ANN Based Static Var Compensator For Improved Power System Security

Rushali L. Kapse, V. Chandrakar
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Abstract

The main aim of this article is to determine the effective control signal for the function of damping oscillation by using Multilayer Feed Forward Network(MLFN) based SVC. MLFN based SVC is designed to achieve reduce settling time of response of different parameters during large and sudden disturbance in multimachine power system. The comparative analysis of proposed ANN based SVC with PI based SVC using MATLAB environment for testing and validation.
基于神经网络的静态无功补偿提高电力系统安全性
本文的主要目的是利用基于SVC的多层前馈网络(MLFN)确定阻尼振荡函数的有效控制信号。为了缩短多机电力系统在大、突发扰动下不同参数响应的稳定时间,设计了基于MLFN的SVC算法。利用MATLAB环境对所提出的基于神经网络的SVC与基于PI的SVC进行了对比分析,并进行了测试和验证。
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