Dear all: 以下感谢张时中教授转寄的演讲讯息，资讯如下: 讲者: Prof. Peter B. Luh 讲题: Optimal Auctions for Deregulated Electricity Markets 时间: 16:00-17:15, 6/25 (Monday) 地点: 电机二馆 142会议室 检附演讲摘要与讲者资料如下; 凡全程参加演讲者，可於专题演讲课程加3分。 Optimal Auctions for Deregulated Electricity Markets Peter B. Luh SNET Professor and Head, Electrical & Computer Engineering, University of Connecticut Storrs, CT 06269-2157 Email: [email protected], URL: http://www.engr.uconn.edu/msl/ Abstract In deregulated electricity markets, auction mechanisms are used to select supply bids for energy and ancillary services. Currently, most Independent System Operators in the US use a “bid cost minimization” auction mechanism that minimizes total supply bid costs to select bids, and afterwards settle the market based on market-clearing prices. Consequently, the consumer payments could be significantly higher than the minimized bid cost from the auction. This gives rise to “payment cost minimization,” an alternative auction mechanism that directly minimizes consumer payments. A review of literature shows that with the same set of supply bids, payment cost minimization leads to reduced consumer payments as compared to bid cost minimization. While methods for minimizing offer costs abound, limited approaches for minimization of payment costs have been reported. This talk presents an effective method for directly minimizing payment costs. In view of the specific features of the problem including the non-separability of its objective function, the discontinuity of offer curves, and the maximum term in defining MCPs, our key idea is to use augmented Lagrangian relaxation, and to form and solve offer and MCP subproblems by using the surrogate optimization framework. Numerical testing results demonstrate that the method is effective, and the resulting payment costs are significantly lower than what are obtained by minimizing the offer costs for a given set of offers. Additionally, strategic behaviors of suppliers are studied within the game theoretic framework for the two auction mechanisms. General matrix games are solved by using the approximate Nash concept and with our auction algorithms developed as the core. Testing results demonstrate the cost savings for consumers under payment cost minimization as compared to bid cost minimization. Bio sketch. Peter B. Luh received his B.S. in Electrical Engineering from National Taiwan University , M.S. in Aeronautics and Astronautics from M.I.T., and Ph.D. in Applied Mathematics from Harvard University . He has been with the University of Connecticut since 1980, and currently is the SNET Professor of Communications & Information Technologies and Head of the Department of Electrical and Computer Engineering. He is a Fellow of IEEE, the founding Editor-in-Chief of the new IEEE Transactions on Automation Science and Engineering, an Associate Editor of IIE Transactions on Design and Manufacturing, was the Editor-in-Chief of IEEE Transactions on Robotics and Automation (1999-2003), and Publications Vice President Elect of IEEE Robotics and Automation Society. -- 对人有感情 所以择善固执 也所以顽冥不灵 对物有感情 所以知所取舍 也所以易役於物 对回忆有感情 所以有笑有泪 也所以魂萦牵梦 牵肠挂肚 --

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