Optimization research on hot spot effect algorithm of PV module based on MPPT control – Taking the main building of a university in Kunming as an example

IF 6 2区 工程技术 Q2 ENERGY & FUELS
Ying Li , Zihao Ni , Shuang Wang , Huihu Shao , Yong Chen , Fashe Li , Hua Wang
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引用次数: 0

Abstract

Rooftop photovoltaic (PV) systems, as a type of distributed PV, is limited by the roof area, and it is important to perform geometric layout optimization to enhance economic efficiency. In this study, we proposed a strategy of controllable shadow occlusion to optimize the layout scheme of PV panels, aiming to maximize the net income of power generation and use the algorithm to optimize the hot spot problem of PV modules. The results show when the local shading is 4/16 S, PV panels exhibit optimal economic performance when installed at 24°. Compared to the original layout scheme, the 25-year total power generated by the PV system increased by 31.42 %, and net income increased to 0.9495 million yuan from 0.8116 million yuan. Based on the optimal layout scheme, the grey wolf optimization algorithm combined with Logistic chaotic sequence (LGWO) is employed to optimize the issue of power transmission efficiency instability and hot spots in the PV system caused by partial shading. LGWO demonstrates better performance in terms of power tracking efficiency and time, which can avoid a local optimal solution, compared to the cuckoo search algorithm (CSA) and the particle swarm optimization algorithm (PSO). The averaged tracking time is increased by 0.85 s and 1.04 s, and the efficiency is increased by 0.22 % and 0.07 %. The simulation results are in good agreement with the experimental results. Therefore, this study provides a feasible approach for optimizing the layout of rooftop PV and ensuring the efficient and stable operation of PV cells.
基于MPPT控制的光伏组件热点效应算法优化研究——以昆明某高校主楼为例
屋顶光伏系统作为分布式光伏的一种,受屋顶面积的限制,对其进行几何布局优化是提高经济效益的重要途径。在本研究中,我们提出了一种可控阴影遮挡策略来优化光伏板布局方案,以最大化发电净收益为目标,并利用该算法来优化光伏组件的热点问题。结果表明,当局部遮阳为4/16 S时,光伏板在24°安装时具有最佳的经济性能。与原布局方案相比,光伏系统25年总发电量增长31.42%,净收入由811.16万元增加至949.5万元。在优化布局方案的基础上,采用灰狼优化算法结合Logistic混沌序列(LGWO)对部分遮阳引起的光伏系统输电效率不稳定和热点问题进行优化。与布谷鸟搜索算法(CSA)和粒子群优化算法(PSO)相比,LGWO在功率跟踪效率和时间方面表现出更好的性能,避免了局部最优解。平均跟踪时间分别提高0.85 s和1.04 s,效率分别提高0.22%和0.07%。仿真结果与实验结果吻合较好。因此,本研究为优化屋顶光伏布局,保证光伏电池高效稳定运行提供了可行的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Solar Energy
Solar Energy 工程技术-能源与燃料
CiteScore
13.90
自引率
9.00%
发文量
0
审稿时长
47 days
期刊介绍: Solar Energy welcomes manuscripts presenting information not previously published in journals on any aspect of solar energy research, development, application, measurement or policy. The term "solar energy" in this context includes the indirect uses such as wind energy and biomass
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