The wave energy converter control competition (WECCCOMP): Wave energy control algorithms compared in both simulation and tank testing

Ringwood, John V.; Tom, Nathan; Ferri, Francesco; Yu, Yi Hsiang; Coe, Ryan G.; Ruehl, Kelley; Bacelli, Giorgio; Shi, Shuo; Patton, Ron J.; Tona, Paolino; Sabiron, Guillaume; Merigaud, Alexis; Ling, Bradley A.; Faedo, Nicolas

Abstract

The wave energy control competition established a benchmark problem which was offered as an open challenge to the wave energy system control community. The competition had two stages: In the first stage, competitors used a standard wave energy simulation platform (WEC-Sim) to evaluate their controllers while, in the second stage, competitors were invited to test their controllers in a real-time implementation on a prototype system in a wave tank. The performance function used was based on converted energy across a range of standard sea states, but also included aspects related to economic performance, such as peak/average power, peak force, etc. This paper compares simulated and experimental results and, in particular, examines if the results obtained in a linear system simulation are borne out in reality. Overall, within the scope of the device tested, the range of sea states employed, and the performance metric used, the conclusion is that high-performance WEC controllers work well in practice, with good carry-over from simulation to experimentation. However, the availability of a good WEC mathematical model is deemed to be crucial.

Citation

Ringwood, J. V., Tom, N., Ferri, F., Yu, Y. H., Coe, R. G., Ruehl, K., …Faedo, N. (2023). The wave energy converter control competition (WECCCOMP): Wave energy control algorithms compared in both simulation and tank testing. Applied Ocean Research, 138, Article 103653. https://doi.org/10.1016/j.apor.2023.103653

• Journal Article Type: Article
• Acceptance Date: Jun 27, 2023
• Online Publication Date: Jul 20, 2023
• Publication Date: Sep 1, 2023
• Deposit Date: Jul 31, 2023
• Publicly Available Date: Aug 2, 2023
• Journal: Applied Ocean Research
• Print ISSN: 0141-1187
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 138
• Article Number: 103653
• DOI: https://doi.org/10.1016/j.apor.2023.103653
• Keywords: Wave energy; Modelling; Control; Estimation; Forecasting; Competition
• Public URL: https://hull-repository.worktribe.com/output/4347232