PSerc - Power Systems Engineering Research Center by tyndale

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									  Day Ahead and Real Time
       Spot Markets



             Shmuel S. Oren
   University of California at Berkeley

Presented at the PUCT Public Workshop on
       Elements of Market Design
    Austin, Texas, November 1, 2002
The SMD NOPR Prescription

• Transmission Provider will operate the
  transmission system using spot markets
     • To manage congestion
     • To balance generation and load
• Spot Markets support bilateral and spot
  transactions


November 1, 2002    Shmuel Oren, UC Berkeley
                                      ...




                                                               Electric System and Market Time Line
                                                   PHYSICAL DELIVERY                                                                                                 REAL TIME
         Priority Service Contracts




                                                                                                                                                                                                                                                           Day Hour Minutes Seconds Cycles
                                                                                                                                                                                                                                                                                      100




                                                                                                                                              Voltage Control/Dynamics
                    Price Menus




                                                                                        Fixed Fee




                                                          Product line and
                                                                                                                    Automatic
                                                                                         Service




                                                          Price Menue Design,
                                                                                                                    Control




                                                                                                                                                                          Operation




                                                          Subscription Managmnt                                                                  Transient Standby
                                                          and Billing.
                                                                                                                                                                                                                                                                                <10
                                                                                                                                                 Frequency control
                                                                                                                                                                                                                  SYSTEM OPERATION
                                                                                       Settlement
       Insurance




                                                                                        Ex-post




                                                          Service Options Design                                                                  Load Balancing

                                                                                                                                                                                                                                              Shmuel Oren, UC Berkeley 15-5 5-1
                                                          Premium Calculation                                                                   (Spinning Reserves)
                                                          Service Reliabilty Forcst
                                                          Financial Settlmnt
                                                                                                                    Computation




                                                                                                                                            Economic Dispatch
                                                          Trading Rules,                                                                 (Congestion managment)
                                                                                                                                                                          Scheduling
                                                                                       Spot Market
       Bidding and




                                                          Bidding Protocols,
         Trading




                                                          Online Comm. Network,
                                                          Optimal Bidding Software,
                                                          Bid Selection Software,
                                                          Online Financial Settlmnt.                                                             Unit Commitment
                                                                                                                                              (scheduled congestion
                                                                                                                                                   managment)
                                                          Standardized Contracts,
Contracts Contracts
           Future




                                                          Clearing House Service,
            EFAs
   Calls and Puts




                                                          On Line Trading Tech.,
                                                          EDI Capability, Hedging




                                                                                                                                                                                                    Maintenance
                                                                                                                   Standards and

                                                          and Valuation Software.
                                                                                                                     Protocols
Forward




                                                                                                                                                                                                                                     Years/Months
                                                                                                                                                Contingency Analysis
 CFDs




                                                          Hedging Instruments
                                                          Valuation Software
                                                                                                                                                Fuel Inventory Mang.




                                                                                                                                                                                       Fuel Procurement
                                                                                                                                                                                                                  ASSET PROVISION
                                                          Trading Rooms,
                                                                                       Negotiation, OTC Trading,

                                                          Electronic Buletin
                                                          Boards                          Contract Bidding
           Long Term Contracts




                                                                                                                                                 Design Principles
                                                                                                                                                    and Limits




                                                                                                                                                                          Planning / Building
                                                                                                                   Load Forecasting
               Investment




                                                                                                                     and Analysis
                                                          Portfolio Analysis,




                                                                                                                                                                                                                                        Decades/Years
                                                          CAPM, Brokerage                                                               Risk and Decision Analysis




                                                                                                                                                                                                                                     November 1, 2002
                                                          and Financing
                                                          Institutions
                                                                                                                                              Capacity planning Tools
                                                                                                                                               (Over/Under, Uplan)




                                                                                                                                                     Technology
                                            Instruments




                                                                                                                                                     Supporting
                                                                Technology
                                                                Supporting




                                                                                                                                                     Tools and




                                                                                                                                                                      Physical
                                                                Tools and




                                                                                                                                                                      System
                                                                                  Market




                                                                                                                                      Means
                                                                                  Form




