Correlation analysis of meteorological factors on daily solar photovoltaic power generation

Min Li; Ju Cao; Liyuan Song; Chenbo Bai

doi:10.1117/12.3025101

13 May 2024 Correlation analysis of meteorological factors on daily solar photovoltaic power generation

Min Li, Ju Cao, Liyuan Song, Chenbo Bai

Author Affiliations +

Proceedings Volume 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023); 1315909 (2024) https://doi.org/10.1117/12.3025101
Event: Eighth International Conference on Energy System, Electricity and Power (ESEP 2023), 2023, Wuhan, China

Abstract

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.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Min Li, Ju Cao, Liyuan Song, and Chenbo Bai "Correlation analysis of meteorological factors on daily solar photovoltaic power generation", Proc. SPIE 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023), 1315909 (13 May 2024); https://doi.org/10.1117/12.3025101

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KEYWORDS

Photovoltaics

Meteorology

Solar energy

Linear regression

Correlation coefficients

Data modeling

Temperature metrology

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