基于粒子群算法的MPPT仿真及应用

Maximum Power Point Tracking Simulation and Application Based on Particle Swarm Optimization

利用PSIM软件建立了太阳能电池仿真模型。光伏模块的伏安特性曲线显示了在出现局部阴影时,使用传统的最大功率点跟踪(MPPT)方案跟踪多个局部的最大功率点(MPP)以获得全局MPP是很难的。鉴于此,提出了一种新型基于粒子群优化算法(PSO)的MPPT。仿真及实验结果表明,即使在复杂的条件下,光伏模块的输出电压也能够稳定运行在MPP附近,基于PSO的跟踪算法为实时光伏系统提供了一个可行的替代解决方案。

Abstract：The PSIM is used to build the simulation model of solar cell.The U-I characteristic of cell exhibits multiple local maximum power points（MPP） during partial shading,making it difficult to find the global MPP.To overcome this diffculty, this paper proposes a novel maximum power point tracking （MPPT） algorithm by introducing a particle swarm optimization（PSO） technique.Simulation and experimental results show that even under complex conditions, the output voltage of PV modules maintains near MPP, this PSO-based tracking scheme provides a feasible alternative solution to real-time PV systems.