MPPT Control Of Potovoltaic System Under Local Shaow

As the first driving force for human economic development and social civilization,energy plays an irreplaceable role.However,with the reduction of fossil energy and the environmental pollution caused by it in recent years,it has become a painful point for the global economic development,so all countries have begun to develop and promote the use of new clean energy.Solar phot ovoltaic power generation is one of the key areas.The most important problem in solar power generation is how to improve its photoelectric conversion efficiency,and one of the means to improve its photoelectric conversion is the maximum power point track ing(Maximum Power Point Tracking,MPPT)technology,that is,the peak point of the output voltage and power of the system.The search for its crest has become the focus of practical engineering research.As the power engine structure in the whole system o f photovoltaic power generation,the photovoltaic array has an important influence and effect on the practical engineering application.However,due to the nonlinearity of the output and the multiple wave peak in the local shadow,the difficulty of the bes t wave peak search is added.A kind of recognition based on the recognition is proposed in this paper.The improved particle swarm optimization algorithm is applied to wave crest control and tracking:(1)Based on the mathematical model of photovoltaic panel,by analyzing the series parallel circuit of photovoltaic panel Road,the essence of the multi peak reason of the photovoltaic array in the local shadow environment is obtained,and the MATLAB/Simulink model is built to simulate and analyze how to find t he foundation for the wave peak search method under the local shadow environment.(2)Three classical MPPT algorithms are analyzed,and their advantages and disadvantages are compared with the constant voltage method,disturbance observation(Perturbation and method,PO)method and conductance increment(Incremental Conductance,INC)method.The parameters setting in the Boost circuit for adjusting the load impedance in MPPT are analyzed,so that the algorithm can better adjust the duty ratio D.(3)An improved basic particle swarm optimization(Particle Swarm Optimization,PSO)algorithm based on recognition is proposed.By analyzing the principle of the basic particle swarm algorithm,it is found that the particle can change the inertia factor and the iteration position formula to make the particle find the best value of the whole domain faster and better.By introducing the concept of recognition,the particle position is compared with the set value,and the particles with better recognition are directly entered into the next better iteration,and the particles with poor recognition are replaced by their historical optimal position,which continues to maintain the search precision and speed of the later particle swarm.Through the static and dynamic simulation analysis of the MATLAB/Simulink system module,the performance of the whole search wave peak based on the recognition particle swarm optimization algorithm is better than the basic particle swarm optimization algorithm.