测试科学与仪器2024，Vol.15Issue(1)：64-71,8.DOI:10.62756/jmsi.1674-8042.2024007
局部阴影下基于GWO-P&Q混合算法的光伏最大功率点跟踪
Maximum photovoltaic power point tracking based on hybrid GWO-P&Q algorithm under local shadow
摘要
Abstract
In view of the problem of multiple peak values of P-U characteristic curve under a local shading environment,the traditional gray wolf optimization (GWO) is slow in convergence speed and low in accuracy of steady state at the late stage when tracking the maximum power point. Combining the advantages of GWO and perturbation & observation (P&O) method, an improved hybrid maximum power point tracking(MPPT) algorithm based on GWO-P&O was proposed. Firstly, optimized by the GWO, the algorithm was gradually close to the global MPPT. Then, P&O was introduced into the GWO at the late convergence stage, so that the local maximum power point of of photovoltaic power can be found at a faster speed while maintaining a high steady-state accuracy of the GWO, which overcomes the shortcomings of the traditional GWO algorithm. Finally, the proposed method was compared with the GWO under different environments. The results show that the proposed GWO-P&O method can improve the convergence speed in the late stage of the GWO when tracking the maximum power while ensuring high steady-state accuracy.关键词
灰狼优化算法/扰动观察法/局部遮阴/混合优化最大功率点跟踪算法/全局最大功率点Key words
gray wolf optimization(GWO)/perturbation & observation(P&Q) method/partial shading environment/hybrid maximum power point tracking (MPPT) algorithm/global maximum power point引用本文复制引用
赵峰,肖成锐,陈小强,王英..局部阴影下基于GWO-P&Q混合算法的光伏最大功率点跟踪[J].测试科学与仪器,2024,15(1):64-71,8.基金项目
This work was supported by National Natural Science Foundation of China(No.52067013) （No.52067013）
Natural Science Foundation of Gansu Province(No.21JR7RA280) （No.21JR7RA280）
