MPPT Control Of Multi Peak PV Greenhouse Based On EV-IKMTOA Intelligent Optimization

The rapid development of photovoltaic power generation system in the actual environment can effectively alleviate the existing energy problems.However,due to the influence of weather and other factors,solar energy itself becomes uncontrollable energy.The partial shadow of photovoltaic array caused by external factors will cause energy loss to the photovoltaic power generation system.Therefore,to find a way to effectively improve the photoelectric conversion efficiency of photovoltaic array is an important means to ensure the stable operation of photovoltaic power generation system.In this paper,based on the shortcomings of the existing photovoltaic system,through the correct diagnosis of uniform illumination and uneven illumination conditions,the maximum power point is tracked and searched by using strategy switching,so that the photovoltaic array can output a smooth and stable maximum power value.(1)A power adaptive dynamic switching strategy based on the working condition of photovoltaic array is proposed.Firstly,the principle of solar cell power generation is analyzed,and the internal structure and working process of photovoltaic cell are analyzed;The influence of different light conditions and ambient temperature on the output characteristics of photovoltaic array is discussed;According to the local shadow environment caused by sand and dirt cover and moving clouds,the multi peak effect caused by different working conditions is studied;Based on this photovoltaic power generation system,a power adaptive dynamic switching search strategy is proposed,and the traditional detection method,improved current detection method and improved voltage detection method are studied to locate the faulty panels in the faulty branch.Theoretical analysis and comparative simulation results show that the voltage detection method is more reasonable and effective.(2)Aiming at the power extremum under uniform illumination,the optimization algorithm based on numerical integral area difference is used to search.According to the search characteristics of solar system for power extreme point,MPPT(maximum power point tracking)model is built to verify the feasibility and effectiveness of traditional single peak optimization strategy.The experimental results show that the traditional MPPT strategy(disturbance observation method,conductance increment method,constant voltage method,etc.)has the problem of low solar energy utilization in complex environment.Based on this,a single peak search strategy with adaptive step size is proposed to optimize the single peak photovoltaic power generation system.The simulation results show that this method has the tracking speed of constant voltage method,low steady-state oscillation characteristics and high search accuracy of incremental conductance method and disturbance observation method.(3)In order to solve the problem that it is difficult for molecular dynamics optimization algorithm to track the global maximum power point in uneven environment,a population diversity search strategy based on P-I search region is proposed.Particle swarm optimization(PSO)and bacterial foraging algorithm(BFA)are two search strategies for MPPT optimization of multi peak photovoltaic power generation system,which are easy to fall into local,low search accuracy and slow dynamic response.The algorithm adjusts the particle uniformity by calculating the variance,self-adjusting the number of iterations and population to speed up the convergence speed,reduces the maximum range of activity based on the P-I search region,and improves the convergence accuracy by using the optimal individual alternation combined with the improved step size.At the same time,the algorithm takes the external light intensity and temperature as the restart conditions of the algorithm.The simulation results show that the algorithm can jump out of the local peak,improve the convergence accuracy,and has excellent response ability in the dynamic environment,and can better realize the intelligent multi peak optimization MPPT control of photovoltaic greenhouse.(4)Research and development of GUI simulation platform and low-power experimental device for photovoltaic greenhouse MPPT control system.The semi-automatic GUI virtual interface of MATLAB software is used to simplify the setting.The virtual GUI mainly includes: entry interface,main interface,photovoltaic cell related parameter setting interface,photovoltaic cell series parallel connection mode design interface,photovoltaic greenhouse environment parameter setting interface and load parameter setting interface,MPPT control selection method interface,intelligent algorithm parameter setting interface,simulation operation result display interface.At the same time,through the hardware circuit design and software system programming of photovoltaic greenhouse MPPT control system,the experimental prototype is developed.The test results are basically close to the simulation results,which verifies the feasibility of the experimental prototype and the effectiveness of the proposed algorithm.