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Analytical Hybrid Particle Swarm Optimization Algorithm for Optimal Siting and Sizing of Distributed Generation in Smart Grid

机译:分析混合粒子群综合优化算法,智能电网中分布式发电的优化选址和尺寸

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摘要

In this paper, the hybridization of standard particle swarm optimisation (PSO) with the analytical method (2/3rd rule) is proposed, which is called as analytical hybrid PSO (AHPSO) algorithm used for the optimal siting and sizing of distribution generation. The proposed AHPSO algorithm is implemented to cater for uniformly distributed, increasingly distributed, centrally distributed, and randomly distributed loads in conventional power systems. To demonstrate the effectiveness of the proposed algorithm, the convergence speed and optimization performances of standard PSO and the proposed AHPSO algorithms are compared for two cases. In the first case, the performances of both the algorithms are compared for four different load distributions via an IEEE 10-bus system. In the second case, the performances of both the algorithms are compared for IEEE 10-bus, IEEE 33-bus, IEEE 69-bus systems, and a real distribution system of Korea. Simulation results show that the proposed AHPSO algorithm converges significantly faster than the standard PSO. The results of the proposed algorithm are compared with those of an analytical algorithm, and the results of them are similar.
机译:在本文中,提出了标准粒子群优化(PSO)与分析方法(2/3D规则)的杂交,其称为用于最佳选址和分布生成尺寸的分析混合PSO(AHPSO)算法。所提出的AHPSO算法被实施为迎合统一分布的,越来越多的分布式,集中分布的和随机分布的负载在传统的电力系统中。为了证明所提出的算法的有效性,将标准PSO的收敛速度和优化性能进行了比较了两种情况。在第一种情况下,通过IEEE 10-BUS系统比较了两种不同负载分布的算法的性能。在第二种情况下,将算法的性能与IEEE 10总线,IEEE 33-BUS,IEEE 69总线系统和韩国的真正分配系统进行比较。仿真结果表明,所提出的AHPSO算法会收敛比标准PSO更快。将所提出的算法的结果与分析算法的结果进行比较,它们的结果是相似的。

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