Optimal position and setting of svc using heuristic optimization techniques

R. Agrawal, S. K. Bharadwaj, D. Kothari
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引用次数: 2

Abstract

During the last decade, there has been an increasing application of Flexible AC transmission system (FACTS) devices in power system due to its numerous advantages. However, to derive maximum benefits their location and rating should be optimal. This paper presents two heuristic optimization techniques, namely Particle Swarm Optimization (PSO) and Teaching Learning Based Optimization (TLBO), to ascertain to optimal location and value of static VAR compensator (SVC) in a power system. In the present study installation cost of SVC and transmission loss minimization are considered as the objective functions. The optimal location and the size of SVC are performed on the different loading condition using PSO and TLBO along with load flow. To show the applicability and validity of the algorithms, IEEE 14 bus power system is used. The simulation results of PSO and TLBO have been compared and presented in the present study.
基于启发式优化技术的svc最优位置与设置
近十年来,柔性交流输电系统(FACTS)由于其诸多优点,在电力系统中得到了越来越多的应用。然而,为了获得最大的利益,它们的位置和评级应该是最优的。针对电力系统中静态无功补偿器(SVC)的最优位置和最优取值问题,提出了两种启发式优化技术——粒子群算法(PSO)和基于教学的优化算法(TLBO)。本文以SVC的安装成本和传输损耗最小化为目标函数。采用PSO法和TLBO法对不同载荷条件下SVC的最优位置和尺寸进行了计算,并对载荷流进行了分析。为验证算法的适用性和有效性,以IEEE 14总线供电系统为例。本研究比较了PSO和TLBO的仿真结果。
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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