Associate Professor Tsung-Che Chiang

Department of Computer Science and Information Engineering
National Taiwan Normal University

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Hsuan-Jen Ko, Thammarsat Visutarrom, and Tsung-Che Chiang, Dynamic economic emission dispatch through evolutionary multiobjective optimization: An experimental study, Proc. of IEEE Symposium Series on Computational Intelligence (SSCI), pp. 750-759, Singapore, Dec. 4-7, 2022.

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Abstract

This paper addresses the dynamic economic emission dispatch (DEED) problem, which needs to allocate power output of generation units in a power system to satisfy power demand over consecutive time periods and minimize cost and emissions simultaneously. We propose a multiobjective evolutionary algorithm to solve the DEED problem. We investigate the effects of the algorithm components including the repair mechanism, selection mechanism, dynamic resource allocation, and dynamic mutation through comprehensive experiments on six test cases. We also compare our algorithm with 15 existing algorithms, and our algorithm shows competitive performance.

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Note. We ran our algorithm with the specified NFE for 20 runs. Then we collected the net set of non-dominated solutions from solutions obtained over 20 runs. The size of the net set could be over 100. Thus, we removed one solution with the worst rank and largest crowding distance at a time until the size reaches 100.