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Optimized Utilization of Demand Response Resources and Utility-Scale Energy Storage in Day-Ahead Energy Markets

Optimized Utilization of Demand Response Resources and Utility-Scale Energy Storage in Day-Ahead Energy Markets. May 4, 2012 Kai Van Horn with adviser Prof. George Gross. OUTLINE. Motivation Background Longer-term simulation Market simulation and storage scheduling

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Optimized Utilization of Demand Response Resources and Utility-Scale Energy Storage in Day-Ahead Energy Markets

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  1. Optimized Utilization of Demand Response Resources and Utility-Scale Energy Storage in Day-Ahead Energy Markets May 4, 2012 Kai Van Horn with adviser Prof. George Gross

  2. OUTLINE Motivation Background Longer-term simulation Market simulation and storage scheduling Key policy developments Future work Concluding remarks

  3. PJM LOAD AND PRICES FOR WEEK OF APRIL 4, 2010 MW $/MWh peak load base load 0 24 48 72 96 120 144 168 h

  4. GOALS quantify reliability and economic impacts of coordinated demand response resource (DRR) and energy storage (ES) utilization over longer-term periods develop effective methods to schedule storage develop effective methods to determine coordinated ES/DRR DAM schedule simulate over longer-term periods include the network

  5. ELECTRICITY MARKET CLEARING / / total buyer benefits total seller “costs”

  6. ELECTRICITY MARKET CLEARING /

  7. LOAD SHAPING MW 0 24 48 72 96 120 144 168 h

  8. ENERGY STORAGE SYSTEM RATINGS Source: http://www.electricitystorage.org

  9. LONGER-TERM SIMULATION storage schedule for days up to market simulation for day sample load and generator availability distributions for each of the 24 hours of day day outcomes

  10. MARKET SIMULATION ES scheduling problem (ESSP) transmission-constrained market clearing problem (TCMCP) ESSP constraints extended TCMCP

  11. MARKET SIMULATION ES scheduling problem (ESSP) extended TCMCP with ESSP constraints Optimized ES/DRR schedule ESSP constraints

  12. TRANSMISSION-CONSTRAINTED MARKET CLEARING PROBLEM (TCMCP)

  13. ES IMPACTS IN THE DAMs / / impact of ES discharge 𝒹

  14. ES IMPACTS IN THE DAMs / / impact of ES charge

  15. ES REPRESENTATION bus discharge power charge power energy in energy out ES unit

  16. DRR REPRESENTATION bus recovery curtailment cumulative net curtailed energy DRR

  17. ES SCHEDULING PERIOD LENGTH MW h 0 24 48 72 96 120 144 168

  18. ES SCHEDULING PROBLEM (ESSP)

  19. EXTENDED TCMCP WITH ESSP CONSTRAINTS

  20. KEY DRR POLICY DEVELOPMENTS • Requires DRRs be paid the post-curtailment LMP for curtailments • Requires calculation of threshold price by the Net Benefits Test Permits CSPs to bid DRRs on behalf of buyers 745 FERCOrder No. 719 2011 2008

  21. DRR THRESHOLD PRICE /

  22. TWO-ROUND MARKET CLEARING extended TCMCP w/ ESSP const. + cleared DRRs extended TCMCP w/ ESSP const. w/o DRR N Y

  23. ILLUSTRATIVE RESULTS IEEE 30-bus system week peak load 420 MW 12 generators, 435 MW total capacity 1 storage device, 30 MW/240 MWh 1 DRR at bus 5, 10 MW Deterministic schedules

  24. LOAD SHAPING

  25. NODE 2 PRICES 633

  26. FUTURE WORK Integrate into longer-term simulation framework Lots of studies Impacts of monthly threshold Represent renewables Non-deterministic storage schedule

  27. CONCLUDING REMARKS Energy storage and demand response play an increasingly prominent role in meeting the supply-demand balance There is a need to understand the longer-term economic and reliability impacts of DRRs and ES Consideration of the network effects in longer-term simulation is also important

  28. Thank You.

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