Research on optimum tilt angle of photovoltaic module based on regional clustering of influencing factors of power generation

Summary This study proposes a methodology to optimize photovoltaic (PV) module tilt angle based on regional clustering and cost evaluation. The factors that affect the power generation of PV module have significant geographical differences and coupling characteristics, and the impact of each influencing factor varies at different installation parameters. Initially, this paper performs clustering analysis on the geographical regions of mainland China to obtain 10 geographic regional classifications based on the consistency of impact degree of influencing factors. A PV module power generation prediction model is constructed by considering the influence of environmental and installation factors comprehensively and then the optimum tilt angle is further obtained. Application results in Wuhan City verifies the accuracy and validity of the proposed model with a relative root mean square error (% RMSE) and mean absolute percentage error (MAPE) of 1.9% and 1.66%, respectively. Subsequently, the model is applied to the power generation prediction of PV module in Hangzhou City. The results indicate that the optimum angle of the PV module is affected by the cleaning cycle. To investigate the relationship between the cleaning cycle and the optimum tilt angle, a novel cost evaluation model that considers the power loss and cleaning costs is proposed. Based on this proposed model, the optimum combination of cleaning cycle and tilt angle in Hangzhou City, namely, 15 days and 22°, is determined. The results are suitable for all the regions that belong to the same regional category with Hangzhou City, Zhejiang Province. The model and analysis method given in this research can provide theoretical support for determining the optimum tilt angle and cleaning cycle of PV module in different clustering regions. (1) A novel prediction model of optimum tilt angle of PV module based on regional clustering of influencing factors of power generation is constructed.(2) The above‐mentioned model reveals that the cleaning cycle will affect the optimum tilt angle.(3) A novel cost evaluation model is proposed to determine the optimum combination of tilt angle and cleaning cycle in specific regional category.