During the Fall and Spring semesters, EPIC presents the Energy Seminar Series with speakers from around the region. These experts share valuable information and their insight into trends and news that is related to energy. Seminars are FREE and are open to students, faculty, and the public. Pizza is included so please register to attend.
Virtual bidding is a financial mechanism that allows participants to speculate on the price spread between day-ahead and real-time wholesale electricity markets. We employ statistical learning methods to show that virtual bidding improves financial efficiency by narrowing the room for arbitrage. We then formulate a two-settlement market model and use it to analyze market data. We find that virtual bidding improves economic efficiency by reducing the system generation cost. Notwithstanding the empirical evidence of its effectiveness, virtual bidding has not fully eliminated market inefficiency, and we propose strategies that extract profits beyond those of the actual virtual bids. Lastly, we conduct a game-theoretic analysis based on the two-settlement model to develop the theory of virtual bidding. The analysis leads to the interpretation of spread as a measure of the average forecast accuracy of the market participants, and implies that introducing more qualified virtual bidders into the market can improve market efficiency.
About the Speaker
Wenyuan Tang is an assistant professor in the Department of Electrical and Computer Engineering at North Carolina State University. He received the B.Eng. degree in electrical engineering from Tsinghua University, Beijing, China, in 2008. He received the M.S. degree in electrical engineering, the M.A. degree in applied mathematics, and the Ph.D. degree in electrical engineering from the University of Southern California, Los Angeles, CA, USA, in 2010, 2014, and 2015, respectively. Prior to joining the NC State faculty in 2017, he was a postdoctoral scholar at the University of California, Berkeley and Stanford University. His research interests include power system operation, energy economics, and data analytics for smart grids.
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