Congestion Management Using Grey Wolf Optimization in a Deregulated Power Market

Gajjala, Madhu Mohan and Ahmad, Aijaz (2022) Congestion Management Using Grey Wolf Optimization in a Deregulated Power Market. POLLACK PERIODICA : AN INTERNATIONAL JOURNAL FOR ENGINEERING AND INFORMATION SCIENCES, 17 (2). pp. 14-19. ISSN 1788-1994 (print); 1788-3911 (online)

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Abstract

Transmission congestion issues became more severe and difficult to control as the power sector became more deregulated. The grey wolf optimization algorithm is proposed to relieve congestion by rescheduling generation effectively, resulting in the least congestion cost. The selection of participating generators is based on sensitivity, and the proposed technique is used to determine the best-rescheduled output active power generation to minimize line overload. The IEEE-30 bus system is used to test the proposed optimization technique. It has been demonstrated that when compared to other algorithms like the real coded genetic algorithm, particle swarm optimization, and differential evolution algorithm, the proposed approach produces excellent results in terms of congestion cost.

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