Research On MPPT Control Strategy Of Photovoltaic Power Generation System

Nowadays,while we enjoy the convenience brought about by technological advancements,we are also concerned about the problem of energy scarcity,particularly the lack of traditional fossil fuels.In addition,fossil fuels also cause environmental pollution,which requires researchers to develop green energy.Solar energy is one of the green energy sources,widely used in the power industry due to its universality and lack of pollution.Currently,the efficiency of photovoltaic systems is limited by defects in photovoltaic materials,such as low utilization of solar energy.Furthermore,the difficult improvement of solar cell materials in the short term has led to the need for the appropriate selection of maximum power point tracking methods to improve the efficiency of photovoltaic system power generation.Through a photovoltaic cell Simulink simulation model,the output characteristics of PV cells were studied,and a dual-function variable step-size incremental conductance MPPT control strategy was proposed for the deficiencies of conventional variable step-size conductance methods.The tracking performance of the proposed method was analyzed through simulation.In addition,on the basis of intelligent control methods,an improved Equilibrium Optimizer was used to realize MPPT control of the photovoltaic system.A Simulink simulation model of the photovoltaic power generation system was constructed,and the tracking performance of the algorithm was analyzed.Specifically,the following work was completed:(1)The basic structure of PV cells,including P-type semiconductor,Ntype semiconductor,and P-N junction,were studied.Then,the mechanism of photovoltaic effect was investigated in detail,and the factors affecting the performance of PV cells,such as light intensity and temperature,were studied.Different models were further analyzed and compared,and a model better suited for practical engineering applications was selected.A PV cell model was constructed using Matlab/Simulink software,and the external output characteristics of PV cells were studied using the model.In addition,a photovoltaic array was formed by connecting PV cells in series using the PV cell simulation model,and the output characteristics of the photovoltaic array were studied based on the different light intensities given to each PV cell.(2)The principle of MPPT control was explored,and several traditional single peak MPPT control algorithms and several modern intelligent controlbased multi peak MPPT control methods were introduced.A Simulink model of the photovoltaic power generation system was utilized to analyze the tracking effect of the traditional INC method in photovoltaic MPPT systems,and the advantages and limitations of this algorithm were evaluated.Furthermore,several variable step-size INC methods were introduced,and a dual-function variable step-size INC method was proposed for the deficiencies of the variable step-size conductance method,introducing a dual-function step-size adjustment coefficient.A comparison was made between the tracking performance of the INC method before and after its improvement.According to the simulation results,the dual-function variable step-size conductance method not only exhibits less steady-state oscillation but also significantly enhances tracking accuracy.(3)Based on the MPPT principle,the Equilibrium Optimizer(EO)algorithm was used to realize MPPT control in the photovoltaic power generation system.To overcome the slow dynamic tracking speed of the EO algorithm,inspired by genetic algorithms and social network search algorithms,an MPPT control strategy based on Improved Equilibrium Optimizer was designed.The performance of the proposed MPPT control method was verified through simulation experiments,and the simulation results showed that the improved equilibrium optimizer algorithm had significant improvements in MPPT tracking accuracy and tracking speed.