Solar power forecasts

Jaspers, N.

Solar power forecasts

Spatio-temporal solar power forecasts via regression

Master thesis (2022)

Authors

N. Jaspers Electrical Engineering, Mathematics and Computer Science

Contributors

Remco Verzijlbergh Energy and Industry (mentor)

Stefan R. de Roode Atmospheric Remote Sensing (mentor)

Z. Lukszo Energy and Industry (mentor)

Faculty

Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science

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Published Date

18-08-2022

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

We aim to make solar power forecasts using regression for grid optimization. We forecast from 1 to 6 hours ahead. The forecasts prove to be accurate with a skill score of 20% compared to persistence for a lead time of one hour.

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