Solar power forecasts

Spatio-temporal solar power forecasts via regression

Master Thesis (2022)
Author(s)

N. Jaspers (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

R.A. Verzijlbergh – Mentor (TU Delft - Energy and Industry)

SR de Roode – Mentor (TU Delft - Atmospheric Remote Sensing)

Z Lukszo – Mentor (TU Delft - Energy and Industry)

Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright
© 2022 Noud Jaspers
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 Noud Jaspers
Graduation Date
18-08-2022
Awarding Institution
Delft University of Technology
Programme
['Electrical Engineering | Sustainable Energy Technology']
Faculty
Electrical Engineering, Mathematics and Computer Science
Reuse Rights

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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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