Research On Grid-Connected Control Of Photovoltaic Power Generation And Its Island Detection Method

Solar energy is a recyclable energy source,in the future development must vigorously develop and utilize solar energy,which is the only way to promote sustainable economic development.Solar photovoltaic power generation has received great attention from international scholars,and has made certain progress in its development field,and the technological development in all aspects is more mature.Therefore,in-depth analysis of photovoltaic grid-connected power generation systems has many significances and roles for better promoting sustainable economic development.Among them,the maximum power point tracking control of photovoltaic power generation and the filtering process of LCL filter are the two main research contents in photovoltaic grid-connected control,and they are also the top priority of this paper.The basic working principle of the entire photovoltaic cell is introduced,and the model is built with the help of Matlab/Simulink,based on which an in-depth analysis is conducted.And the use of photovoltaic cell manufacturers to provide the parameters,on this basis to form P-V and I-V curves,for the simulation results of a comprehensive analysis,you can get to know the development characteristics of photovoltaic cells under different development conditions.The established photovoltaic cells are built into photovoltaic arrays to analyze the effects of different light and temperature conditions on the output characteristics of photovoltaic cells.Secondly,the advantages and disadvantages of several control methods in tracking the maximum power point are compared and analyzed,which paves the way for the improved particle swarm algorithm proposed later.The particle swarm optimization algorithm and the gray wolf algorithm are effectively integrated together,which can form a new particle swarm optimization algorithm,so that the advantages and disadvantages of the two algorithms are complementary,and the convergence curve and three-dimensional image of the three algorithms of the particle swarm algorithm,the gray wolf algorithm,and the improved particle swarm algorithm are simulated,and the optimization characteristics between the algorithms are compared,and on the basis of which,the particle swarm algorithm is improved and modified.The comprehensive comparison and analysis of different algorithms shows the basic efficiency of the entire algorithm.The third part is based on the passive damping control strategy,select different damping values to simulate the grid-connected system,verify the impact of the change of damping value on system stability for the traditional filter design process is cumbersome,need to continue to try to find the appropriate filter value of the problem,this paper proposes the fish swarm algorithm to improve the traditional filter design method,and details the working principle of the proposed fish swarm algorithm,using the proposed algorithm and the traditional algorithm to optimize the filter parameters,respectively,The obtained gridconnected simulation results are compared,and the superiority of the proposed algorithm in the filter optimization process is verified.Finally,several conventional methods of island detection are introduced,and the sliding film frequency shift method is selected to analyze the blind zone range under the parallel inverter and single inverter,and the detection performance of several detection methods is compared under the same load and parameters.