Optimizing Day-Ahead Electricity Market Prices:
Increasing the Total Surplus for Energy Exchange Istanbul
Asst. Prof. Dr. Kürsad Derinkuyu, Industrial Engineering Department, TOBB University of Economics and Technology.
April 13, Friday 13:30
EA-409
Abstract
We design a combinatorial auction to clear the Turkish day-ahead electricity market and we develop effective tabu search and genetic algorithms to solve the problem of matching bidders and maximizing social welfare within a reasonable amount of time for practical purposes. A double-sided blind combinatorial auction is used to determine electricity prices for day-ahead markets in Europe. Considering the integer requirements associated with market participants’ bids and the non-linear social welfare objective, a complicated problem arises in these markets.
We use nonlinear mixed-integer programming and tabu search and genetic algorithms. We analyze the performance of our algorithms by comparing them with solutions commercially available to the market operator. We also establish that genetic algorithms work better than tabu search for the Turkish day-ahead market. We deliver a practical tool using innovative optimization techniques to clear the Turkish day-ahead electricity market. We also modify our model to handle other similar European day-ahead markets and show that performances of our heuristics are robust under different auction designs.
Short Bio of the speaker
Kürşad Derinkuyu started at Ankara Science High School in 1994 and received his B.S. degree in Industrial Engineering from Bilkent University in 2002. He received his M.Sc. degree (ranked as 1st) from same department. Dr. Derinkuyu continued his graduate studies at Lehigh University and The University of Texas at Austin, and received his second M.Sc. degree (Management Science) in 2006 and Ph.D. degree (Operations Research and Industrial Engineering) in 2011 with 4.0 CGPAs. He is currently working at Industrial Engineering Department of TOBB University of Economics and Technology.