Recent advances in intra-hour solar forecasting: A review of ground-based sky image methods

Fan Lin, Yao Zhang and Jianxue Wang

International Journal of Forecasting, 2023, vol. 39, issue 1, 244-265

Abstract: As the penetration of solar energy generation into power systems keeps rising, intra-hour solar forecasting (IHSF) is becoming increasingly important for the secure and economical operation of a power system. One major difficulty in providing very accurate IHSF emanates from rapid cloud changes in the sky. The ground-based sky image (GSI) provides the intuitive information of intra-hour cloud changes and has thus been widely utilized in studies on IHSF. This paper presents a systematic review of the state-of-the-art of ground-based sky image-based intra-hour solar forecasting (GSI-IHSF). To our knowledge, we first propose a generic framework of GSI-IHSF consisting of four modules, i.e., sky image acquisition, sky image preprocessing, cloud forecasting, and solar forecasting. Then, as for each module, this paper introduces its core function, shows the major challenges, briefly reviews several extensively used techniques, summarizing research trends. Finally, this paper offers a prospect of GSI-IHSF research, discusses recent advances that demonstrate the potential for a great improvement in forecast accuracy, pointing out some new requirements and challenges that should be further investigated in the future.

Keywords: Intra-hour solar forecasting; Ramp-down forecasting; Ground-based sky image; Cloud forecasting; Computer vision; Machine learning (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:39:y:2023:i:1:p:244-265

DOI: 10.1016/j.ijforecast.2021.11.002

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