Research On Output Characteristics And Maximum Power Tracking Of Photovoltaic Arrays Under Local Shadows

The energy crisis has become a major problem facing humanity today,and it has become an inevitable trend that the photovoltaic power generation industry has received extensive attention.As an important part of renewable energy,solar energy has always been valued by researchers.How to use it efficiently is the focus of photovoltaic power generation technology.Affected by the environment of the photovoltaic power generation system,shadow occlusion of the photovoltaic array is inevitable,and the output characteristics of the array will change greatly under the shadow.In order to improve the energy conversion efficiency,the correlation between photovoltaic array output characteristics and maximum power tracking under local shadow is of great significance.The main work of this paper is as follows:(1)Based on the mathematical model of photovoltaic cell engineering,the output characteristics of the photovoltaic array under uniform illumination were verified by simulation.The effects of string and parallel connection of battery components on the output characteristics of photovoltaic arrays under local shadow are analyzed in detail,and a phenomenon that there is no local peak of P-U curve is discussed.Then the mathematical model of the photovoltaic array under the shadow is established.The photovoltaic array is simulated in the Matlab/Simulink environment.The simulation results show that the I-U curve of the photovoltaic array is multi-knee and the P-U curve is multi-peak under local shadow.(2)Taking several photovoltaic arrays with different series-parallel structure as an example,the maximum power point power and maximum power point voltage of the PV array under different shadow distributions are recorded.The data results are summarized to summarize the general rule of the shadow distribution affecting the maximum power of the photovoltaic array.The series connection of the same or similar components in the photovoltaic array to the same branch results in a larger output power of the array,which can be optimized for maximum output power.Finally,the optimization idea is verified by several simulation examples.(3)The traditional MPPT methods are summarized and discussed,and their advantages and disadvantages are discussed.The traditional MPPT method will fall into the local peak point when tracking the maximum power point of the photovoltaic array under local shadow.For this problem,the paper focuses on the bacterial foraging algorithm and particle swarm algorithm in the intelligent algorithm,and analyzes and summarizes the advantages of the two.inferior.Aiming at the problem that the bacterial foraging algorithm is slow in tracking the global maximum power point,an improved method based on reducing the tracking range is proposed.On the other hand,the self-learning factor and social learning factor in the particle swarm algorithm are introduced into the bacteria foraging optimization algorithm.The performance of convergence rate is improved by the hybrid algorithm algorithm.Finally,the two improved methods are simulated by the programming module in Matlab/Simulink,and compared with the conventional bacterial foraging algorithm,the simulation results verify the effectiveness and rapidity of the improved method.