Research On Maximum Power Point Tracking Strategy Of Photovoltaic Cells Under Partial Shading Conditions

With the aggravation of the energy crisis and the increasingly serious environmental pollution,people have realized that it is an inevitable trend to change the energy structure and utilize renewable energy actively,and the cleanliness of solar energy has drawn worldwide attention.However,the low photoelectric conversion efficiency of photovoltaic is the key factor that restricts the further development of photovoltaic industry,in order to find and output the maximum power of PV array under various environmental conditions,the photovoltaic array is studied from the following aspects:The output characteristics of photovoltaic cells are strongly nonlinear,I set up the mathematic models of the PV array under both uniform illumination and local shading conditions by reading a large number of references.The output characteristics and the number of power extreme points under local shadow conditions are studied in this paper,which laid the foundation for the research of follow-up maximum power tracking method.Under the condition of uniform illumination,the traditional fixed step-size algorithm must take a compromise between the steady-state accuracy and the response speed in the selection of step.As the incremental conductance method has its own defects,there may be a misjudgment when the external conditions change drastically.A new variable step-size method based on power prediction is proposed,this method solves the contradiction between tracking speed and steady-state precision.When the illumination changes drastically,the algorithm ensures that the judgments before and after the disturbance are carried out on the same power curve to avoid the occurrence of misjudgment.Under partial shading conditions,two global maximum power point tracking methods are proposed in this paper.The first method is a new global MPPT algorithm based on sampled data preprocessing,and this algorithm is suitable for most shading situations.The basic idea is to pre-process the output characteristic curve of the PV array,gradually narrow the range of the interval where the maximum power point is located,and then convert the multi-peak optimization problem into the single-peak optimization problem;The second method is to apply an improved intelligent algorithm to the MPPT of photovoltaic array,the algorithm combines the mutation strategy in the differential evolution algorithm with the artificial bee colony algorithm to realize the global maximum power point tracking control under time-varying conditions,and efficient iteration stop strategy is proposed which could reduce the power oscillation when trending to steady state.The model of PV system is built in Matlab/Simulink,and the model is based on the S-Function module of the proposed algorithms.The simulation results show that the proposed algorithm has excellent dynamic and steady-state performance under uniform illumination conditions and can effectively avoid the misjudgment phenomenon caused by environmental mutation;Under the partial shading condition,the two proposed algorithms can find the global maximum power point effectively in the condition of both no shading and partial shading conditions,and can effectively prevent the PV array output power from oscillating at the MPP and improve the output efficiency of the photovoltaic cell.