Hybrid genetic algorithm and particle swarm for optimal power flow with non-smooth fuel cost functions

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• 作者：Abdelmalek Gacem ; Djilani Benattous
• 关键词：HGAPSO ; Non ; smooth cost function ; Optimal power flow ; Valve point effects
• 刊名：International Journal of System Assurance Engineering and Management
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：8
• 期：1-supp
• 页码：146-153
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Quality Control, Reliability, Safety and Risk; Engineering Economics, Organization, Logistics, Marketing;
• 出版者：Springer India
• ISSN：0976-4348
• 卷排序：8

文摘

This paper presents a hybrid genetic algorithm and particle swarm optimization (HGAPSO) for solving optimal power flow problem with non-smooth cost function and subjected to limits on generator real, reactive power outputs, bus voltages, transformer taps and power flow of transmission lines. In (HGAPSO), individuals in a new generation are created, not only by crossover and mutation operation as in (GA), but also by (PSO). The effectiveness of this algorithm is examined and tested for standard IEEE 30 bus system with six generating units. The results of the proposed technique are compared with that of PSO and other methods reported in the literature.