Optimal location and initial parameter settings of multiple TCSCs for reactive power planning using genetic algorithms

N. Padhy, M. Abdel-Moamen, B. Praveen Kumar
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引用次数: 31

Abstract

In this paper, a genetic algorithms based optimal reactive power planning model incorporating FACTS devices has been presented. Optimal placement of multiple FACTS devices will naturally control the overall reactive power requirements. But the mathematical complexity and hence the solution time increases for reactive power planning of large power networks with multiple FACTS devices. To obtain a feasible and suboptimal solution for reactive power planning, optimal location of FACTS devices and its parameters have been determined using simple genetic algorithms. Genetic algorithm, performed on two parameters: the optimal location of the devices and their control parameter and then the fitness function has been determined using quasi-Newton algorithm based optimal power flows for minimization of reactive power losses and generations. The performance of the proposed algorithm has been tested for IEEE-30 systems with multiple TCSC devices. It has also been observed that the proposed algorithm can be applied to larger systems and do not suffer with computational difficulties.
基于遗传算法的无功规划中多个tscs的最优位置和初始参数设置
本文提出了一种基于遗传算法的包含FACTS器件的最优无功规划模型。多个FACTS器件的最佳放置自然会控制总体无功功率需求。但是,对于具有多个fact设备的大型电网的无功规划,其数学复杂度和求解时间都会增加。为了获得可行的、次优的无功规划方案,采用简单的遗传算法确定了FACTS器件的最优位置及其参数。采用遗传算法,对设备的最优位置和控制参数两个参数进行优化,然后利用拟牛顿算法确定了最优潮流的适应度函数,以实现无功损耗和代数的最小化。该算法的性能已在具有多个TCSC设备的IEEE-30系统中进行了测试。我们还观察到,所提出的算法可以应用于更大的系统,并且没有计算困难。
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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