Comprehensive overview of meta-heuristic algorithm applications on PV cell parameter identification

Comprehensive overview of meta-heuristic algorithm applications on PV cell parameter identification
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元启发式算法在光伏电池参数识别中的应用全面概述

DOI:
10.1016/j.enconman.2020.112595
复制
发表时间:
2020-03
影响因子:
10.4
通讯作者:
Sun Liming
Sun Liming
中科院分区:
工程技术1区
文献类型:
--
作者:
Yang Bo;Wang Jingbo;Zhang Xiaoshun;Yu Tao;Yao Wei;Shu Hongchun;Zeng Fang;Sun Liming

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准确的参数辨识对于光伏电池的精确建模和光伏系统特性分析至关重要,而输出i - v曲线的高度非线性使得这一问题非常棘手。因此,在过去的几年里,大量的研究引起了广泛的兴趣。由于计算机技术和群体智能的快速发展,各种有前途的元启发式算法被提出,进一步加速了这一趋势。本文旨在对元启发式算法及其相关变体在光伏电池参数识别中的应用进行全面综述。具体来说,这些算法分为四类,即基于生物学的算法、基于物理学的算法、基于社会学的算法和基于数学的算法。同时,对各种算法的评价标准和识别性能进行了深入的讨论。此外,为了对各种算法进行定量评价和比较,在每个算法的最后都提供了识别出的PV参数,包括具体误差和模拟的输出i - vorp - v曲线。此外,还对这些方法进行了全面的总结,以更具体地指导读者掌握和利用这些方法。最后,结语部分对所涉及的28种算法进行了总结,并对未来的发展提出了展望和建议。
Accurate parameter identification is crucial for a precise PV cell modelling and analysis of characteristics of PV systems, while high nonlinearity of outputI-Vcurve makes this problem extremely thorny. Hence, a large number of researches have aroused extensive interests in the past few years. Due to the rapid advancement of computer technology and swarm intelligence, various promising meta-heuristic algorithms have been proposed to further accelerate this trend. This paper aims to undertake a comprehensive review on meta-heuristic algorithms and related variants which have been applied on PV cell parameter identification. Particularly, these algorithms are classified into four categories, e.g., biology-based algorithms, physics-based algorithms, sociology-based algorithms and mathematics-based algorithms. Meanwhile, the evaluation criteria and identification performance of each algorithm are thoroughly addressed. Besides, in order to quantitatively evaluate and compare various algorithms, the identified PV parameters including the specific error and the simulated outputI-VorP-Vcurves are provided at the end of each algorithm. Moreover, a comprehensive summary is also introduced to more specifically guide the readers to grasp and utilize these approaches. Lastly, based on the covered twenty-eight algorithms, conclusion presents some perspectives and recommendations for future development.
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