Photovoltaic module regional clustering in mainland China and application based on factors influencing field reliability

Weidong Liu, Xiaohua Jiang, Shaoshuai Li, Ji Luo and Gen Wen

Renewable and Sustainable Energy Reviews, 2020, vol. 133, issue C

Abstract: The field reliability of photovoltaic modules is important to make investment, design, operation and maintenance decisions in PV power generation projects. By minimizing the field reliability differences between the congeneric regions of PV modules, a regional clustering method based on the factors influencing field reliability is proposed, and a model to predict the field reliability or service lifetime by the clustering results is presented. Based on systematic analysis of the regional differences between workload and natural wear factors impacting field reliability, a comprehensive clustering model is constructed, and nine clustering indexes are accurately quantified. The Ward and entropy weight methods are adopted to objectively calculate index and time weights, respectively. The weighted Ward clustering algorithm is applied to cluster regions based on workload and natural wear factors. Two clustering results are integrated through comprehensive clustering to obtain the final result. Finally, this method is applied to the clustering of 31 provincial administrative regions in mainland China, and the result is applied to predict the average annual power degradation amount of the PV modules in the different regions, both of which validate the applicability and effectiveness of the proposed method.

Keywords: Field reliability; Factors influencing reliability; Photovoltaic modules; Regional clustering; Weighted ward algorithm; Degradation predicting (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.rser.2020.110339

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