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Economic dispatch using stochastic whale optimization algorithm

descriptionPublicationkeyboard_double_arrow_right Conference object , Other literature type 01 Feb 2018Publisher:IEEEJournal:2018 International Conference on Innovative Trends in Computer Engineering (ITCE)

Authors: Karar Mahmoud; Salah Kamel; FatmaAlzahra Mohamed; Mohamed Abdel-Nasser;

doi: 10.1109/itce.2018.8316594

Economic dispatch using stochastic whale optimization algorithm

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Abstract

Economic dispatch aims to determine the optimal generated power from the generation units to meet the required load at the lowest fuel cost. In this paper, a stochastic whale optimization (SWO) method is proposed to solve the economic dispatch problem. Whale optimization algorithm is enhanced using mutation and crossover operators. To test the proposed method two systems (3 and 10 generating units) are tested. We compare the proposed SWO algorithm with whale optimization algorithm, artificial bee colony algorithm, dragonfly algorithm, ant lion algorithm, gray wolf optimization, and whale optimization algorithm with mutation only. The obtained results demonstrate the high efficiency of the proposed method compared with the other methods.

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Aswan University
Egypt

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	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	14
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%