基于PIDPSS的农田肥力优化方法缓解SMIB波动

A. Sabo, Noor Izzri Abdul Wahab, M. Lutfi Othman, Mai Zurwatul Ahlam Mohd Jaffar
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引用次数: 2

摘要

本研究提出了在MATLAB/SIMULINK中设计用于抑制单机无限总线(SMIB)电力系统振荡的比例积分导数(PID) PSS (PIDPSS)。提出了一种受大自然启发的农田肥力算法(FFA),通过最小化鲁棒时域性能指标——时间平方乘误差平方的积分(ISTSE)目标函数来优化PIDPSS参数。通过与4种常用的时间积分指标进行比较,验证了ISTSE指标的稳健性,并与传统PIDPSS (CPIDPSS)和入侵杂草优化(IWO)算法进行了比较,验证了FFA PIDPSS在杂草分类中的合理应用。相量仿真结果表明,与IWO方法相比,FFA方法的ISTSE、速度偏差SMIB暂态响应的上升时间、稳定时间和峰值时间分别提高了35.16%、40.57%、77.1%和1%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mitigation of Oscillations in SMIB using a Novel Farmland Fertility Optimization based PIDPSS
In this study, the design of proportional integral derivative (PID) PSS (PIDPSS) is proposed for damping oscillations in single machine infinite bus (SMIB) power system in MATLAB/SIMULINK. A new metaheuristics method called Farmland Fertility Algorithm (FFA) inspired by nature is proposed to optimize the PIDPSS parameters via minimizing robust time domain performance indices called Integral of Squared Time multiplied by Squared Error (ISTSE) objective function. The robustness of the ISTSE index was tested by comparing it with four common time integral indices, also, the FFA PIDPSS was compare with Conventional PIDPSS (CPIDPSS) and Invasive Weed Optimization (IWO) algorithm for plausible application in. The phasor simulation results shows that the proposed ISTSE, the speed deviation SMIB transient response in terms of rise time, settling time, peak time were all remarkably improved by an amount of 35.16%, 40.57%, 77.1% and 1% respectively by the proposed FFA method compare to the IWO method.
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