期刊名称：Leonardo Electronic Journal of Practices and Technologies
印刷版ISSN：1583-1078
出版年度：2018
卷号：17
期号：32
页码：249-270
出版社：Academic Direct Publishing House
摘要：The current trend of study is to hybridize two and more algorithms to gain the bestsolution in the area of optimization problems. In this paper presents the recentlydeveloped hybrid optimization technique named PSO-GWO combines the frameworkof particle swarm optimization (PSO) with grey wolves optimization (GWO) to solvethe optimal power flow (OPF) problem. OPF is formulated as a nonlinear optimizationproblem with conflicting objectives and subjected to both equality and inequalityconstraints. The performance of this technique is deliberated and evaluated on thestandard IEEE 30-bus test system with a single objective and multi-objective casessuch as fuel cost minimization, Active power loss reduction, Voltage profileimprovement and Voltage stability enhancement, and is compared to approachesavailable in the literature. The hybrid PSO-GWO provides better results compared tothe original PSO, GWO, and other techniques mentioned in the literature as shown inthe simulation results.
关键词：Optimal power flow; Voltage stability; Active power loss; Emission; Constraints;Hybrid PSO-GWO.
