Sky image-based solar irradiance prediction methodologies using artificial neural networks

Jane Oktavia Kamadinata, Tan Lit Ken and Tohru Suwa

Renewable Energy, 2019, vol. 134, issue C, 837-845

Abstract: In order to decelerate global warming, it is important to promote renewable energy technologies. Solar energy, which is one of the most promising renewable energy sources, can be converted into electricity by using photovoltaic power generation systems. Whether the photovoltaic power generation systems are connected to an electrical grid or not, predicting near-future global solar radiation is useful to balance electricity supply and demand.

Keywords: Artificial neural network; Global horizontal irradiance prediction; Sky image; Solar energy; Photovoltaic power generation (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (16)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:134:y:2019:i:c:p:837-845

DOI: 10.1016/j.renene.2018.11.056

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