Heuristic search algorithms to detect collusive opportunities in deregulated electricity markets

Yılmaz, Elif (2020) Heuristic search algorithms to detect collusive opportunities in deregulated electricity markets. [Thesis]

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Official URL: https://risc01.sabanciuniv.edu/record=b2486369 _ (Table of contents)


In deregulated electricity markets, the main objective is to maintain a competitive trading environment and satisfy demand at lowest possible cost. However, sustaining a competitive environment is challenging and collusion among the Power Generation Companies (GenCos) might exist. Therefore, the Independent System Operator (ISO) controls the auction mechanism as a decision-maker for the electricity distribution. In order to guide the ISO to detect collusion, we develop a search algorithm and its variations by using the bi-level programming problem in Aliabadi, Kaya & Sahin (2016). We create 26 instances of 3 different problem sizes to test the performance of the algorithms. We compare the results of the algorithms to the total enumeration algorithm, which is an exact method to detect collusion but may not be executed in reasonable time, and among themselves. Moreover, we experiment with the algorithms using alternative single-level formulations of the bi-level programming problem

Item Type:Thesis
Uncontrolled Keywords:tacit collusion. -- deregulated electricity markets. -- heuristic search algorithm. -- bi-level programming. -- gizli anlaşma. -- serbestleşmiş elektrik piyasası. -- sezgisel arama algoritması. -- iki seviyeli programlama.
Subjects:T Technology > T Technology (General) > T055.4-60.8 Industrial engineering. Management engineering
ID Code:41192
Deposited By:IC-Cataloging
Deposited On:25 Oct 2020 11:58
Last Modified:25 Oct 2020 11:58

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