GENETIC ALGORITHM MODEL FOR PROFIT MAXIMIZATION OF GENERATING COMPANIES IN DEREGULATED ELECTRICITY MARKETS

Author: Georgilakis, Pavlos

Source: Applied Artificial Intelligence, Volume 23, Number 6, July 2009 , pp. 538-552(15)

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Abstract:

In deregulated and rapidly changing electricity markets, there is strong interest on how to solve the new price-based unit commitment (PBUC) problem used by each generating company to optimize its generation schedule in order to maximize its profit. This article proposes a genetic algorithm (GA) solution to the PBUC problem. The advantages of the proposed GA are: 1) flexibility in modeling problem constraints because the PBUC problem is not decomposed either by time or by unit; 2) smooth and easier convergence to the optimum solution thanks to the proposed variable fitness function which not only penalizes solutions that violate the constraints but also this penalization is smoothly increasing as the number of generations increases; 3) easy implementation to work on parallel computers, and 4) production of multiple unit commitment schedules, some of which may be well suited to situations that may arise quickly due to unexpected contingencies. The method has been applied to systems of up to 120 units and the results show that the proposed GA constantly outperforms the Lagrangian relaxation PBUC method for systems with more than 60 units. Moreover, the difference between the worst and the best GA solution is very small, ranging from 0.10% to 0.49%.

Document Type: Research article

DOI: http://dx.doi.org/10.1080/08839510903078101

Affiliations: 1: Department of Production Engineering and Management, Technical University of Crete, Chania, Greece

Publication date: 2009-07-01

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