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Optimal Power Flow of Power Systems Using Hybrid Firefly and Particle Swarm Optimization Technique

机译:利用混合萤火虫和粒子群优化技术的功率系统的最佳电流

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This paper presents a new endeavor of using the Hybrid Firefly and Particle Swarm Optimization (HFPSO) technique in tackling the optimal power flow (OPF) problem for electric power networks. The fuel cost optimization represents the main target considering the system constraints. The decision variable of the OPF problem is chosen to be the generators output real power. The HFPSO technique is chosen to optimize the objective function and to determine the optimal solutions of the problem. Many IEEE test systems are included in this study to assure the soundness of the introduced technique such as the IEEE 14-bus, 30-bus, and 57-bus grids. To acquire a sensible outcome, actual load curves are taken into account during the examination. Simulation results are examined then investigated. They show the appropriateness and privilege of the presented HFPSO -based OPF problem over the genetic algorithm (GA) and the particle swarm optimization (PSO).
机译:本文介绍了使用混合萤火虫和粒子群优化(HFPSO)技术在解决电力网络的最佳功率流(OPF)问题时的新努力。考虑系统约束,燃料成本优化代表了主要目标。选择OPF问题的决策变量是发电机输出实际功率。选择HFPSO技术以优化目标函数并确定问题的最佳解决方案。本研究包括许多IEEE测试系统,以确保引入技术的健全性,例如IEEE 14总线,30公交车和57母线网格。为了获得合理的结果,在考试期间考虑实际的负载曲线。检查仿真结果然后调查。它们显示出通过遗传算法(GA)和粒子群优化(PSO)的呈现HFPSO的opled OPF问题的适当性和特权。

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