Cloud detection method using ground-based sky images based on clear sky library and superpixel local threshold

Yinsen Niu, Jifeng Song, Lianglin Zou, Zixuan Yan and Xilong Lin

Renewable Energy, 2024, vol. 226, issue C

Abstract: In the intra-hour time scale, shielding of solar radiation by clouds is the main reason for the fluctuation of photovoltaic, so cloud parameters are important for intra-hour solar irradiance and photovoltaic power forecasting. Extracting cloud regions from cloud images provides a basis for quantifying cloud size and shape. It is difficult to detect clouds in these three cases, such as clouds in circumsolar region, clouds in haze weather and thin clouds at cloud edge. Aiming at such problems, this study firstly establishes a clear sky library based on pixel-level sun positions and haze conditions to deal with the complex changes of sky brightness. Then this study proposes a cloud detection method for ground-based images, which performs two segmentations on the cloud image. The initial segmentation process is a combination method that uses clear sky library method when the sun is visible and uses adaptive threshold method when the sun is occluded. The secondary segmentation process is based on superpixels and local threshold method, which restores some thin clouds that are easily ignored. Finally, for the influence of ghosts, this study summarizes the position and color features of ghosts, and uses different color channel information to deal with them.

Keywords: Photovoltaic power forecasting; Ground-based cloud image; Clear sky library method; Superpixel; Local threshold method; Image segmentation (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:226:y:2024:i:c:s0960148124005172

DOI: 10.1016/j.renene.2024.120452

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