Optimal sizing and siting of distributed generators using Big Bang Big Crunch method

Y. Hegazy, Mahmoud M. Othman, W. El-Khattam, A. Abdelaziz
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引用次数: 16

Abstract

The concept of integrating small generating units in the power system attracted the attention in the last few decades. Distributed generator (DG) reinforces the main generating station in covering the growing power demand. DG can be connected or disconnected easily from the network unlike the main power stations, thus providing higher flexibility. Good planned and operated DG has many benefits as economic savings, decrement of power losses, greater reliability and higher power quality. Optimal location and capacity of DGs plays a pivotal rule in achievement of gaining the maximum benefits from DGs, on the other side improper placement or sizing of DGs may cause undesirable effects. This paper applies the Big Bang Big Crunch optimization algorithm on balanced/ unbalanced distribution networks for optimal placement and sizing of distributed generators. The proposed algorithm deals with the optimization problems incorporating voltage controlled distributed generators for the sake of power loss minimization. The proposed algorithm is implemented in MATLAB environment and tested on the 69-bus feeder system and the IEEE 37-node feeder. Validation of the proposed method is done via comparing the results with published results obtained from other competing methods.
用大爆炸大压缩方法优化分布式发电机的尺寸和选址
在过去的几十年里,将小型发电机组集成到电力系统中的概念引起了人们的关注。分布式发电机(DG)加强了主发电站,以满足日益增长的电力需求。与主电站不同,DG可以很容易地与电网连接或断开,从而提供更高的灵活性。良好的规划和运行的DG具有许多好处,如节约经济,减少电力损失,提高可靠性和更高的电力质量。dg的最佳位置和容量是实现dg效益最大化的关键,但dg的位置和尺寸不当也会产生不良影响。本文将Big Bang Big Crunch优化算法应用于平衡/不平衡配电网中分布式发电机的最优配置和规模。该算法处理的是电压控制分布式发电机的优化问题,以达到功率损耗最小的目的。该算法在MATLAB环境下实现,并在69总线馈线系统和IEEE 37节点馈线系统上进行了测试。通过将结果与其他竞争方法获得的已发表结果进行比较,验证了所提出的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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