A dynamic thermal model for a photovoltaic module under varying atmospheric conditions

Abstract

Operating temperature strongly affects the performance of the photovoltaic module. Thus, the accurate estimation of the module temperature plays an important role in the assessment of photovoltaic system generation. In this article, it was shown that the existing empirical models are characterized by a limited accuracy in determining the module temperature under varying atmospheric conditions, and the estimation error exceeded 25 °C. This feature of empirical models results from the neglect of the thermal inertia of the module. To solve this problem, a dynamic thermal model for the photovoltaic module was proposed. The proposed model is based on the Finite Difference Method and only uses data on the ambient temperature, solar irradiation, and wind speed. The model coefficients were optimized using the Particle Swarm Optimization method. Developed model was benchmarked against field measurements at the Silesian University of Technology, Poland. The performance of the proposed model was also compared with the performance of the dynamic thermal model proposed by Barry et al., using measurements from systems located in the Allgäu region, Germany. The results demonstrated the effectiveness of the proposed dynamic thermal model for the correct calculation of the photovoltaic module temperature under varying weather conditions. The temperature estimation error did not exceed 9 °C.