Reserch On Max Power Point Tracking And Online Diagnosis Method For Photovoltaic Array Under Partial Shading Condition

Solar energy is one of the representatives of clean energy and new energy,in the fossil energy supply situation is tight and cause more serious pollution of the moment,more and more people's attention.Photovoltaic power generation is the main way for people to use solar energy,and photovoltaic cells in the actual operation of the process prone to shadow block,aging,corrosion,cracks,hot spots and other phenomena,making the output characteristics of photovoltaic arrays have changed dramatically,the traditional maximum power Point tracking method is almost ineffective,photovoltaic power generation system stability and security are also facing severe challenges.Since the influence of almost all PV array faults on the PV array can be approximated by local shadow occlusion,the output characteristics of the photovoltaic array under local shadow masking are studied and the maximum power point tracking method for the shadow occlusion situation and the photovoltaic array.The online diagnostic method of shadow occlusion is imminent.In order to solve the problem of the influence of natural factors on the photovoltaic array,this paper proposes a method to describe the influence of the two factors on the output characteristics of the PV array by descriptive statistics method.The influence of the two factors on the output characteristics of the PV array is described by the statistical method.Law to explain.In order to ensure the authority of the data and to meet the high demand of the statistical method for the data range and accuracy,the simulation model is built on the reference model of the photovoltaic array model database of the US Renewable Energy Laboratory(NREL).Through the illumination,Temperature univariate analysis and the comprehensive analysis of the two factors,respectively,summed up the PV array in different light intensity,temperature distribution of the output characteristics of the law.Based on the conclusion of the statistical analysis of photovoltaic arrays,an adaptive variable step-size perturbation observation method based on statistical information is proposed as a max power point tracking method in this paper.The method of perturbation observation is the basis of the search strategy,which avoids the disadvantage of the traditional global search algorithm in coping with the dynamic optimization problem and designs a variable step mechanism to deal with the traditional disturbance observation.The appropriate tracking variables are selected and the search range is optimized accordingly.A voltage reverse searching mechanism is designed to avoid the traditional disturbance observation In this way,the method establishes a set of variable initial adaptive mechanism to ensure the fastness of the algorithm.Finally,this paper verifies the effectiveness of the method by simulation.In this paper,the problem of online diagnosis of PV array shadow occlusion is discussed.After considering the problem of incomplete data and poor data accuracy,the advantages and disadvantages of various diagnostic methods of PV array are discussed.Based on power tracking Data of the PV array shaded occlusion of the online diagnostic method.This method realizes the raw data in real time by the adaptive variable step perturbation observation method based on statistical information,which combines the online diagnosis method with the maximum power point tracking method,saving the system cost,and the dimension of the data for the diagnosis.The number of sub-arrays is increased and the feature extraction and dimension reduction methods based on principal component analysis are proposed,which reduces the amount of data.For the widely used artificial neural network,the training time is long.Support vector machine is used as the diagnosis algorithm to improve the adaptability and fastness of the diagnosis method for high dimensional data.Finally,this paper verifies the validity and superiority of the method by simulation.