Losses minimization in network reconfiguration for fault restoration via a uniform crossover of genetic algorithm

2015 International Symposium on Technology Management and Emerging Technologies (ISTMET) Pub Date : 2015-08-01 DOI:10.1109/ISTMET.2015.7359053

N. H. Shamsudin, M. Basir, A. Abdullah, M. F. Sulaima, E. Shair

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引用次数: 7

Abstract

Fault is a type of disturbance that affecting the continuity of the power supply to loads. Therefore, it is essential for a distribution power system to have a flexible, stable and more reliable load restoration system. The aim of the load restoration in this paper is to restore as many loads as possible through the network reconfiguration while minimizing the power losses after the occurrences of fault. Distribution network reconfiguration (DNR) is applied to determine the best combination of open switches that acts as the best route to optimize the reduction of power losses during load restoration process. An improved genetic algorithm (IGA) is proposed in this paper. The algorithm proposed is tested and validated on 69 IEEE bus using MATLAB software. A detail analysis is performed to demonstrate the effectiveness of IGA. The proposed method is applied and the effects of method on the power losses are examined. Results show that IGA method for load restoration via DNR is more effective compared with genetic algorithm (GA) solution.

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基于均匀交叉遗传算法的故障恢复网络重构中的损失最小化

故障是一种影响负载供电连续性的扰动。因此，一个灵活、稳定、可靠的负荷恢复系统对配电系统至关重要。本文的负荷恢复的目的是通过网络重构恢复尽可能多的负荷，同时使故障发生后的功率损失最小化。采用配电网重构(DNR)方法确定开路开关的最佳组合，使其成为负荷恢复过程中最大限度地减少电力损耗的最佳路径。提出了一种改进的遗传算法(IGA)。利用MATLAB软件在69 IEEE总线上对该算法进行了测试和验证。详细分析了IGA的有效性。应用了该方法，并分析了该方法对功率损耗的影响。结果表明，与遗传算法(GA)解决方案相比，IGA方法通过DNR恢复负荷更有效。

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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2015 International Symposium on Technology Management and Emerging Technologies (ISTMET)

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