     reduce generation?
   – Technically: can we transport
     these hydro generation out to
     other states?
                  An Example Case
• Reduce the power output of a
  hydro plant.
• Let Puget Sound Energy (a
  generator company in Seattle)
  pick up the power.
   – Adjust the power outputs of the
     thermal generators
   – Satisfy the transmission
     constraints (no congestion)
   – Power flow converge
• Based on the cost curves,
  calculate the cost of the
  replacement energy.
Simulation in WECC systems
                      Cost Curves
• The cost curve of Hydro
  electric plants vary with
  respect to the hydraulic
  heads.
• Thermal power plants usually
  have startup costs. When
  capacity limits are reached,
  the cost goes up significantly.
Replacing Reduced Hydro with Thermal Generation
(Peak Summer Day - WECC Planning Scenario)



                     Hydro   Thermal      Net
      Scenario     (Coulee)* (PGE)*    Gain/Loss*
      Base        1800 MW 1443 MW          na

      - 10%       1620 MW    1614 MW     -$5,198

      - 20%       1440 MW    1794 MW   -$13,670

      - 30%       1260 MW    1974 MW   -$32,316

                 *per hour
    Modeling Peak Electricity
  Demand as a Function of max
  Temperature and Day of Week
• hourly electric loads by service areas for western
  utilities as reported annually to FERC
• We use the daily peak for a representative sample
  of utilities with “clean” data
• daily TMAX on 1/8 degree grid averaged for four
  regions: NW, NoCA, SoCA, SW
• peak daily load is fit to TMAX and
  weekday/weekend
• Result is scaled to loads reported in WECC
  planning cases
Northwest Peak Hourly Electricity Demand as a function of TMAX
Northern CA Peak Hourly Electricity Demand as a function of TMAX
Southern CA Peak Hourly Electricity Demand as a function of TMAX
Southwest Peak Hourly Electricity Demand as a function of TMAX
  Coupling Energy Demand and
      Generation Models
• Electricity Generation from WECC model
  given Demands as a function of TMAX
  – optimization given generic thermal, hydro cost
    curves
  – constrained by existing transmission capacity
• WECC model is modified
  – from peak hour planning case to 24 hours
  – from non-coincident to coincident peak demand
             WECC Peak Generation - Peak Load

   TMAX at 90th %tile                  TMAX at 100th %tile




Additional demand in California is met by increased production
          in the Northwest and Southwest (cheaper)
              WECC Peak Generation - Peak Load
 TMAX at 95th %tile in CA,           TMAX at 95th %tile in CA,
 50th %tile in NW & SW               95th %tile in NW & SW




   Additional demand in Northwest & Southwest reduces exports
to California, more power produced in California (more expensive)
    Forecasting Summer Tmax
• Summer Tmax influenced by Pacific
  climate
• Modest skill
• CCA methodology
• Trend
• Parametric approach: PDF conditional on
  climate indices
Use Patterns in March Sea Surface Temperature and PDSI




                                         to forecast patterns in
                                         spring and summer
                                         temperatures




after Alfaro, Gershunov and Cayan 2005
      Probability Density for Southern California
Detrended Summer TMAX Conditional on ENSO & PDO
Example: probability of western TMAX in top 95 percentile




                       Out of 92 day season
  Management Strategies
 conditional on a T forecast
Demand:
    curtailment
    variable pricing

Supply:
     forward contracts
      Forecasting Streamflow,
           Hydropower
• Climate forecasts dominate planning in fall
  and early winter
• by late winter, spring, observed snowpack
  dominates planning
• ENSO/PDO basis of long lead forecasts for
  both hydropower (supply) and temperature
  (demand)
                                   April 1 SWE (mm)




         Winter Climate          Hydrologic State
       Forecasts Dominate       Variables Dominate

June                 December                   March
                      ColSim
Climate              Reservoir
Forecast              Model




        VIC
   Hydrology Model
             Linkage to Reservoir Models


Streamflow
 Forecast     Bias Correction




                                Reservoir Model     Storage
                                                   Ensemble




    Observed Reservoir
                                Demand Scenarios
         Contents
    Bias Corrected Long Range Streamflow Forecast for the Columbia River at The Dalles
    Nino3.4 index between 0.2 and 1.2 and warm PDO (interannual)
Natural Streamflow (cfs)




                                                          Red = Unconditional mean
                                                          Blue = Ensemble mean
                                                          Black = 2005 Observed
Management Strategies conditional
 on a Streamflow/ Hydropower
            forecast
  Demand:
      curtailment (advance warning)
      variable pricing

  Supply:
       forward contracts
       conserve cheaper hydro supply
       export hydro

				
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posted:1/12/2011
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