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首页> 外文会议>International Conference on Renewable Energy Research and Applications >Comparative Analysis of ABC, Bat, GWO and PSO Algorithms for MPPT in PV Systems
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Comparative Analysis of ABC, Bat, GWO and PSO Algorithms for MPPT in PV Systems

机译：光伏系统中MPPT的ABC，Bat，GWO和PSO算法的比较分析

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摘要

Traditional algorithms used to perform the maximum power point tracking (MPPT) may not reach the global maximum power point (GMPP) when the photovoltaic (PV) modules are subjected to partial shading condition. Therefore, this paper presents a comparative analysis involving four MPPT algorithms employed in a PV system subject to partial shading condition, being these four MPPT techniques based on artificial bee colony, bat, grey wolf optimization and particle swarm optimization algorithms, respectively. These algorithms are always able to track the GMPP, presenting lower power oscillations in steady-state. In addition, these algorithms are evaluated and compared to each other taking into account three different cases: (i) PV array operating at standard test condition with uniform solar irradiation; (ii) and (iii) PV array under different cases of partial shading. By means of computational simulation results, the performances of the presented MPPT algorithm are evaluated and compared to each other considering the power oscillations in steady-state, the tracking factor, as well as the convergence time to reach the GMPP.
机译：当光伏（PV）模块处于部分阴影条件下时，用于执行最大功率点跟踪（MPPT）的传统算法可能无法达到全局最大功率点（GMPP）。因此，本文提出了一种比较分析，涉及受部分遮蔽条件影响的光伏系统中采用的四种MPPT算法，分别是基于人工蜂群，蝙蝠，灰狼优化和粒子群优化算法的这四种MPPT技术。这些算法始终能够跟踪GMPP，从而在稳态下呈现出较低的功率振荡。此外，考虑到三种不同情况，对这些算法进行了评估并进行了比较：（i）在标准测试条件下以均匀的太阳辐射运行的光伏阵列; （ii）和（iii）不同阴影情况下的PV阵列。通过计算仿真结果，对所提出的MPPT算法的性能进行了评估，并在考虑稳态时的功率振荡，跟踪因子以及达到GMPP的收敛时间之间进行了比较。

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