Master'sOpen Access

Genetik algoritması kullanarak serbestleşmiş elektrik piyasalarında gizli anlaşmaları tespit etme

2019
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Advisor: Doç. Dr. Güvenç Şahin

Abstract (EN)

Deregulated electricity markets allow competition over the electricity price among the power companies. However, in an oligopolistic environment, the strategic behavior of the power companies in the electricity market may lead to collusive opportunities. The independent system operator (ISO) is an authorized entity which is responsible for administrating the electricity market. Therefore, ISO shall be able to detect and avoid collusive opportunities among generators. In this study, we propose a metaheuristics approach to assist ISO in the decision-making process to prevent collusions. We develop a method, based on principles of genetic algorithm to detect the collusive opportunities in deregulated electricity markets. We test our algorithm on three problems of varying size. Our results are promising in terms of both speed and accuracy. For the large-scale problem, our algorithm works much faster than the existing alternatives in the literature.

Author

Dr. Barış Esen

How to Cite

Barış Esen (Master Thesis). Genetik algoritması kullanarak serbestleşmiş elektrik piyasalarında gizli anlaşmaları tespit etme, 2019, Sabanci University.

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