Assessing the impact of wave model calibration in the uncertainty of wave energy estimation

• Type: Article in International Scientific Journal
• Date: 2023-08-01

Authors

Ajab Majidi (Author) Other; José Victor Ramos (Author) Other; K. Amarouche (Author) Other; Paulo Rosa Santos (Author) FEUP; Luciana das Neves (Author) FEUP; Francisco Taveira Pinto (Author) FEUP

Journal

Title: Renewable Energy

Vol. 212

Pages: 415-429

ISSN: 0960-1481

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 1 Citation

ISI Web of Science

Scopus - 1 Citation

Scientific classification

CORDIS: Technological sciences

FOS: Engineering and technology

Other information

Authenticus ID: P-00Y-DJZ

DOI: 10.1016/j.renene.2023.05.049

Abstract (EN): The accuracy of estimated sea conditions, specifically wave height and peak/average wave periods, affects the estimation of electrical energy production from wave energy converters. This study investigates the uncertainty in wave energy harvesting estimated by the SWAN wave model and determines possible improvements by adjusting the model's tunable parameters. Three different wave energy converters (OEBuoy, WaveBob, and Pontoon) and ten different locations along the Atlantic coast of the Iberian Peninsula are used in the study. The SWAN model is calibrated using the ST6 term package based on both wave height and peak period wave pa-rameters. Different wave hindcast data produced by different model settings are used to estimate the wave energy produced by the wave energy converters at ten buoy locations and compared to wave energy produced estimated based on wave observations. The study finds that the physical settings of the SWAN model have a considerable influence on the uncertainty in the estimation of the power output produced by the device. The best-fitting calibrated model improved the mean energy output value of all locations compared to the SWAN default settings. The study concludes that adjusting the SWAN model parameters can improve the accuracy of the estimation of the energy output.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 15