                                                                                                                                                                      The
SMD Spot Market
Characteristics

• Operated in two time frames
     • Day-ahead
     • Real-time
• Prices and schedules are based on
  participants’ bids
     • Bidding is voluntary, except when required
       for market power mitigation
     • Prices are market clearing

November 1, 2002    Shmuel Oren, UC Berkeley
Specific Characteristics of
Proposed Day-Ahead Market
 • Physically feasible security constrained bid based
   dispatch of energy and reserves
 • Voluntary central unit commitment based on multi-
   dimensional offers specifying costs and constraints of
   each resource
 • Self-commitment allowed
 • Virtual bidding (identified as such) allowed
 • Bilateral transactions allowed (do not have to submit
   bids) but are subject to congestion charges based on
   day ahead LMP
 • CRRs in the form of PTP contracts, PTP options or
   flowgate rights settled based on day ahead LMP.
 • Two settlements: DA transactions settled at DA LMP
   whereas RT deviations from DA schedules settled at RT
   LMP.
November 1, 2002     Shmuel Oren, UC Berkeley
Important Observations

• Congestion management and transmission
  pricing are independent from the organization of
  spot markets
• It is possible to have LMP-based congestion
  management and transmission pricing with only
  a single settlement RT spot market (Victoria
  Pool)
• It is possible to have a mandatory day ahead
  market with central unit commitment and no
  locational pricing (original UK system)

November 1, 2002   Shmuel Oren, UC Berkeley
Where is ERCOT?

• The balancing market (especially after relaxing
  the balanced schedule requirement) qualifies as
  a RT single settlement spot market but it is not
  fully efficient because of limited information
  exchange (portfolio bidding, no binding resource
  plan)
• Ancillary service market is a limited DA market
  with the RPRS procurement representing a
  simplified unit commitment for covering
  expected imbalances.

November 1, 2002   Shmuel Oren, UC Berkeley
Arguments for a Day Ahead Market

• Operator needs to know in advance what are the balancing needs
• With relaxed balanced schedules early knowledge of balancing
  needs will enable more efficient deployment of resources (efficient
  procurement of RPRS)
• DA market enables differential pricing of planned and unplanned
  imbalances so as to reflect the higher cost of responding to
  unplanned imbalances
• Provides an additional trading forum for market participants who
  have predictable imbalances to cover their positions.
• Mitigates market power in RT
• Facilitates demand side response from load that cannot respond in
  real time
• Enhances price discovery and provide a better (less volatile) bench
  mark for contract settlements than RT prices.



November 1, 2002          Shmuel Oren, UC Berkeley
Scope of the DA market

• All DA transactions are bilateral, with
  possible private exchanges (ERCOT, NETA)
• Voluntary RTO operated DA market.
• Mandatory RTO operated DA market. All
  transactions must submit bids. No
  guaranteed dispatch. Bilateral contracts are
  financial hedges (CFD)


November 1, 2002   Shmuel Oren, UC Berkeley
Physical feasibility

• DA transactions can violate known
  constraints (California PX, ERCOT step 1).
  Constraints satisfied through RT balancing
  market.
• DA transactions must satisfy security
  constrained dispatch (PJM, NY)



November 1, 2002   Shmuel Oren, UC Berkeley
Settlements

• Single settlement: DA settled at RT prices
  (Victoria pool)
• Two settlement: DA clearing prices
  financially binding. Deviations from DA
  schedules settled at RT prices




November 1, 2002   Shmuel Oren, UC Berkeley
Virtual Bidding

• Virtual DA bids are used to arbitrage DA
  prices against RT prices
• Virtual bids must be declared
     • Virtual bids participate in setting DA LMP
       (PJM). Enables gaming of FTR values (virtual
       bids can be used to congest or decongest
       PTP)
     • Virtual bids excluded from setting DA LMP

November 1, 2002    Shmuel Oren, UC Berkeley
Unit Commitment Considerations

• Central optimization can improve economic
  efficiency
• Cost not one dimensional. Marginal cost affected
  by schedule (e.g. startup)
• Without constraint information dispatch may be
  infeasible resulting in deviations
• Constraints information can be gamed
• Optimal solution is not perfect and may not be
  unique. May result in inequity


