微电网多SPV分布式发电机组优化配置的粒子群算法

S. Dawoud, Xiangning Lin, Firas M. F. Flaih, Merfat I. Okba
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引用次数: 8

摘要

可再生分布式发电(RDG)对微电网的总体影响是积极的。这些rdg通常位于负荷中心附近,这带来了一些好处,例如;系统功率损耗;改善电压分布和稳定性;环境友好性,重新调度系统升级,提高可靠性。本文提出了基于粒子群算法的微电网中太阳能光伏(SPV)的最优选址问题。考虑到配电网的不同约束条件,将粒子群算法应用于改善径向电网的功率损耗。本文提出了一种新的平均总体电压稳定指标,可以量化微电网母线的电压稳定水平。利用贝塔概率分布函数计算太阳辐射。该技术已在33总线和69总线微电网系统上进行了测试。在电压分布和平均总电压稳定指数方面均有改善。为了验证所提出的粒子群算法,将结果与其他流行的算法进行了比较。
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PSO algorithm for optimal placement of multiple SPV based distributed generators in Microgrids
Renewable distributed generation (RDG) has an overall positive impact on a microgrid. These RDGs are usually located near to the load centers which lead to some benefits such as; system power loss; voltage profile and stability improvement; environmental friendliness, rescheduling system upgrading, and reliability enhancement. In this paper, the particle swarm optimization (PSO) has been proposed to find the optimal location of solar photovoltaic (SPV) based in a microgrid. PSO has been applied to improve the power losses of radial networks considering different constraints related to the distribution network. A novel average overall voltage stability index has been proposed, in this paper which can quantify voltage stability levels of buses in a microgrid. Beta probability distribution function has been used to calculate the solar radiation. The proposed technique has been tested on 33-bus and 69-bus microgrid system. The improvements in voltage profile and average overall voltage stability index of the RDGs have been observed. To confirm the suggested PSO technique the results have been compared with the other popular algorithms.
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