2011PSCE0279 1 Abstract—Presently, Independent System Operators (ISOs) in deregulated electricity markets in the U.S. use an auction method that minimizes the total bid cost when determining units to be on and their generation levels (Bid Cost Minimization or BCM). It has recently been shown that this method of auction does not provide minimal consumer payment costs for a given set of bids under the Market Clearing Price (MCP)-based or congestion- dependent Locational Marginal Price (LMP) scheme. Instead, an alternative auction method that directly minimizes the total consumer payment (Payment Cost Minimization or PCM) provides the payment-minimizing auction selection. Though the use of PCM minimizes consumer payments for a given set of bids for a day, it has not been fully illustrated that PCM minimizes payments over a longer time period with intelligent bidders that can adjust to the new auction mechanism. To address this important economic issue, a novel discrete game theoretic method of bidder behavior is used to model the competitive nature of generating companies in the day-ahead market. Numerical testing results show that PCM significantly reduces consumer payments with intelligent bidders. Simulation using a market simulator is also presented with similar results. Finally, insight into the potential benefits of PCM is briefly presented. Index Terms – Payment cost minimization (PCM), bid cost minimization (BCM), electricity auction, Nash equilibrium, strategic behavior, multi-agent simulation. I. INTRODUCTION HE Independent System Operators (ISOs) that oversee wholesale electricity markets in the U.S. use an auction mechanism to select supply and demand bids in the day-ahead market for energy and ancillary services. Subsequently, a pricing algorithm is executed to determine Market Clearing Prices (MCPs) or congestion-dependent Locational Marginal Prices (LMPs). Presently, ISOs employ the “bid cost minimization” (BCM) auction method that minimizes the total bid cost given the set of bids. However, since generating companies may not bid according to their true production costs, bid cost minimization may not always equate to social welfare maximization. Manuscript received September 30, 2010. This work was supported in part by the National Science Foundation under grants ECS-0621936 and ECCS- 1028870. D. P. Ghosh was with the Department of Electrical and Computer Engineering, University of Connecticut, and is now with the School of Electrical and Computer Engineering, Cornell University, Ithaca, NY 14853 USA (Phone: 607-255-4346; e-mail: dpg65@cornell.edu). P. B. Luh is with the Department of Electrical and Computer Engineering, University of Connecticut, Storrs, CT 06269-2157 USA (Phone: 860-486-4821; e-mail: peter.luh@uconn.edu). It has been shown recently that an alternative method of auction selection, known as “payment cost minimization” (PCM), results in a lower cost of energy for consumers than BCM does for a given set of supply bids for a day, where demand is assumed given for simplicity. This is because the MCP or LMP settlement scheme is not consistent with the BCM auction mechanism [1, 2]. However, market participants may behave differently when the PCM auction mechanism is used. Thus, it is important to determine if PCM can deliver lower energy prices consistently given the intelligent and competitive nature of generating companies. It has been shown that PCM can do this for a 24- hour matrix-based game theoretic model with the Nash equilibrium as the solution concept [3]. In the present study, it will be shown that the Nash equilibria of the PCM game consistently specify a strategy tuple that provides lower energy costs for consumers over a 14-day period. The effects of BCM and PCM are also studied using an electricity market simulator, EMCAS [4]. A four-supplier, multiple-day simulation was constructed with scaled real loads. It was observed that PCM lowered energy costs for consumers. Key improvements in this study over previous ones include the use of simulation techniques such as EMCAS and a mixed integer programming package, CPLEX, to execute the BCM and PCM auction selections. II. LITERATURE REVIEW Many studies analyzing BCM exist in the literature. Generally, the Nash equilibrium is used as a solution concept for bid and auction simulations. Many studies focus on continuous games as they reflect ISO markets. Further, [5, 6] use mathematical programming methods with solutions derived from the Karush-Kuhn-Tucker conditions. Due to the difficulty of modeling continuous games and the fact that important discrete unit startup and shut down decisions cannot be considered in such formulations, later studies employ a discrete game theoretic method, in which bid levels are discretized at several intervals, and Nash equilibria are searched among the strategy tuples. Meanwhile, few studies of PCM exist. Zhao et. al. employed a method of bid discretization and a novel algorithm for the equilibrium search while considering discrete unit startup and shut down decisions [7]. This method provides limited results on the potential long-term effects of PCM implementation. Here, a 14-day period is simulated using a similar method of discrete bidding. Additionally, a 30-day period is simulated using EMCAS. T Analysis and Simulation of Payment Cost Minimization and Bid Cost Minimization with Strategic Bidders Dipayan P. Ghosh and Peter B. Luh, Fellow, IEEE 978-1-61284-788-7/11/$26.00 ©2011 IEEE