Correlation feature selection and mutual information theory based quantitative research on meteorological impact factors of module temperature for solar photovoltaic systems

The module temperature is the most important parameter influencing the output power of solar photovoltaic (PV) systems, aside from solar irradiance. In this paper, we focus on the interdisciplinary research that combines the correlation analysis, mutual information (MI) and heat transfer theory, which aims to figure out the correlative relations between different meteorological impact factors (MIFs) and PV module temperature from both quality and quantitative aspects. The identification and confirmation of primary MIFs of PV module temperature are investigated as the first step of this research from the perspective of physical meaning and mathematical analysis about electrical performance and thermal characteristic of PV modules based on PV effect and heat transfer theory. Furthermore, the quantitative description of the MIFs influence on PV module temperature is mathematically formulated as several indexes using correlation-based feature selection (CFS) and MI theory to explore the specific impact degrees under four different typical weather statuses named general weather classes (GWCs). Case studies for the proposed methods were conducted using actual measurement data of a 500 kW grid-connected solar PV plant in China. The results not only verified the knowledge about the main MIFs of PV module temperatures, more importantly, but also provide the specific ratio of quantitative impact degrees of these three MIFs respectively through CFS and MI based measures under four different GWCs.This work was supported in part by the National Natural Science Foundation of China (51577067, 51277075); the Natural Science Foundation of Beijing (3162033); the Natural Science Foundation of Hebei Province (E2015502060); the Key Project of the Science and Technology Support Program of Hebei Province (12213913D); the Fundamental Research Funds for the Central Universities (2014ZD29 and 2015XS108); State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (LAPS15009, LAPS16007 and LAPS16015), the China Scholarship Council (CSC) and the Science & Technology Project of State Grid Corporation of China (SGCC)