Solar Irradiance Anticipative Transformer

Authors: Mercier, T.M., Rahman, T. and Sabet, A.

Journal: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

Volume: 2023-June

Pages: 2065-2074

eISSN: 2160-7516

ISBN: 9798350302493

ISSN: 2160-7508

DOI: 10.1109/CVPRW59228.2023.00200

Abstract:

This paper proposes an anticipative transformer-based model for short-term solar irradiance forecasting. Given a sequence of sky images, our proposed vision transformer encodes features of consecutive images, feeding into a transformer decoder to predict irradiance values associated with future unseen sky images. We show that our model effectively learns to attend only to relevant features in images in order to forecast irradiance. Moreover, the proposed anticipative transformer captures long-range dependencies between sky images to achieve a forecasting skill of 21.45 % on a 15 minute ahead prediction for a newly introduced dataset of all-sky images when compared to a smart persistence model.

https://eprints.bournemouth.ac.uk/39066/

Source: Scopus