基于粒子群算法的光伏最大功率跟踪模糊控制器优化设计

IF 0.7 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
P.D. Barjoei, Mehrdad Kouhpaei
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引用次数: 0

摘要

太阳能电池板具有非线性的电流电压特性和指定的最大功率点,这取决于太阳辐射和环境温度等环境因素。在不同大气条件下,光伏系统的电压-功率曲线存在多个峰值,降低了最大功率跟踪技术的效率。本文提出了一种基于粒子群优化算法的模糊控制器优化设计方法,用于跟踪光伏系统在不同工况下的最大功率点,以提高系统的性能。该系统对粒子群进行优化,产生一个最优的工作系数,该系数随光伏参数的变化而变化,以获取最大功率。使用MATLAB软件进行的仿真结果显示了所提出方法的优点,即能够在短时间内跟踪最大功率点,并在环境条件变化相对较大的情况下保持输出波形。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal Design of Fuzzy Controller for Photovoltaic Maximum Power Tracking Using Particles Swarm Optimization Algorithm
Solar panels have non-linear current-voltage characteristics and a specified maximum power point, which depends on environmental factors like the solar radiation and ambient temperature. The voltage-power curve of the photovoltaic system has multiple peaks under different atmospheric conditions that reduce the efficiency of the maximum power tracking techniques. This paper proposes an optimal design of a fuzzy controller using particle swarm optimization algorithm to track the maximum power point of a photovoltaic system operating under different conditions to improve its performance. The proposed system optimizes the particle swarm to produce an optimal working coefficient, which varies with photovoltaic parameters to extract maximum power. Results of simulations – performed using the MATLAB software - show the advantages of the proposed method, namely the ability to track the maximum power point in a short time and maintain the output waveform despite the relatively high variations in environmental conditions.
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CiteScore
0.20
自引率
14.30%
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