摘要
针对传统最大功率跟踪(MPPT)算法在跟踪局部阴影时的光伏最大功率失效问题,以及目前元启发式MPPT算法中较多初始种群数导致算法计算负担过大,寻优时间过长的现象,提出了一种新的蝴蝶算法(BOA)-爬山法(HC)混合MPPT控制算法。该算法利用BOA进行全局寻优,在搜索至全局最大功率附近时采用HC进行后续搜索。利用传统MPPT方法的快速收敛性来提高元启发式算法的搜索速度,减小BOA的搜索空间,加快整体算法的全局跟踪速度。利用MATLAB/Simulink仿真软件搭建了局部阴影下的光伏发电系统,并在相同种群数目下对粒子群(PSO)和BOA算法进行测试对比,验证了所提算法的有效性。
A new butterfly optimization algorithm(BOA)-hill climbing method(HC)hybrid MPPT control algorithm was proposed to solve the problem of photovoltaic maximum power failure when the traditional MPPT algorithm is under partial shading conditions,and the problem that the current metaheuristic MPPT algorithm has many initial populations,resulting in much computational burden and long optimization time.In this algorithm,the BOA was used for global optimization,and the HC was used for subsequent search when the search was near the global maximum power.The fast convergence of the traditional MPPT method was used to improve the search speed of the metaheuristic algorithm,reducing the search space of the BOA and accelerating the global tracking speed of the overall algorithm.The photovoltaic power generation system under local shadow was built by MATLAB/Simulink simulation software,and the particle swarm optimization(PSO)and BOA algorithms were tested and compared under the same population number to verify the effectiveness of the proposed algorithm.
作者
张鹏宇
赵晋斌
潘超
毛玲
王一鸣
ZHANG Pengyu;ZHAO Jinbin;PAN Chao;MAO Ling;WANG Yiming(School of Electrical Engineering,Shanghai University of Electric Power,Shanghai 200090,China;Ginlong Technologies Co.,Ltd.,Ningbo Zhejiang 315712,China)
出处
《电源技术》
CAS
北大核心
2023年第10期1346-1350,共5页
Chinese Journal of Power Sources
基金
国家自然科学基金(52177184)。
关键词
光伏
最大功率跟踪
蝴蝶优化算法
局部阴影
photovoltaic
maximum power point tracking
butterfly optimization algorithm
partial shading conditions
