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Optimal sizing and placement of distributed generation in Egyptian radial distribution systems using crow search algorithm

机译:使用乌鸦搜索算法在埃及径向配电系统中优化分布式发电的规模和布局

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In recent years, the integration of distributed generation (DG) sources in electrical distribution systems has become increasingly essential due to their multiple advantages such as power loss reduction, voltage profile improvement, and relieved system's congestion. These benefits can be obtained by optimal sizing and placement of the DG sources. In this paper, a recent population-based optimization, known as Crow Search Algorithm (CSA), is used for the sizing and placement of DG in radial distribution networks. Loss sensitivity factor (LSF) is used to initially determine the most candidate buses for DG installation. Three DG types have been examined. The proposed algorithm is applied to a real Egyptian distribution system, and the achieved results revealed the effectiveness of the CSA in reducing the network losses and maximizing the overall saving while considering various load types such as constant power, constant impedance, and constant current.
机译:近年来,由于分布式发电(DG)源具有多种优势,例如降低功率损耗,改善电压曲线和缓解系统拥堵,因此在配电系统中的集成已变得越来越重要。通过优化DG源的大小和放置可以获得这些好处。在本文中,最近的基于人口的优化方法被称为乌鸦搜索算法(CSA),用于在分布式配电网中确定DG的大小和位置。损耗灵敏度因子(LSF)用于最初确定用于DG安装的大多数候选总线。已经检查了三种DG类型。将该算法应用于实际的埃及配电系统,所获得的结果表明,在考虑各种负载类型(例如恒定功率,恒定阻抗和恒定电流)的同时,CSA在减少网络损耗和最大程度地节省总体成本方面的有效性。

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