November 1, 2002   Shmuel Oren, UC Berkeley
Unit Commitment Alternatives

• Self commitment. Energy only bids in DA market
  (CalPX)
• Self-commitment with energy only bids. Strips
  and minimum daily revenue offers allowed.
  (Spanish market)
• Central unit commitment of all resources
  (including bilateral transactions) all bilateral day
  ahead trading is financial (NY, old UK system)
• Voluntary unit commitment. Bilateral
  transactions do not have to bid and self
  committed energy bids accepted
November 1, 2002   Shmuel Oren, UC Berkeley
Unit Commitment Alternatives

• Unit commitment applied only to “net short”
  (CAISO MD02)
• Technical parameters fixed for long time periods
• Treatment of ancillary services
     • Joint optimization of energy and reserves (NY)
     • Separate AS market (PJM - regulation)
• Treatment of transmission constraints
     • Transmission constraints included in UC (NY)
     • Loacational vs. systemwide reserves
     • UC ignores transmission constraints


November 1, 2002       Shmuel Oren, UC Berkeley
     Unit Commitment Problem




Minimize                         [ St at e T ransit io n Cost + Energ y co st ]
{ St at e, Out put }   Time Resource


subject to:                        Dem and con st raint
                                  Spinning reserve require ment
                                  Int e rt emp o ral con st raint s ( e. g . Ramp in g )
                                  Co mm it ment / availab ilit y con st raint s
                                   (Transmission constraints)
    November 1, 2002                     Shmuel Oren, UC Berkeley
UNIT COMMITMENT PROBLEM


               Transition Cost            Commitmen t state {0,1}               Ge neratio n cost
                       T         I
     Minimize  [Sit (x (i,t 1) ,x it )  Cit (pit )]
                                                                                         Resource i
                                                                                         Ti me    t
       {xit ,p it }
                      t 1 i 1
                                                                                Ge neratio n l evel
                             I
    subject to              p       it    Dt , t  1,...,T                 Demand constra int

                            i 1
              I

             pi
             i 1
                      max
                           ui (x it )  Rt , t  1,...,T                     Spinning reserv e requirement



                                           Resource fra cti on avai la ble given state



            min                                  max
         pit ui (xit )  pit  pit ui (x it ),i  1,...,I,t  1,...,T
                                                                                                          Intertemporal
                                                                                                          constraints



        xi  Xi , i  1,..., I                     Where      xi  (xi1 , xi 2 ,..., xiT )            Commitment
                                                                                                      constraints

November 1, 2002                               Shmuel Oren, UC Berkeley
DAY AHEAD BIDDING IN THE
UK SYSTEM
OFFER DATA PROVIDED TO GRID OPERATOR BY EACH GENERATOR, BY
   10:00 AM ON EACH DAY:
• OFFERED AVAILABILITY (MAX MW FOR EVERY MINUTE)
• PRICES (SUPPLY CURVE)
• OPERATING CHARACTERISTICS:
    • Run-up rates
    • Run-down rates
    • Synchronizing generation
    • Minimum output
    • Other
• DECLARED INFLEXIBILITY:
    • Max On/Off between daily peaks
    • Fixed output level at specified time intervals
     • Minimum output level at specified time interval

November 1, 2002            Shmuel Oren, UC Berkeley
Description of the CALECO
System Used in Pool Simulations


       U nit N ame      M a x L o ad   Mi n Lo a d     S tartu p $           Min Up        Min Down      Fuel

      Col-S tm             1000            25 0         100000                 12 0             48    Coal
      Stm1                   750             50           15000                  24             48    Gas
      Stm5                   330             50           15000                   6              3    Gas
      Stm6                   3 30            50           15000                    6             3    G as
      Stm7                   3 40            85           15000                    6             3    G as
      QF                   1000          1000                 N/A               N/A            N/A    QF
      P o n d Hy d ro      1 5 00             1                   0                1             1    P o n d Hy d ro ( L im i te d )
      ROR Hydro             9 00              0                   0                1             1    ROR Hydro
      Nuke                 2000               0         200000                     1             1    Nuke
      CT s                 1 0 00             0                   0                1             1    D istil la te
      Econ01                 500              0                   0                1             1    Transaction at $17.5/MWH
      Econ02                 5 00             0                   0                1             1    Transaction at $30/MWH

