Research On Maximum Power Point Tracking Control Strategy Of Photovoltaic Power Generation System

In recent years,due to the excessive dependence on traditional fossil energy in the rapid economic development,the non-renewable energy which has been stored for thousands of years will face the risk of exhaustion after only a few decades of consumption,and the use of these fossil energy has caused immeasurable harm to the environment.At present,countries all over the world have allocated a lot of energy in the development and utilization of new energy,in which photovoltaic power generation is the use of endless solar energy reserves,has become the focus of people’s attention.However,in practical engineering applications,the working environment of photovoltaic array is complex and changeable.When the photovoltaic array is in the local shadow condition,its power voltage output characteristic curve has multiple extreme points and has strong non-linearity.How to make the photovoltaic system work at the global maximum power point is a technical difficulty.As an important branch of photovoltaic power generation system,the research of maximum power point tracking technology plays a vital role in improving the efficiency of converting light energy into electric energy.Therefore,it is of great significance to improve the algorithm of maximum power point tracking.Firstly,the principle of photoelectric conversion of photovoltaic cell is introduced,and a practical mathematical model is established based on the single diode model of photovoltaic cells,and the hot spot effect and treatment method of photovoltaic arrays are analyzed.The influence of light intensity and temperature on the output characteristics of photovoltaic arrays is studied,which lays a theoretical foundation for the subsequent maximum power point tracking.Secondly,the application of the classical maximum power point tracking algorithm under uniform illumination conditions is analyzed,and the simulation model is established to verify the advantages and disadvantages of each algorithm.The constant voltage method is combined with the variable step size perturbation observation method,the output voltage when the system is started is set near the maximum power point by the constant voltage method.Then,by setting the step size transformation conditions,the variable step size perturbation observation method is use to track the maximum power point.The improved perturbation observation method effectively solves the contradiction that the tracking speed and tracking accuracy of the classical algorithm are difficult to meet simultaneously.As for the defect of the traditional algorithm,it is easy to track the local extreme value when the photovoltaic array is in local shadow.The initial position,inertia weight,learning factor and other parameters of the basic particle swarm optimization algorithm are improved,an improved particle swarm optimization algorithm is proposed.Finally,this algorithm is compared with the perturbation observation method and the elementary particle swarm optimization algorithm,and the results show that the improved particle swarm optimization algorithm has better performance in tracking speed,accuracy and stability.