局部遮荫下基于改进金枪鱼算法的光伏最大功率点跟踪控制

Photovoltaic MPPT control under local shade based on improved TSO algorithm

光伏阵列在局部遮荫环境下的P-U特性曲线呈现多峰特性,导致传统最大功率点跟踪(MPPT)算法在跟踪最大功率时失效。为此,提出一种基于改进金枪鱼算法的光伏MPPT双层控制模型,在上层中将莱维飞行(Levy)策略和多项式变异策略嵌入金枪鱼算法中,构建莱维-多项式变异金枪鱼算法(LPTSO)来搜索全局功率最大点;在下层中采用扰动观察法对全局最大功率点进行局部跟踪,以降低局部遮荫环境下的功率振荡。将该双层控制模型应用于光伏MPPT仿真系统中,仿真实验结果表明,针对多峰MPPT控制,所提模型在收敛速度、跟踪效率、功率振荡等方面都有较大提升,该光伏MPPT双层控制模型能够有效解决局部遮荫环境下最大功率跟踪失效的问题。

The P-U characteristic curve of a photovoltaic array exhibits multi-peak characteristics in partially shaded environments,leading to the inefficiency of conventional maximum power point tracking(MPPT)algorithm in tracking the maximum power.To address this issue,this paper proposes a two-layer control model for photovoltaic MPPT based on an improved tuned swarm optimization(TSO)algorithm.In the upper layer,the Levy flight strategy and polynomial mutation strategy are embedded into tuna algorithm,creating the Levy-polynomial mutation tuna swam optimization(LPTSO)to search for the global maximum power point.In the lower layer,the perturbation observation method is employed to locally track the global maximum power point,thereby reducing power oscillations in local shading environments.The two-layer control model is applied to the photovoltaic MPPT simulation system,and the simulation experimental results show that,for multi-peak MPPT control,the proposed model achieves significant improvements in convergence speed,tracking efficiency,power oscillations,etc.In conclusion,the proposed two-layer control model for photovoltaic MPPT effectively addresses the issue of maximum power tracking failure in partially shaded environments.