基于动态种群规模差分进化(DynNP-DE)算法的光伏系统全局最大功率点跟踪

M. Tajuddin, S. M. Ayob, Z. Salam
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引用次数: 7

摘要

本文提出了一种基于种群的直接全局优化技术——动态种群大小差异进化(DynNP-DE)来处理部分遮阳现象。在该技术中,种群的大小显著减小,而不影响原始DE算法的鲁棒性。为了评估所提出的MPPT技术的有效性,该算法在升压转换器上实现,并通过几个部分阴影模式进行验证。仿真结果表明,改进后的算法收敛速度更快,能够处理部分阴影情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Global maximum power point tracking of PV system using dynamic population size differential evolution (DynNP-DE) algorithm
In this paper, a population-based direct global optimization technique called Dynamic Population Size Differential Evolution (DynNP-DE) to deal with partial shading occurrence is proposed. In this proposed technique, the size of the population is significantly reduced without compromising the robustness of the original DE algorithm. To evaluate the effectiveness of the proposed MPPT technique, the algorithm is implemented on a boost converter and validated through several partial-shading patterns. Simulation results show that the proposed modification yields faster convergence and capable to handle partial shading conditions.
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