Dear all:
以下感謝張時中教授轉寄的演講訊息，資訊如下:
講者: Prof. Peter B. Luh
講題: Optimal Auctions for Deregulated Electricity Markets
時間: 16:00-17:15, 6/25 (Monday)
地點: 電機二館 142會議室
檢附演講摘要與講者資料如下; 凡全程參加演講者，可於專題演講課程加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: Peter.Luh@uconn.edu, 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.
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