文章基本信息

标题：MULTI-OBJECTIVE OPTIMAL REACTIVE POWER DISPATCH USING HYBRID TIME VARYING PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHM
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作者：SABHAN KANATA ; SUWARNO ; GIBSON HILMAN SIANIPAR 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2019
卷号：97
期号：19
页码：5103-5114
出版社：Journal of Theoretical and Applied
摘要：The hybrid time varying particle swarm optimization and genetic algorithm method (TVPSOGA) was introduced to solve multi-objective reactive power dispatch (MORPD) problems. MORPD as a non-linear multi-objective optimization problem that has the characteristics of non-convex, multi-constraint, and multi-variable which consists of a mixture of solutions that have discrete and continuous variables. The feasibility of the proposed method was tested on the IEEE 57-bus and IEEE 118-bus power systems. Comparison of simulation results shows the efficacy of the proposed optimization method compared to methods such as multi-objective enhanced particle swarm optimization (MOEPSO), multi-objective particle swarm optimization (MOPSO) and multi-objective ant lion optimization (MOALO) for the case of IEEE 57-bus power system. As for the case of the IEEE 118-bus power system, this method shows better efficacy compared to biogeography based optimization (BBO), the particle swarm optimization method with an aging leader and challengers (ALC-PSO), the enhanced gaussian bare-bones water cycle algorithm (NGBWCA) and PSO with a gravitational search algorithm (PSOGSA).
关键词：Time Varying Particle Swarm Optimization; Genetic Algorithm; Multi-Objective Reactive Power Dispatch; The Real Power Losses; The Total Voltage Deviation