In this paper, the hybridization of standard particle swarm optimisation (PSO) with the analytical method (2/3 ^rd 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.

中文翻译：

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智能电网分布式发电最优选址和规模的解析混合粒子群优化算法

本文将标准粒子群优化（PSO）与分析方法（2 / ^3rd规则），该方法被称为分析混合PSO（AHPSO）算法，用于优化配电网的选址和规模。所提出的AHPSO算法的实现是为了满足常规电力系统中均匀分布，逐渐分布，集中分布和随机分布的负载。为了证明所提算法的有效性，比较了两种情况下标准PSO和所提AHPSO算法的收敛速度和优化性能。在第一种情况下，通过IEEE 10总线系统比较了四种算法在四种不同负载分配下的性能。在第二种情况下，比较了两种算法在IEEE 10总线，IEEE 33总线，IEEE 69总线系统和韩国的实际配电系统中的性能。仿真结果表明，所提出的AHPSO算法的收敛速度明显快于标准PSO算法。将该算法的结果与解析算法的结果进行比较，结果相似。