Modified artificial wolf pack method for maximum power point tracking under partial shading condition

Shweta Gupta, K. Saurabh
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引用次数: 10

Abstract

Photovoltaic power generation systems operate at maximum power point to maximize the use of solar energy. MPP tracking (MPPT) is usually attained using several traditional methods. But during partial shading conditions, a PV panel shows multiple peaks in power versus voltage curve and traditional methods do not always promise to make operate PV panel at true MPP. This paper introduces modified artificial wolf pack (MAWP) algorithm for global maximum power point (GMPP) tracking under various conditions. The problem formulation, application of MAWP and the results are analyzed in this paper. The proposed method has been simulated on MATLAB/SIMULINK for one PV configuration under one shading pattern. The results have been compared with artificial bee colony (ABC) and particle swarm optimization (PSO) method which suggests that the proposed method is best amongst all MPPT alternatives.
部分遮阳条件下最大功率点跟踪的改进人工狼群方法
光伏发电系统在最大功率点运行,最大限度地利用太阳能。MPP跟踪(MPPT)通常使用几种传统方法来实现。但在部分遮阳条件下,光伏板在功率与电压曲线上显示多个峰值,传统方法并不总能保证光伏板在真正的MPP下运行。提出了一种改进的人工狼群(MAWP)算法,用于各种条件下全局最大功率点(GMPP)跟踪。本文对MAWP的问题提出、应用及结果进行了分析。在MATLAB/SIMULINK上对一种遮光模式下的PV构型进行了仿真。结果与人工蜂群(ABC)和粒子群优化(PSO)方法进行了比较,表明该方法是所有MPPT方案中最优的。
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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