摘要
针对局部阴影环境及环境辐照度阶跃的问题,提出一种基于Z源逆变器的粒子群和模糊变步长电导增量MPPT算法。粒子群通过少量迭代搜索至最大功率点附近,再切换至模糊变步长电导增量法,不仅使得最大功率点跟踪过程用时短,还可保证最大功率点追踪的稳态精度。同时此算法针对辐照度阶跃变化的情况设置重启环节,以便在功率阶跃后能迅速跟踪至新的最大功率点。通过建立的仿真模型和搭建的试验平台验证算法的可行性和优越性。
Aiming at the partial shading condition and the step change of irradiance,an algorithm of particle swarm optimization(PSO)and fuzzy variable step incremental conductance method based on the Z-source inverter is proposed.Less iterations of PSO are used to search close to the maximum power point,and the fuzzy variable step incremental conductance method is switched. It not only requires less time for maximum power point tracking(MPPT),but also guarantees the steady state accuracy of MPPT. Besides,the restart process is set in the algorithm for the step change of irradiance. It can track the new maximum power point rapidly after the power step change. The feasibility and superiority of the algorithm is verified by established simulation models and experiments.
作者
梅润杰
张经炜
Mei Runjie;Zhang Jingwei(College of Energy and Electrical Engineering,Hohai University,Nanjing 211100,China)
出处
《太阳能学报》
EI
CAS
CSCD
北大核心
2020年第1期137-145,共9页
Acta Energiae Solaris Sinica
关键词
粒子群算法
最大功率点追踪
模糊控制
光伏发电
particle swarm optimization
maximum power point trackers
fuzzy control
photovoltaic generators
