Smart Capacity Markets:Can they be Smart Enough?

Tim MountDepartment of Applied Economics and Management

Cornell University

*TDM2@cornell.edu

Smart Capacity MarketsWashington DC, November 9-10, 2009

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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 CornellEngineers Economists

Lindsay AndersonAlberto LamadridHsiao-Dong Chiang Surin ManeevitjitAndrew Hunter Tim MountBob Thomas Dick SchulerLang Tong Bill SchulzeMax Zhang

Ray Zimmerman

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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

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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

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30-BUS TEST NETWORK

Area 1- Urban- High Load- High Cost- VOLL = $10,000/MWh

Area 2- Rural- Low Load- Low Cost- VOLL = $5,000/MWh

Wind Farm+ 3xWind MW- Coal MW

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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

Annual Payments in the Wholesale Market

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Case 2: NORMAL Wind .0: 0MW of WindCase 3: NICE Wind .1: 26MW of WindCase 4: NASTY Wind .2: 52MW of Wind

.3: 78MW of Wind

.4: 105MW of Wind

NORMAL NICE NASTY

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 negative3) Revenues for Wind Generators are relatively small4) Customers may pay more with NASTY Wind

• WHAT ARE THE IMPLICATIONS FOR FINANCIAL ADEQUACY?

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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

Total Annual System Costs

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Case 2: NORMAL Wind .0: 0MW of WindCase 3: NICE Wind .1: 26MW of WindCase 4: NASTY Wind .2: 52MW of Wind

.3: 78MW of Wind

.4: 105MW of Wind

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

Need a New Dynamic Rate Structure

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Adding wind generation will result in: Wholesale Energy Prices going DOWN Capacity Prices going UP

All customers should pay for both Energy and CapacityReal-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

IDEAL Distribution Networks I

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THE PROBLEMImpractical for many Residential and Commercial customers topay for both Energy used and Capacity demanded:

Difficult to measure Capacity correctly for individual customersResponses to Real-Time Prices for Energy are relatively slowInformation overload for many customers inefficient response

A SOLUTIONAggregate the loads of “small” customers and manage them asa single Wholesale customer:

Better management of the aggregate load and peak capacity demandedRapid response using wireless signals/automatic controlsSimplifies the operations for Transmission System Operators

IDEAL Distribution Networks II

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Need a new generation of engineer/managers to operate and manage community distribution systems:

Manage new Distributed Energy Resources effectivelyReduce costs for customers by managing the aggregate peak loadProvide new capabilities to support the bulk-power grid

Cornell has proposed an Intelligent Dependable Energywith Active Load (IDEAL) campus network:

Diverse types of Distributed Energy Resources already existNew facilities for training students will be developed An IDEAL campus network will lead to IDEAL community networks

Capacity Markets I

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Objectives: 1) Ensure Generation Adequacy in the FUTURE2) Provide the “missing money” for generators3) Reduce the financial risk for new entrants4) Prorate costs to Load Serving Entities using actual peak loads

Implications:1) Determines an annual price for capacity2) Does not determine the correct incentives for loads

- seasonal prices for capacity REDUCE SYSTEM PEAK- hourly prices for capacity SMOOTH DAILY LOAD PATTERN

Capacity Markets II

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Future Objectives with IDEAL Community Networks: 1) Ensure Generation Adequacy of the BULK POWER GRID2) Forecast the peak system load for the BULK POWER GRID3) Reduce the financial risk for new entrants4) Prorate costs using actual peak loads at the SUBSTATION level5) DON’T TREAT LOAD RESPONSE AS NEGATIVE CAPACITY

Implications:1) All “customers” on the the Bulk Power Grid will be Wholesale2) IDEAL Operator/Managers will allocate costs to customers3) Need SEASONAL CAPACITY PRICES REDUCE NET PEAK LOAD4) Need RAMPING MARKETS SMOOTH DAILY LOAD PATTERNS5) These issues are important topics for future research

Cornell Combined Heat & Power Project

2 x 15MWGas turbines

Smart substation

THANK YOU

Questions?