江汉大学学报（自然科学版）2026，Vol.54Issue(3)：85-96,12.DOI:10.16389/j.cnki.cn42-1737/n.2026.03.010
局部遮荫下融合PSO&INC的MPPT研究
MPPT Study Combining PSO and INC under Partial Shading
摘要
Abstract
Changes in the maximum power of photovoltaic cells under partial shading directly affect the efficiency of photovoltaic systems.To address this issue,a hybrid method combining particle swarm optimization(PSO)and the incremental conductance(INC)method is proposed.By performing mean partitioning of the initial population,the corresponding multi-peak power curve can be effectively divided into different regions,thereby significantly improving the search speed.Then,the particle positions are updated according to a strategy combining the number of iterations and the global maximum of the population.Based on the calculated power variation,small-step incremental conductance(INC)is further adopted for local optimization,which effectively reduces the number of iterations and saves iteration time.Simulations under different scenarios of partial shading and dynamic shading were carried out in Simulink.The results show that,compared with the original particle swarm optimization algorithm,the proposed hybrid algorithm can achieve a photovoltaic efficiency of 98.20%,with the optimization speed improved by 59.46%.Experimental results further verify that the proposed power tracking method can effectively track the maximum power point of the photovoltaic array under partial shading,with the tracking speed increased by 50%and the tracking accuracy reaching 98.91%.关键词
均值分区/粒子群/局部遮荫/小步长INC/光伏发电Key words
mean partitioning/particle swarm optimization/partial shading/small-step INC/photovoltaic power generation分类
信息技术与安全科学引用本文复制引用
徐东,姜能惠,祖冉,张振..局部遮荫下融合PSO&INC的MPPT研究[J].江汉大学学报（自然科学版）,2026,54(3):85-96,12.基金项目
安徽省高校自然科学重点项目(2024AH05026,2025AH2HX2K30422) （2024AH05026,2025AH2HX2K30422）
2024年安徽省中青年教师培养行动项目优秀青年教师培育项目(YQYB2024181) （YQYB2024181）
2024年度芜湖市第二批科技计划项目(2024kj039) （2024kj039）
安徽机电职业技术学院横向科研项目(HX2025117) （HX2025117）
安徽机电职业技术学院校极科研项目(KY202503) （KY202503）
