Smart Capacity Markets: Can they be Smart Enough?

1. Smart Capacity Markets Washington DC, November 9-10, 2009 Smart Capacity Markets:Can they be Smart Enough? Tim Mount Department of Applied Economics and Management Cornell University *TDM2@cornell.edu

2. Page 2 Acknowledgements The research used in this presentation was supported by the US Department of Energy through the Consortium for Electric Reliability Technology Solutions (CERTS) and by the Power Systems Engineering Research Center (PSERC). Researchers at Cornell Engineers Economists Lindsay Anderson Alberto Lamadrid Hsiao-Dong Chiang Surin Maneevitjit Andrew Hunter Tim Mount Bob Thomas Dick Schuler Lang Tong Bill Schulze Max Zhang Ray Zimmerman

3. Page 3 New Goals for Energy Policy • OBJECTIVE • Mitigate the effects of climate change • President Obama’s proposed goal is to reduce national emissions of greenhouse gases by 80% by 2050. • NECESSARY STEPS • Generate electricity from renewable sources of energy and replace fossil fuels like coal • Use electricity for transportation and replace petroleum fuels ( Energy Independence) • Make buildings energy efficient and use ground-source heat pumps for space conditioning with thermal storage • Decentralize energy sources and controls

4. Page 4 OUTLINE • INVESTIGATE THE EFFECTS OF RENEWABLES • Add wind generating capacity to replace coal capacity • Determine the effects on: • Annual earnings of conventional units in the wholesale market • Missing money needed to maintain their Financial Adequacy • CASE STUDY • Use a 30-bus test AC network in a deregulated market • Determine the generating capacity needed to maintain System Adequacy endogenously • Determine the Total Annual System Cost • IDEAL COMMUNITY NETWORK

5. Page 5 30-BUS TEST NETWORK Wind Farm + 3xWind MW - Coal MW • Area 1 • Urban • High Load • High Cost • VOLL = • $10,000/MWh • Area 2 • Rural • Low Load • Low Cost • VOLL = • $5,000/MWh • Area 3 • Rural • Low Load • Low Cost • VOLL = • $5,000/MWh

6. Page 6 Scenarios Considered • Case 1: NO Wind, Initial System Capacity • Case 2: NORMAL Wind • 105MW of variable wind replaces 35MW of coal in Area 2 in four increments • Case 3: NICE Wind • Variability of wind smoothed by storage in Area 2 • Case 4: NASTY Wind • Variable wind with a “must-take” contract in Area 2

7. Page 7 Annual Payments in the Wholesale Market • NORMAL and NICE Wind • Slightly Lower Fuel Costs • Much Lower Net Earnings • Low Earnings for Wind • NASTY Wind • Higher Fuel Costs • Higher Net Earnings • Higher Earnings for Wind NORMAL NICE NASTY Case 2: NORMAL Wind .0: 0MW of Wind Case 3: NICE Wind .1: 26MW of Wind Case 4: NASTY Wind .2: 52MW of Wind .3: 78MW of Wind .4: 105MW of Wind

8. PAYMENTS BY CUSTOMERS IN THE WHOLESALE MARKET • Congestion Rents = Total Annual Payments by Customers – Total Annual Payments to Generators • Total Annual Earnings for Generators = Total Annual Payments – Total Annual Operating Costs (Zero Operating Costs for Wind Generation) • GENERAL CONCLUSIONS • 1) Conventional Generators are the big losers and Customers are the big winners with NORMAL and NICE Wind • 2) Congestion Rents are relatively small and maybe negative • 3) Revenues for Wind Generators are relatively small • 4) Customers may pay more with NASTY Wind • WHAT ARE THE IMPLICATIONS FOR FINANCIAL ADEQUACY?

9. Page 9 Missing Money for Generating Units  Total Annual System Cost • Minimum Earnings = Annualized Capital Cost x MW Committed to meet the Peak System Load (i.e. to maintain System Adequacy) • By type of generating unit (e.g. $88,000/MW/year for G1 and G2) • Missing Money = Max[(Minimum Earnings – Actual Net Revenue), 0] • Capacity Price = Missing Money/ MW Committed for System Adequacy • Capacity Markets use the maximum Capacity Price by Region to pay all MW Committed in a Region • Area 1 for Gen 1 and Gen 2 • Areas 2 and 3 for Gen 3 - 6 • Total Annual System Cost = Total Annual Wholesale Payments + Total Annual Capacity Payments to Generators and to Transmission Owners

10. Page 10 Total Annual System Costs Additional Missing Money for the Conventional Generators offsets most of the savings in the Wholesale Market for NORMAL and NICE Wind Total Annual System Costs increase with NASTY Wind NORMAL NICE NASTY Case 2: NORMAL Wind .0: 0MW of Wind Case 3: NICE Wind .1: 26MW of Wind Case 4: NASTY Wind .2: 52MW of Wind .3: 78MW of Wind .4: 105MW of Wind

11. Page 11 Need a New Dynamic Rate Structure Adding wind generation will result in: Wholesale Energy Prices going DOWN Capacity Prices going UP All customers should pay for both Energy and Capacity Real-time nodal prices for the ENERGY used Correct price for the CAPACITY demanded at the system peak The financial viability of storage technologies and controllable load depends on getting the Capacity Price and Capacity Demanded measured correctly

12. Page 12 IDEAL Distribution Networks I THE PROBLEM Impractical for many Residential and Commercial customers to pay for both Energy used and Capacity demanded: Difficult to measure Capacity correctly for individual customers Responses to Real-Time Prices for Energy are relatively slow Information overload for many customers  inefficient response A SOLUTION Aggregate the loads of “small” customers and manage them as a single Wholesale customer: Better management of the aggregate load and peak capacity demanded Rapid response using wireless signals/automatic controls Simplifies the operations for Transmission System Operators

13. Page 13 IDEAL Distribution Networks II Need a new generation of engineer/managers to operate and manage community distribution systems: Manage new Distributed Energy Resources effectively Reduce costs for customers by managing the aggregate peak load Provide new capabilities to support the bulk-power grid Cornell has proposed an Intelligent Dependable Energy with Active Load (IDEAL) campus network: Diverse types of Distributed Energy Resources already exist New facilities for training students will be developed An IDEAL campus network will lead to IDEAL community networks

14. Page 14 Capacity Markets I Objectives: 1) Ensure Generation Adequacy in the FUTURE 2) Provide the “missing money” for generators 3) Reduce the financial risk for new entrants 4) Prorate costs to Load Serving Entities using actual peak loads Implications: 1) Determines an annual price for capacity 2) Does not determine the correct incentives for loads - seasonal prices for capacity  REDUCE SYSTEM PEAK - hourly prices for capacity  SMOOTH DAILY LOAD PATTERN

15. Page 15 Capacity Markets II Future Objectives with IDEAL Community Networks: 1) Ensure Generation Adequacy of the BULK POWER GRID 2) Forecast the peak system load for the BULK POWER GRID 3) Reduce the financial risk for new entrants 4) Prorate costs using actual peak loads at the SUBSTATION level 5) DON’T TREAT LOAD RESPONSE AS NEGATIVE CAPACITY Implications: 1) All “customers” on the the Bulk Power Grid will be Wholesale 2) IDEAL Operator/Managers will allocate costs to customers 3) Need SEASONAL CAPACITY PRICES  REDUCE NET PEAK LOAD 4) Need RAMPING MARKETS  SMOOTH DAILY LOAD PATTERNS 5) These issues are important topics for future research

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