Accurate control parameter optimisation and power production assessment is essential to evaluate the performance of a wave energy converter (WEC). However, commonly used numerical models excessively simplify the power take-off (PTO) system of the WEC, which may strongly affect power production predictions. Therefore, the present paper compares a commonly used WEC model that includes nonlinear viscous losses and an ideal PTO system model, referred to as NLideal, with a high-fidelity wave-to-wire model (HFW2W) model. Results show the incapacity of the commonly used NLideal model to accurately optimise control parameters, particularly using reactive control. Likewise, the annual mean power production (AMPP) predicted using the NLideal model is significantly overestimated, with differences of up to 160% with respect to the more realistic HFW2W model. More dramatically, the use of control parameters optimised with the NLideal model in the HFW2W model results in negative AMPP, meaning that the WEC consumes more energy than it produces.
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ASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering
June 17–22, 2018
Madrid, Spain
Conference Sponsors:
- Ocean, Offshore and Arctic Engineering Division
ISBN:
978-0-7918-5131-9
PROCEEDINGS PAPER
The Impact of a High-Fidelity Wave-to-Wire Model in Control Parameter Optimisation and Power Production Assessment
Markel Penalba,
Markel Penalba
Maynooth University, Maynooth, Ireland
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John V. Ringwood
John V. Ringwood
Maynooth University, Maynooth, Ireland
Search for other works by this author on:
Markel Penalba
Maynooth University, Maynooth, Ireland
John V. Ringwood
Maynooth University, Maynooth, Ireland
Paper No:
OMAE2018-77501, V010T09A039; 10 pages
Published Online:
September 25, 2018
Citation
Penalba, M, & Ringwood, JV. "The Impact of a High-Fidelity Wave-to-Wire Model in Control Parameter Optimisation and Power Production Assessment." Proceedings of the ASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering. Volume 10: Ocean Renewable Energy. Madrid, Spain. June 17–22, 2018. V010T09A039. ASME. https://doi.org/10.1115/OMAE2018-77501
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