Toward defining wave prediction requirements for wave energy applications

Maximising the electrical output of wave energy converters through advanced control strategies depends significantly on the accuracy of incoming wave predictions. Various wave prediction techniques have been developed specifically for wave energy applications, typically operating under the assumption that greater accuracy leads to better performance. However, a clear understanding of how prediction errors influence controller performance remains lacking. This study explores the impact of wave prediction accuracy on energy output, aiming to define performance benchmarks for wave prediction models. Three hypothetical prediction error sources have been investigated, including the time delay, restricted frequency bandwidth in the predicted wave signal, and the prediction noise. The study was done specifically for the CETO wave energy converter and the test site located in Spain. The results indicate that to keep power losses due to wave prediction errors below 5\%, the prediction accuracy should achieve a normalised root mean square error (NRMSE) of less than 9\%.

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Publication Details

Journal
Proceedings of the ... European Wave and Tidal Energy Conference
Published
2025-09-08
DOI
https://doi.org/10.36688/ewtec-2025-946
Primary Topic
Wave and Wind Energy Systems
Type
article
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article

Toward defining wave prediction requirements for wave energy applications

Nataliia Y. Sergiienko, Mathieu Cocho
Proceedings of the ... European Wave and Tidal Energy Conference
Wave and Wind Energy Systems
article

Toward defining wave prediction requirements for wave energy applications

Nataliia Y. Sergiienko, Mathieu Cocho
article en

Abstract

Maximising the electrical output of wave energy converters through advanced control strategies depends significantly on the accuracy of incoming wave predictions. Various wave prediction techniques have been developed specifically for wave energy applications, typically operating under the assumption that greater accuracy leads to better performance. However, a clear understanding of how prediction errors influence controller performance remains lacking. This study explores the impact of wave prediction accuracy on energy output, aiming to define performance benchmarks for wave prediction models. Three hypothetical prediction error sources have been investigated, including the time delay, restricted frequency bandwidth in the predicted wave signal, and the prediction noise. The study was done specifically for the CETO wave energy converter and the test site located in Spain. The results indicate that to keep power losses due to wave prediction errors below 5\%, the prediction accuracy should achieve a normalised root mean square error (NRMSE) of less than 9\%.

Proceedings of the ... European Wave and Tidal Energy ConferenceVol. 16
Marymount University (US)
Openalex Percentile: Top 52%
Wave and Wind Energy Systems
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