基于群体搜索优化器的种内竞争和随机行走优化潮流

2013 IEEE Symposium on Swarm Intelligence (SIS) Pub Date : 2013-04-16 DOI:10.1109/SIS.2013.6615187

Yuanqing Li, Mengshi Li, Z. Ji, Qinghua Wu

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引用次数: 9

摘要

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

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).

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2013 IEEE Symposium on Swarm Intelligence (SIS)

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