How Retail Markets Can Optimize Electricity Distribution

1. How Retail Markets Can Optimize Electricity Distribution D. P. Chassin Pacific Northwest National Laboratory

2. Overview Introduction to real-time capacity markets Purpose, theory, basic examples, issues Examine Olypen market design/results Objectives, implementation, results, insights Preview AEP NE Columbus RTP-DA rate Rate design and valuation process

3. Purpose of Retail Real-Time Pricing • Discover retail price of energy • Time-varying value of (constrained) supply • Incorporates time-varying value of demand response • Addresses 3 major distribution issues: Load growth, distributed resource control, demand response

4. Markets as optimizers Auctions solve allocation problem Computationally efficient (parallelizable) Equilibrium assignment of buyers and sellers Interative (either explicit or implicit) Linear program discovers price Maximizes total benefit (primal) Minimize local costs (dual) Price solution is Pareto optimal See DP Bertsekas , Linear Network Optimization: Algorithms and Codes, MIT Press, 1991

5. Retail Capacity Market Buyer surplus Energy price [$/MWh] Cleared price Seller surplus Power [MW] Cleared load

6. Incorporate Day-Ahead Schedule RTP customers’ actual response Price ($/MWh) Retail price between DA and RT Real-time price is high Cleared price Day-ahead Price is low Load (MW) Unresponsive Load Maximum Load Scheduled Load

7. Some potential issues/FAQs Should utility be allowed to own/coordinate distributed resources (analog to generation/transmission conflict)? How to ensure costs are not double-embedded? How is seller surplus from feeder congestion used? How does utility fairly compensate consumers? Are there any subsidies built into the rate scheme? How is misbid/misresponse handled? What kind of security is really needed? How is rebound managed?

8. Rebound peaks occur with load control Fixed price Time-of-use price

9. Complex pricing strategies mitigate rebound Time-of-use group 1 Time-of-use group 3 Time-of-use group 2 Time-of-use group 4 Time-of-use group 6 Time-of-use group 5

10. At some point a capacity market is easier Fixed price Real-time price

11. Pacific NW GridWise™ Testbed Projects GridWise Testbed Participants Bonneville Power Administration IBM Pacificorp Whirlpool/Sears Kenmore Portland General Electric Clallum County Public Utility District City of Port Angeles Municipal Utility 11

12. Virtual Distribution Utility Operation IBM Invensys Johnson Controls Internet broadband communications Market $ MW 12

13. Olympic Peninsula RTP Market

14. Customer participation $35 Economy Comfort

15. Economic Cooling Response k k Tmin Tmax User sets: Tdesired, comfort (based on occupancy calendar) These imply: Tmax, Tmin, k (price response parameters) Price is expressed as std. deviation from mean (over a short period, e.g., 24 hrs) Pbid Pavg Price Pclear Tset Tdesired Tcurrent Temperature 15

16. Managing Constraints DG required above feeder limit Load (kW) Market failed to cap demand for one 5-min. interval in 12 months of operation Price ($/MWh) Hour 16

17. Load Shifting RTP Customers • Winter peak load shifted by pre-heating • Resulting new peak load at 3 AM is non-coincident with system peak at 7 AM • Illustrates key finding that a portfolio of contract typesmay be preferred – i.e., we don’t want to just create a new peak 17

18. Mixing rates also manages uncertainty It is impossible to choose a portfolio in this white region because no combination of contracts can yield such risk/return 18

19. Peak energy uncertainty 19

20. Gross margin volatility 20

21. Response Manages New Resources Regulation: one or more fast-responding power plants continually throttle to match normal fluctuations in load Highest cost generation in markets (zero net energy sales, wear & tear, fuel consumption) Intermittency of wind output can exceed regulation capability and reduces cost effectiveness of wind Demand management to a capacity cap with real-time prices eliminated load fluctuations for 12 hours! normal fluctuations in load Load (kW) Hour 21

22. AEP NE Columbus Project • Many tariffs are planned • Fixed Rate (standard) • Interruptible Tariff (direct load control) • 2-Tier Time of Use (2-TOU) • 3-Tier Time of Use (3-TOU) • Real Time Price Double Auction (RTPDA) • Each tariff enable a difference kind of response

23. RTP Rate Design Determine RTP-DA pricing method PJM DA Hourly LMP 5-minute RTP LMP Customer bids (Heating, AC, hotwater) Feeder constraints (physical limits) System limits not expressed in LMP Residential (exc. RR1), small commercial May include special terms (e.g., 1 yr harmless) May also include other resources TBD PUCO approval required

24. System requirements Advanced Metering Infrastructure (AMI) Home Energy Manager (HEM) Advanced equipment controls Heating systems (electric only) Air-conditioning system Hotwater heaters (electric only) Resource control (e.g., CES strategies) Smart Grid Dispatch engine

25. RTP-DA Valuation Values included Wholesale energy production Generation capacity Ancillary services (regulation and reserves) Transmission congestion Distribution congestion Values excluded Scarcity pricing Subtrans. constraints Environment constraints Wind/bundling/firming Reactive power Emergency/reliability Financial transmission rights Determine costs/benefits of RTP-DA

26. How Does RTPDA work?

27. Conclusions Retail capacity markets Energy price of Pareto-optimal allocation Olypen project a simple/full example Demonstrated basic concept Showed important of enabling technology AEP NE Columbus project Significant scaling up of implementation Stronger integration into wholesale operations

28. Questions/Comments Contact: David P. Chassin Pacific Northwest National Laboratory david.chassin@pnl.gov