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作 者:齐高峰 杜齐 郭文豪 覃团发[1,3] QI Gao-feng;DU Qi;GUO Wen-hao;QIN Tuan-fa(School of Computer and Electronic Information,Guangxi University,Nanning Guangxi 530004,China;School of Electrical Engineering,Guangxi University,Nanning Guangxi530004,China;Guangxi Key Laboratory of Multimedia Communications and Network Technology,Nanning Guangxi 530004,China)
机构地区:[1]广西大学计算机与电子信息学院,广西南宁530004 [2]广西大学电气工程学院,广西南宁530004 [3]广西多媒体通讯与网络技术重点实验室,广西南宁530004
出 处:《计算机仿真》2024年第12期96-100,171,共6页Computer Simulation
基 金:广西重点研发计划(2022AB05028);2020年度南宁市创新创业领军人才(团队)“邕江计划”项目(2020006)。
摘 要:光伏阵列在局部遮荫的情况下,其输出特性呈现多峰值,在最大功率跟踪(maximum power point tracking,MPPT)过程中跟踪速度较慢,且跟踪精度不足。针对上述问题提出一种基于邻域搜索策略的蝴蝶优化算法(Butterfly Optimization Algorithm,BOA)和变步长扰动观察法(Perturbation Observation,PO)的融合改进算法。利用改进蝴蝶优化算法的全局搜索能力跟踪到最大功率点附近,通过变步长扰动观察法的局部搜索能力弥补前置算法跟踪精度不足的问题,使其快速准确的跟踪到最大功率点。光伏发电具有随机性和波动性,在应用中常与储能元件相结合,构成光储系统。为了结合实际应用,在MATLAB/Simulink中搭建光储系统模型分析,验证了上述算法在跟踪速度和精度上的优越性。Under partial shading conditions,photovoltaic arrays exhibit multi peaks output characteristics,slow tracking speed,and insufficient tracking accuracy during maximum power point tracking(MPPT).In this article,an improved algorithm based on neighborhood search strategy was presented,which combined the Butterfly Optimization Algorithm(BOA)with Perturbation Observation(PO).Firstly,the global search ability of the improved butterfly optimization algorithm was utilized to track near the maximum power point.Then,the local search ability of the variable step perturbation observation method was used to compensate for the insufficient tracking accuracy of the proposed algorithm,thus enabling it to track to the maximum power point quickly and accurately.Photovoltaic power generation has randomness and volatility,and is often combined with energy storage components in applications to form an optical storage system.Based on practical applications,an optical storage system model was built in MATLAB/Simulink for analysis,and the superiority of the proposed algorithm in tracking speed and accuracy was verified.
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