Wind is a renewable energy source that has become more important in recent years. Wind turbines are equipped with a SCADA system, which allows for remote supervision of the wind farm. SCADA systems are customarily used to provide data averaged every 10 minutes. Nevertheless, recent literature suggests that more insights could be extracted with a higher granularity of data. In this work, a naive methodology based on Multi-Task Gaussian Process Regression is presented, in order to show how spatiotemporal modeling benefits power estimation. Using sparsity properties a model for possible power prediction is proposed. The model proposed performs better than the power curves provided by the manufacturer.
Originele taal-2English
TitelJournal of Physics: Conference Series
Plaats van productieVisby, Sweden
UitgeverijIOP Publishing
Aantal pagina's12
StatusPublished - 22 jun 2023

Publicatie series

NaamJournal of Physics: Conference Series
ISSN van geprinte versie1742-6588

Bibliografische nota

Funding Information:
This research was funded in the context of the Energy Transition Fund project Poseidon. The authors acknowledge VLAIO/Blue Cluster Supersized 4.0 ICON project (HBC.2019.0135), ICON Rainbow project, and SEAFD project. The research was supported by the Flemish Government under the “Onderzoeksprogramma Artificiële Intelligentie (AI) Vlaanderen” program. The authors are also grateful to the VSC Supercomputing Flanders centre for the support in the context of the VSC Cloud program.

Publisher Copyright:
© Published under licence by IOP Publishing Ltd.

Copyright 2023 Elsevier B.V., All rights reserved.


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