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Improved particle swam optimization algorithm for OPF problems

机译:改进DPF问题的粒子群优化算法

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This work presents the solution of the optimal power flow (OPF) using particle swarm optimization (PSO) technique. The main goal of this paper is to verify the viability of using PSO problem composed by the different objective functions. Incorporation of nonstationary multistage assignment penalty function in solving OFF problems can significantly improve the convergence and gain more accurate values. The proposed PSO method is demonstrated and compared with linear programming (LP) approach and genetic algorithm (GA) approach on the standard IEEE 30-bus system. The results show that the proposed PSO method is capable of obtaining higher quality solutions efficiently in OFF problem.
机译:这项工作介绍了使用粒子群优化(PSO)技术的最佳功率流(OPF)的解决方案。本文的主要目标是验证使用不同客观函数组成的PSO问题的可行性。在解决问题时纳入非间断的多级分配惩罚功能可以显着提高收敛性并获得更准确的值。在标准IEEE 30总线系统上对所提出的PSO方法进行了说明并与线性编程(LP)方法和遗传算法(GA)方法进行了比较。结果表明,所提出的PSO方法能够有效地在问题中有效地获得更高质量的解决方案。

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