1. Electric Capacity Market Performance with Generation Investment and Renewables Cynthia Bothwell Benjamin Hobbs Johns Hopkins University Work Supported in part by NSF grants OISE 1243482 (WINDINSPIRE) and ECCS 1230788

2. Outline  Motivation  Methodology  General  Data  Model  Results  Without Renewables: Benchmark  Optimal Renewable Mix  Summary Findings  Next Steps

3. Motivation: In light of existing market failures, how does the introduction of intermittent renewable generation sources (wind and solar) affect electricity markets? In particular, how do renewables affect the performance of alternative energy & capacity market designs?

4. General approach: 1. Identify optimal generation mixes 2. Determine whether alternative market designs “support” the optimal mixes (are investments sufficiently profitable to support investment, but so profitable as to incent too much?) The optimal mix and participant profitability was examined including a variety of renewable penetrations to determine whether and how renewable generation impacts markets. Methodology:Overview

5. Methodology & Data  Modeled Two Different Systems using hourly actual load, wind, and solar data for one year.  Modeled new generation costs per EIA for CT and CC. Included an existing baseload plant with fixed cost 25% of new construction – limited to 45% of the peak load. Examined renewables with and without subsidies.

6. Methodology – The Model 1. Determined an optimal investment mix to serve each of the two systems by minimizing annual cost subject to a reserve margin. 2. Compared the cost for optimal operation with the revenues collected using four different electricity market mechanism: 1. Energy Only 2. Energy with Scarcity Pricing 3. Energy with capacity Market for dispatchable capacity 4. Energy with capacity market for all generation with intermittent contribution equal to the difference in the peak load with and without the renewable resource.

7. Results: Before renewables Lower gas price, lower cost: revenues close to cost Natural gas generator revenues are less than costs -Will not motivate new investment without capacity mechanism Existing baseload revenues are greater than cost -Motivation to modernize -Higher costs to consumers

8. Results: Optimal Mix with Renewables Reduction in portfolio cost No solar in optimal mix without subsidy Increase wind development optimal with high gas price Natural gas generator revenues are still less than costs Existing baseload revenues are still greater than cost but reduced -Less motivation to modernize -Motivation is removed if wind is built in excess of optimal due to subsidy

9. Summary Results  Scarcity pricing insufficient to meet reliability targets  Solar needs subsidies  Optimal wind development depends on fuel prices and may not guarantee profits  Wind may receive economic rents – if underdeveloped, subsidized, or higher capacity factor  Baseload capacity lacks incentives for modernization when gas prices are low and renewable investment is higher than the economically optimal level (RPS or subsidy).

10. Key Findings  Existing depreciated baseload can represent a larger distortion than renewables  Capacity market distortions are sensitive to varying factors which lead to different policy solutions  Generation adequacy determinations are also important in setting capacity mechanisms

11. Next Steps  Current work:  Expanding cases with more actual data  Looking at reliability criteria – reserve margin versus VOLL  Understanding magnitudes of market distortions  Consider alternative renewable capacity contribution methods  Analyze market equilibrium investment and operations under designs  Assess the resulting distortions, efficiency, consumer impacts, and incentives for renewable investment