Optimal power flow using group search optimizer with intraspecific competition and lévy walk

Yuanqing Li, Mengshi Li, Z. Ji, Qinghua Wu
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引用次数: 9

Abstract

This paper presents an enhanced group search optimizer (GSO), group search optimizer with intraspecific competition and lévy walk (GSOICLW), to solve the optimal power flow (OPF) problem. GSOICLW s a more biologically realistic algorithm and performs better balance between global and local searching than GSO n hat intraspecific competition IC) and lévy walk (LW) are introduced o GSO. GSOICLW is tested or the OPF problem on the IEEE 30-bus power system, with green house gases emission constraint considered. Simulation results demonstrate the accuracy and reliability of the proposed algorithm, compared with other evolutionary algorithms EAs).
基于群体搜索优化器的种内竞争和随机行走优化潮流
针对最优潮流问题,提出了一种改进的群体搜索优化器(GSO),即具有种群内竞争和种群内游动的群体搜索优化器(GSOICLW)。GSOICLW是一种更符合生物现实的算法,在引入种内竞争IC (intra - specific competition IC)和LW (LW)后,比GSO更好地平衡了全局和局部搜索。GSOICLW在考虑温室气体排放约束的IEEE 30总线电力系统上对OPF问题进行了测试。仿真结果验证了该算法的准确性和可靠性,并与其他进化算法进行了比较。
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