      L oad assum ption s:                        M a xi m u m lo a d = 9 7 4 9 M W
                                                  Minim um load = 4990 MW
                                                  T o ta l l o a d = 1 1 7 8 8 6 1 M W H
                                                  Load factor = 74%
                                                  168 hours




November 1, 2002                             Shmuel Oren, UC Berkeley
LOAD NET OF BASE LOADED
RESOURCES AND HYDRO

           100 00

                                                                                                             hav y
                                                                                                      Peak -S e H dro
            900 0

                                                                                                                     R       v     y
                                                                                                                      un-of-Ri er H dro
            800 0



            700 0




            600 0
                    LOA D /GEN ER A TION ( MW)




            500 0



            400 0

                                                                                        COAL-STEAM
            300 0

                                                                                           QF
            200 0



            100 0                                                                          U
                                                                                          N KE

                    0
                                                 0   10   20   30   40   50   60   70     80     90     100   110   120   130   140   150   160
                                                                                           H O URS




November 1, 2002                                                         Shmuel Oren, UC Berkeley
November 1, 2002   Shmuel Oren, UC Berkeley
Profit Volatility in Power Pools
with Central Unit Commitment
                                          DEVIATION FROM AVERAGE PROFIT ON DIFFERENT RUNS OF UNIT COMMITMENT
                                   100

                                                                                                                   5
                                                                                                                   6
                                   80                                                                              7
                                                                                                                   8
                                                                                                                   9
     Deviation From Average (K$)




                                   60                                                                              11

                                                                     Average Profit/Cost (K$)
                                   40
                                          708      739        31       177       177       332   116    2,638   20,317

                                   20




                                    0




                                   -20




                                   -40
                                         Econ01   Col-Stm   Econ02    Stm6     Stm5     Stm1     Stm7    QF     TOT Cost
                                                                     Dispatchable Resources



November 1, 2002                                                   Shmuel Oren, UC Berkeley
Incentive compatibility problems

• Optimum flat and dispatch decisions sensitive to small
  changes in parameters
• Incentives for bidders to try manipulating the dispatch
  and prices through declaration of constraints (such
  manipulation was prevalent in the UK before NETA)
• Optimizing unit commitment with misrepresented
  generator characteristics undermines efficiency objective
• Unit commitment does not account for all the variables
  that affect a generator’s decision to run (e.g. long term
  fuel supply contracts)
• Day ahead unit commitment does not capture
  optimization over longer planning horizons (e.g. hydro
  scheduling)

November 1, 2002     Shmuel Oren, UC Berkeley
 Gaming Ramp Constraints
                                          OffPeak                  Peak
                  Demand                  1000MW                   3000MW
                  Generator A Bids        1000MW at $10/MWh        1000 MW at $10/MWh
                  Generator B Bids        2000 MW at $15/MWh       2000 MW at $15/MWh
                  Generator C Bids        2000 MW at $25/MWh       2000 MW at $25/MWh

          Least cost dispatch with no intertemporal constraints
                           Clearing Price      Generator A      Generator B      Generator C
          OffPeak          $10/MWh             1000MW           0                0
          Peak             $15/MWh             1000MW           2000MW           0
          Financials       Soc. Cst=$600,000   Prft.=$60,000    Prft.=0          Prft.=0

          Least cost dispatch with zero ramp rate constraint by Generator B
                           Clearing Price      Generator A      Generator B      Generator C
          OffPeak          $15/MWh             0                1000MW           0
          Peak             $25/MWh             1000MW           1000MW           1000MW
          Financials       Soc. Cst=$780,000   Prft.=$180,000   Prft.=$120,000   Prft.=0


•Clearing prices in each time period are not the correct marginal costs
•Uniform price settlements based on the clearing price in each period
create perverse incentive to impose ramp constraints
 November 1, 2002                        Shmuel Oren, UC Berkeley
Conclusions

• Day ahead markets could be beneficial
• The devil is in the details
• Central unit commitment creates gaming
  opportunities
• Voluntary DA market with self-
  commitment is a good compromise
• Virtual bidding is a good idea but should
  not be allowed to set DA LMP.

November 1, 2002   Shmuel Oren, UC Berkeley
November 1, 2002   Shmuel Oren, UC Berkeley

								
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