Faced with uncertainty of future electricity generation supply, many regional electricity markets have adopted or considered adopting capacity markets for electricity. We study the structure of these markets and in particular capacity supply auctions such as the one implemented by PJM Interconnection (PJM), a regional transmission organization. Participants bid generation capacity into the auction, and those that win receive a capacity payment in return for having this capacity available for generation at a future delivery date. The auctions can be classified as multi-unit uniform price auctions, though price is set according to a demand curve rather than by participants' bids. We find closed-form solutions for the optimal bids as a function of cost, study welfare impacts of the auction, and show how the results can be extended numerically for more complex situations. We then use these optimal bid functions in an agent-based simulation of electricity markets, comparing energy-only markets to capacity markets and measuring the impact on both the generators and consumers of electricity. Lastly we use our agent-based simulation model coupled with reinforcement learners to determine whether or not the optimal bid strategy discovered in the beginning can be learned over time by agents participating in the energy and capacity markets.Information, Risk, and Operations Management (IROM
