基于粒子群算法的信号光伏组件参数提取

Hamsa Nashoor, Khalid Yahya, Mahmoud Aldababsa, A. Amer, Saleh B. Abusuilik
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引用次数: 0

摘要

高性能太阳能电池是全球太阳能发展的趋势。对太阳能电池进行建模并准确识别其参数是有价值的。太阳能电池的单二极管模型(SDMs)已经被提出。在这个模型中,有几个参数没有确定,文献中提出了不同的方法来确定它们的理想值。然而,粒子群优化算法(PSO)最近被提出作为一种有效的估计太阳系模型参数的算法。此外,它还可以帮助研究人员增强先前提出的算法。本文在MATLAB环境下对PSO算法进行了实现,验证了分析结果和实验结果的正确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Parameter Extraction Based on PSO for A Signal PV Module Using MATLAB
High-performance solar cells are developing due to the global trend toward solar energy. It is worth modeling solar cells and identifying their parameters accurately. Single-diode models (SDMs) have been put forth for solar cells. In this model, several parameters are not determined, and different approaches have been put forth in the literature to determine their ideal values. However, particle swarm optimization (PSO) has been recently proposed as an efficient algorithm to estimate the solar systems' model parameters. Additionally, it assists researchers in enhancing the previously proposed algorithms. In this work, the PSO algorithm has been implemented in a MATLAB environment to verify the correctness of analytical and experimental results.
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