Research On MPPT Of Photovoltaic Power Generation System Considering Multi-extreme Point Conditions

Nowadays,photovoltaic power generation as one of the many ways to use solar energy for power generation,its applications are increasingly wide.In practical application,there may be some obstructions on the top of the photovoltaic array,the output characteristic curve of the photovoltaic array will show multiple power extremum points.In order to track the maximum power point of photovoltaic quickly and accurately,two improved maximum power point tracking algorithms are proposed based on the conductance increment method and the drosophila algorithm,and the effectiveness of the proposed algorithms are validated based on simulation results.The main research work of this thesis includes:Firstly,the mathematical model of photovoltaic cell is established,and the expressions of output voltage and current are deduced by analyzing the model.The simulation model of single photovoltaic cell and photovoltaic array is established in Simulink,and the output characteristics of and photovoltaic array under the occlusion are analyzed.In view of the series parallel mismatch of photovoltaic cells,this thesis makes a brief analysis and gives common solutions.Secondly,in case of sudden change of environment,a power prediction variable step conductance increment method is proposed.In order to solve the problem that the incremental condectance method cannot guarantee the tracking speed and the steady-state accuracy at the same time when tracking the maximum power point of photovoltaic,the step coefficient of incremental conductance method is improved.In order to avoid the power loss of the algorithm in the case of environmental mutation,power prediction technology is added to the algorithm.Finally,through the simulation example,through the comparison with the existing algorithm,the proposed algorithm is verified to be fast and stable.Finally,for local occlusion,based on the algorithm of drosophila,a maximum power point tracking(MPPT)algorithm based on adaptive variable step size drosophila algorithm is proposed.The proposed algorithm adopts the adaptive variable step length Levy flight strategy,and adds the avoidance of local optimal factor into the determination formula of taste concentration of drosophila,so as to update the diversity of the search direction and expand the search range when the drosophila population searches for food,and effectively solve the problem of local optimal in the algorithm.Finally,the simulation results show that the proposed algorithm is fast tracking and good steady-state under normal illumination and local occlusion.