Photovoltaic Module Regional Clustering In China Mainland And Application Based On Factors Influencing Field Reliability

The field reliability of photovoltaic(PV)modules is important for the investment,design,operation and maintenance of PV power generation projects.Because the laboratory test conditions cannot reappear the performance degradation influencing factors(i.e.the field reliability influencing factors)of PV modules in service environment,the experimental results cannot be applied to the field reliability assessment and prediction.There are objective and accurate assessment and prediction results of field reliability are obtained by performance degradation data obtained from long-term observation of the service environment.However,the complexity and diversity service environments bring the significant regional differences of field reliability,which leads to the limitation of the applicable regional scope of the evaluation conclusions obtained from the observation test of PV modules in a specific region.In view of the above problems,this paper studies the field reliability influencing factors,regional clustering based on factors affecting field reliability,and influencing factors and service lifetime prediction based on regional clustering results.Specific tasks are as follows:(1)The factors affecting the field reliability of PV modules are analyzed qualitatively and quantitatively from two dimensions of workload and natural wearing.The factors affecting the field reliability of PV modules,including temperature,humidity,sunshine,precipitation,wind speed,dust,latitude,altitude and cloud cover are identified systematically and accurately from two dimensions of workload and natural wearing.The clustering indexes of the 31 provincial administrative divisions in Mainland China are derived from the average of the corresponding indexes of all the prefecture-level administrative divisions,which consider the influence of all prefecture-level administrative divisions on the measurement accuracy of clustering indexes.(2)A comprehensive clustering framework model based on workload factors and natural wearing factors is constructed.The regional clustering model is constructed by the method of decomposition and synthesis,considering comprehensively the influence of workload factors and natural wearing factors on the field reliability of PV modules,which can effectively avoid the one-sidedness of a single clustering index and reduce the difficulty of clustering.The absolute weighted distance,increment weighted distance,undulation weighted distance and weighted Ward clustering algorithm are involved in model clustering which take into account the influence of the time weight and index weight of the panel data,so the more accurate regional clustering results can be obtain by the model.(3)The models of influence degree analysis of factors and service lifetime prediction based on clustering results are constructed.The frame model can accurately obtain different clustering results under the influence of factors.Dunn index is used to measure the difference of clustering effect of the corresponding clustering results,and the influence of a single factor on the final clustering results could be determined according to the measurement results.The relationship model between the field reliability difference and the distance among the clustering regions is constructed based on the regional clustering results,which can be used to predict the field reliability in other clustering regions based on the field reliability in one clustering region.The service lifetime of PV modules can be calculated according to the predicted results of field reliability and the failure threshold.The research results show that the method proposed in this paper can accurately realize the geographical region classification of the field reliability of PV modules and realize the service lifetime prediction of PV modules in different geographical regions,and can effectively improve the value of the existing field reliability conclusions of PV modules.The research results can provide reference for similar research on wind power equipment,solar water heater and solar street lamp.