Global horizontal irradiance prediction model for multi-site fusion under different aerosol types

Xiu-Yan Gao, Chun-Lin Huang, Zhen-Huan Zhang, Qi-Xiang Chen, Yu Zheng, Di-Song Fu and Yuan Yuan

Renewable Energy, 2024, vol. 227, issue C

Abstract: Accurate prediction of global horizontal irradiance (GHI) is crucial for anticipating the volatility of solar power output. Under clear-sky conditions, aerosols play a significant role in influencing GHI, with different types of aerosols exhibiting distinct radiation effects. In this study, we employed the Planck mean aerosol optical depth (AOD) —Informer model to forecast future GHI, utilizing historical data of AOD, meteorological parameters, and GHI as input variables. Two data-fusion schemes were proposed, and the calculation results indicate that Scheme 1, organized in the order of Xianghe—Beijing—Shangdianzi (XBS) based on the day as a unit, demonstrates superior prediction performance. Additionally, the site information was blurred, allowing for the flexible selection of input and output lengths. The calculation results remained stable and reliable, suggesting that the inclusion of fuzzy site information does not degrade the prediction effect. Building upon this, we categorized aerosols into three types based on their time span and data volume. GHI predictions for different aerosol types revealed that the mean square error (0.145) for marine aerosols were significantly lower than those for the other types. The GHI predictions for continental aerosols were closest to the true values.

Keywords: GHI prediction; Aerosol type; Data fusion; Planck mean AOD; Informer (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:227:y:2024:i:c:s0960148124006335

DOI: 10.1016/j.renene.2024.120565

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