基于改进粒子群优化模糊控制的MPPT算法研究

Research on MPPT Algorithm Based on Improved Particle Swarm Optimization Fuzzy Control

在光照强度和温度变化时,常规的最大功率点跟踪(MPPT)算法难以快速准确地跟踪光伏系统最大功率点。针对此问题,设计了一种改进粒子群优化算法(PSO)的模糊控制器。首先,依据常规MPPT特性,设计了一种带调整因子的模糊控制算法以快速收敛到最大功率点;然后,采用参数自适应PSO对设计的模糊控制器调整因子进行动态优化。仿真结果表明:所设计的参数自适应PSO优化模糊控制器能快速准确地跟踪最大功率点,保证了MPPT的动态响应速度和稳态精度,提高了光伏系统的工作效率。

When the light intensity and temperature change in photovoltaic system, the conventional maximum power point tracking(MPPT) algorithm was difficult to track the maximum power point quickly and accurately. Aiming at this problem, a fuzzy controller based on improved particle swarm optimization(PSO) was designed. Firstly, according to the characteristics of conventional MPPT algorithm, a fuzzy control algorithm with adjusting factor was designed to rapidly converge to the maximum power point. Then, parameters adaptive PSO was used to dynamically optimize the adjusting factors of the designed fuzzy controller. The simulation results showed that the designed parameters adaptive PSO optimized fuzzy controller could track the maximum power point quickly and accurately, which ensured the dynamic response speed and steady-state accuracy of MPPT and improved the work efficiency of photovoltaic system.