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A bio-geography-based algorithm for optimal siting and sizing of distributed generators with an effective power factor model

机译:一种基于生物地理基于具有有效功率因数模型的分布式发电机尺寸的生物地理算法

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In this paper, a bio-geography-based optimization techniqueis proposed for optimal sizing and placement of multiple distributed generators to reduce system loss and to improve system voltage profiles in electric distribution systems. Distributed generation paves the way for installing generating sources in the vicinity of the loads, for improving the power factor of the system, and thereby significantly reducing total system losses. An effective power factor model is proposed to pre-set the power factor of each distributed generator placed at various locations in a distribution system. The bio-geography optimization algorithm is enhanced with a differential learning scheme to deal with the problems of high dimensionality and complex constraints. A sensitivity factor approach is presented to reduce the search space for the placement of distributed generators in the system. Numerical simulations are performed on the IEEE 33-bus and IEEE 69-bus systems and the results of the proposed method are compared with other methods reported in the literature. (C) 2018 Elsevier Ltd. All rights reserved.
机译:本文提出了一种基于生物地理学的优化技术,提出了多个分布式发电机的最佳施胶和放置,以降低系统损耗,并改善配电系统中的系统电压型材。分布式发电铺平了用于在负载附近安装发电源的方式,以改善系统的功率因数,从而显着降低总系统损耗。提出了一种有效的功率因数模型,将每个分布式发电机的功率因数预先设置在分配系统中的各个位置。生物地理优化算法通过差分学习方案增强,以应对高维度和复杂约束的问题。提出了一种灵敏度因子方法以减少系统中分布式发电机的放置的搜索空间。在IEEE 33总线和IEEE 69总线系统上执行数值模拟,并将所提出的方法的结果与文献中报道的其他方法进行比较。 (c)2018年elestvier有限公司保留所有权利。

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