Solar photovoltaic (PV) generation, a keystone of renewable energy, has gained worldwide recognition and application. Conventional methods based on experience and observational data struggle to determine the specific impact of meteorological factors on daily solar PV energy generation. In this paper, the quantitative meteorological factors combined with the Pearson coefficient significance test method and multiple regression analysis model are used to analyze the impact of meteorological factors on the daily energy generation of solar photovoltaic. By using the photovoltaic power generation data collected by Shen6 gas collection station of Shenmu Second Gas Production Plant in Shenmu County, Yulin City, Shaanxi Province in 2022, combined with multiple meteorological factors such as daily maximum temperature, minimum temperature, average temperature, precipitation and weather conditions, the correlation analysis of photovoltaic daily power generation was carried out. The maximum temperature, minimum temperature and average temperature showed a moderate positive correlation with the daily photovoltaic power generation, while the precipitation showed a weak negative correlation with the daily photovoltaic power generation, in addition, the degree of sunny and the daily photovoltaic power generation showed a very significant positive correlation. The results of this study provide a certain reference for predicting the daily photovoltaic power generation.
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Li et al. (2024) studied this question.
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