摘要
针对采用干扰观察法时最大功率跟踪系统的输出功率在最大功率点附近小幅振荡的问题,设计了一种应用粒子群优化算法(particle swarm optimization,PSO)的模糊控制器,并将其应用于光伏发电系统的最大功率点跟踪(maximum power point tracking,MPPT)。该控制器采用粒子群算法优化模糊控制的隶属度函数,能够实时调整跟踪步长,保证系统在光照强度和温度变化时有较快的动态响应速度和较高的稳态精度。分别对采用干扰观察法、常规模糊控制方法和带粒子群优化的模糊控制器在相同情况进行了仿真和试验,结果证明了所提方法的有效性和鲁棒性。
To solve the problem of the output power of maximum power point tracking system by perturbation and observation（PO） method small oscillating around the maximum power point,a fuzzy controller with particle swarm optimization（PSO） algorithm was applied to maximum power point tracking（MPPT） of photovoltaic generation system.The PSO algorithm was applied to optimize the membership function of fuzzy controller and to accomplish real-time adjustment and tracking of step size in order to ensure that the system has a faster dynamic response speed and higher steady-state accuracy in case the light intensity or temperature varies.In this research,simulations and experiments were performed with the perturbation and observation method,the fuzzy control method and the fuzzy controller with PSO algorithm on the same condition,and the result demonstrates the effectiveness and robustness of the proposed method.
出处
《中国电机工程学报》
EI
CSCD
北大核心
2011年第6期52-57,共6页
Proceedings of the CSEE
关键词
光伏发电系统
最大功率跟踪
粒子群优化算法
模糊控制器
photovoltaic generation system
maximum power point tracking（MPPT）
particle swarm optimization（PSO） algorithm
fuzzy controller
