What is it about?

This work is focused on the domain of short-term and ultra-short term solar power forecasting. Aiming to comprehend the different factors affecting the outcome of the prediction process, the review has focused on the effect of the different climatic conditions and the geographical location of the reviewed datasets as well as the technical characteristics of the forecasting models.

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Why is it important?

This paper evaluated novel state-of-the-art ultra-short-term and short-term solar power forecasting models. It further classified the reviewed works from a climatic point of view. Classifications based on the input data and technical characteristics were also provided. Evading to focus specifically on the different forecasting methodologies, this review is a useful guide that provides information over the effect of the different climatic conditions to the forecasting accuracy. Further comparison of similar cases in terms of input variables or technical data offers the possibility to evaluate the efficiency of each forecasting model and indicates the main limitations and directions for further development.

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This page is a summary of: A taxonomy of short‐term solar power forecasting: Classifications focused on climatic conditions and input data, IET Renewable Power Generation, May 2023, the Institution of Engineering and Technology (the IET), DOI: 10.1049/rpg2.12736.
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