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Comparative Study on Distributed Generator Sizing Using Three Types of Particle Swarm Optimization

机译:三种粒子群优化算法在分布式发电机选型中的比较研究

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Total power losses in a distribution network can be minimized by installing Distributed Generator (DG) with correct size. In line with this objective, most of the researchers have used multiple types of optimization technique to regulate the DG's output to compute its optimal size. In this paper, a comparative studies of a new proposed Rank Evolutionary Particle Swarm Optimization (REPSO) method with Evolutionary Particle Swarm Optimization (EPSO) and Traditional Particle Swarm Optimization (PSO) is conducted. Both REPSO and EPSO are using the concept of Evolutionary Programming (EP) in Particle Swarm Optimization (PSO) process. The implementation of EP in PSO allows the entire particles to move toward the optimal value faster. A test on determining optimum size of DGs in 69 bus radial distribution system reveals the superiority of REPSO over PSO and EPSO.
机译:通过安装尺寸正确的分布式发电机(DG),可以最大程度地降低配电网络中的总功率损耗。为了实现这一目标,大多数研究人员已使用多种类型的优化技术来调节DG的输出以计算其最佳尺寸。本文对一种新的提出的秩进化粒子群优化(REPSO)方法与进化粒子群优化(EPSO)和传统粒子群优化(PSO)方法进行了比较研究。 REPSO和EPSO都在粒子群优化(PSO)过程中使用了进化规划(EP)的概念。在PSO中实施EP可使整个粒子更快地移向最佳值。通过一项确定69客车径向配电系统中DG最佳尺寸的测试,揭示了REPSO优于PSO和EPSO。

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