Browsing by Author "Derinkuyu, K."
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Item Open Access An improved probability bound for the Approximate S-Lemma(Elsevier, 2007) Derinkuyu, K.; Pınar, M. Ç.; Camcı, A.The purpose of this note is to give a probability bound on symmetric matrices to improve an error bound in the Approximate S-Lemma used in establishing levels of conservatism results for approximate robust counterparts.Item Open Access On the S-procedure and some variants(Springer, 2006) Derinkuyu, K.; Pınar, M. Ç.We give a concise review and extension of S-procedure that is an instrumental tool in control theory and robust optimization analysis. We also discuss the approximate S-Lemma as well as its applications in robust optimization.Item Open Access Optimizing day-ahead electricity market prices: increasing the total surplus for energy exchange İstanbul(INFORMS: Institute for Operations Research and the Management Sciences, 2020) Derinkuyu, K.; Tanrısever, Fehmi; Kurt, N.; Ceyhan, G.Problem definition: 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. Academic/practical relevance: 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 nonlinear social welfare objective, a complicated problem arises. In Turkey, the total number of bids reaches 15,000, and this large problem needs to be solved within minutes every day. Given the practical time limit, solving this problem with standard optimization packages is not guaranteed, and therefore, heuristic algorithms are needed to quickly obtain a high-quality solution. Methodology: 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. Results: We provide structural results to reduce the problem size and then develop customized heuristics by exploiting the problem structure in the day-ahead market. Our algorithms are guaranteed to generate a feasible solution, and Energy Exchange Istanbul has been using them since June 2016, increasing its surplus by 448,418 Turkish liras (US$128,119) per day and 163,672,570 Turkish liras (US$46,763,591) per year, on average. We also establish that genetic algorithms work better than tabu search for the Turkish day-ahead market. Managerial implications: We deliver a practical tool using innovative optimization techniques to clear the Turkish day-ahead electricity market. We also modify our model to handle similar European day-ahead markets and show that performances of our heuristics are robust under different auction designs.Item Open Access Organization and functioning of liberalized electricity markets: An overview of the Dutch market(Elsevier Ltd, 2015) Tanrisever, F.; Derinkuyu, K.; Jongen, G.Abstract In this paper, we examine the organization and the functioning of the Dutch electricity market. First we describe the organization of the Dutch electricity supply chain and the role of the main market participants including the transmission system operator, distribution system operators, program responsible parties and metering companies. We then describe the organization of financial trading and clearing mechanism of electricity through the organized futures exchange (The European Energy Derivatives Exchange), and the spot market (Amsterdam Power Exchange) which includes the day-ahead market and intra-day markets. We also detail the functioning of the imbalance market and reserve capacity management in the Netherlands. Through a set of numerical analysis, we provide an exploratory analysis of the APX day-ahead spot prices and the real-time imbalance prices using electricity price data from 2002 to 2013. We observe the price spikes both in the day-ahead and imbalance markets usually occur around 6-10 AM and 5-7 PM. We also observe that in the imbalance market system overages happen significantly more often than shortages pointing out that the market tends to buy more than what is demanded. This could be explained by the risk attitude of the market participants in the imbalance market.