EMS Annual Meeting Abstracts
Vol. 21, EMS2024-441, 2024, updated on 05 Jul 2024
https://doi.org/10.5194/ems2024-441
EMS Annual Meeting 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Poster | Thursday, 05 Sep, 18:00–19:30 (CEST), Display time Thursday, 05 Sep, 13:30–Friday, 06 Sep, 16:00|

CMIP6 climate projections based wave energy production analysis for Mutriku Wave Energy Plant in the XXI century

Sheila Carreno-Madinabeitia1, Paula Serras2, Gabriel Ibarra-Berastegui2,3, Jon Sáenz3,4, and Alain Ulazia5
Sheila Carreno-Madinabeitia et al.
  • 1Department of Mathematics, University of the Basque Country (UPV/EHU), Paseo de la Universidad, 01006 Vitoria-Gasteiz, Spain
  • 2Energy Engineering Department, University of the Basque Country (UPV/EHU), Alda, Urkijo, 48013 Bilbao, Spain
  • 3Plentziako Itsas Estazioa (BEGIK), University of the Basque Country (UPV/EHU), Areatza Hiribidea 47, 48620 Plentzia, Spain
  • 4Department of Physics, University of the Basque Country (UPV/EHU), Leioa, Spain
  • 5Energy Engineering Department, Gipuzkoa Faculty of Engineering (UPV/EHU), Eibar, Spain

Nowadays, the number of operational renewable energy plants is steadily increasing. It is necessary to analyse how climate change might affect their energy production.  Motivated by this need, this study analyses the Mutriku Wave Energy Plant, which has been operating since July 2011 and has a total capacity of 296 kW.

ECMWF Reanalysis v5 (ERA5) data and Commonwealth Scientific and Industrial Research Organisation (CSIRO) wave climate projections are used between 2015 and 2100. The projections are derived from two CMIP6 models: ACCESS-CM2 and EC-EARTH3, along with their respective parameterizations CDFAC1.08 and CDFAC1. Specifically, we employ six different climate projections, two based on the low-emission SSP1-2.6 scenario and four based on the higher-emission SSP5-8.5 scenario.

Bias correction for vector-valued variables are performed using the multivariate bias technique based on the MBC N-pdf bivariate pdf, while for univariate variables; the classical Quantile Mapping (QM) technique is applied. Additionally, the self-organising map, SOM, technique is also used to classify the daily frequencies and powers of sea type. Finally, the Smirnov test is employed to assess if the shapes of the probability distributions from the different datasets differed statistically. A significance level of 0.05 is used.

Our results show that wave energy production in the Bay of Biscay remains stable in the 21st century. This stability is reflected in a significantly way in the analysis of sea type frequencies and in the energy production. This consistent wave scenario ensures reliable and predictable energy generation, making the Bay of Biscay a valuable source of renewable energy both now and in the future.

How to cite: Carreno-Madinabeitia, S., Serras, P., Ibarra-Berastegui, G., Sáenz, J., and Ulazia, A.: CMIP6 climate projections based wave energy production analysis for Mutriku Wave Energy Plant in the XXI century, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-441, https://doi.org/10.5194/ems2024-441, 2024.