A Novel MPPT(Maximum Power Point Tracking) Algorithm Based On A Modified Particle Swarm Optimization Algorithm In Photovoltaic System

As one of the renewable energy sources,photovoltaic power generation has gradually entered the daily life of people.Photovoltaic buildings,solar roofs,solar power stations and other complementary power stations have emerged in China,although compared with the traditional power generation technology,There are still many unsolved problems in photovoltaic systems,such as low voltage traversing,current bifurcation,chaos,maximum power tracking control,island and load forecasting,etc.,but with the development of science and technology,these problems will be overcome one by one,photovoltaic power generation technology will gradually mature.This paper is devoted to the research of maximum power tracking in photovoltaic system.Because the output voltage and current of photovoltaic system are all affected by external temperature and radiation,in order to improve the output power as much as possible,The research of maximum power tracking technology is very important.The specific contents of the study are as follows:Firstly,the principle of photovoltaic cell is analyzed,and the mathematical model of photovoltaic cell is established.The relationship between current,voltage and output power is demonstrated by two methods of calculation and simulation.Through the discussion of the mathematical model of photovoltaic cell,the basic principle of shadow phenomenon is expounded,and through the analysis and calculation of the formula,the corresponding solution,that is,the maximum power tracking technique,is put forward.Secondly,the working mechanism of mountain climbing algorithm and particle swarm optimization algorithm are analyzed,and the corresponding models of the two algorithms are established.The advantages and problems of traditional algorithm and intelligent algorithm in photovoltaic system are compared.Then,the concept of fuzzy logic is introduced,and a series of theoretical problems are studied.By combining the characteristics of fast optimization speed of fuzzy logic and strong convergence of particle swarm optimization algorithm,An improved particle swarm optimization algorithm is proposed.In order to test the effectiveness of this method,the simulation model of the improved PSO algorithm is designed and compared with the PSO algorithm.The experimental results show that the tracking speed of the improved algorithm is obviously improved,and the accuracy of the optimization is not reduced.Finally,in the case of shadow,the phenomenon of multiple peaks in the PV curve is analyzed,and an improved genetic algorithm is proposed,taking two photovoltaic cells in series as an example.The number of peak output characteristic curves in different cases is analyzed.The output characteristics and tracking performance are compared under different shadows.Simulation results show that the method has a strong tracking ability.