Research On Photovoltaic MPPT Control Strategy Based On SFSPSO Algorithm Under Partial Shadow

In recent years,photovoltaic power generation industry technology has developed rapidly,but due to low photoelectric conversion efficiency,high cost of power generation,it is difficult to achieve the expected economic benefits.The output power of the photovoltaic cell determines the cost of the entire photovoltaic power generation system.The output characteristics of photovoltaic cells are nonlinear and will be affected by external factors.PV arrays usually exposed outdoor at the same temperature,clouds,birds and other force majeure factors will cause the PV cells by light intensity change,lead to the output power of photovoltaic cells produce fluctuations,appear many local maximum power point,in order to get maximum power output,improve the efficiency of photovoltaic power generation,will be to maximum power point tracking of photovoltaic cells,The maximum power of the output system.In this paper,the influence of MPPT algorithm on the power output of solar photovoltaic modules under local shadow condition is studied.Therefore,the photovoltaic cell model was built based on Matlab/Simulink to study the output characteristics of the photovoltaic cell under the condition of uniform illumination and local shading,and the simulation model of the entire photovoltaic system was built.In order to better simulate the changing trend of illumination,this paper selects the annual illumination data of a photovoltaic power plant in Northwest China,uses DPC clustering and polynomial fitting to process the data,and evaluates the real climate conditions.Simulation and analysis of the disturbance observation method and the conductance increment method in the traditional control algorithm under different lighting conditions.The analysis found that the stability of the incremental conductance method under partial shadows is better,but the tracking speed is not fast enough.Therefore,the particle swarm algorithm with better tracking speed in the intelligent MPPT control algorithm is selected.The particle swarm algorithm can be divided into basic particle swarm algorithm and standard particle swarm algorithm.After function test.it is found that the optimization effect of standard particle swarm algorithm with inertial weight is added.better.However,under fast-changing local shadow conditions,the standard particle swarm algorithm will produce local jitter,which may fall into local peaks and cause power loss.In order to compensate for the local jitter problem of the standard particle swarm algorithm,the paper adopts the PSO(Stochastic Focusing Search PSO,SFSPSO)algorithm of the random focus search strategy.Through the function test,it is found that the optimization effect of the SFSPSO algorithm is better than that of the standard PSO algorithm.The photovoltaic MPPT control strategy is compared with the tracking effect of the standard PSO algorithm under the shadow condition simulated by the light change in a certain area in the northwest.It is found that the tracking speed and tracking accuracy of the SFSPSO algorithm are better improved,which can well improve the photovoltaic cell Output efficiency.