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Using bias-correction to improve future projections of offshore wind energy resource: A case study on the Iberian Peninsula

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  • Costoya, X.
  • Rocha, A.
  • Carvalho, D.

Abstract

The reduction of the error in climate model’s meteorological variables representation is a key challenge to improve the reliability of future climate projections. It has special importance when analyzing wind power density (WPD) because this variable is proportional to the wind speed cubed. The first aim of this study is to determine whether bias correction improved WPD future projections from the Coordinated Regional Climate Downscalling project. With this purpose, two bias correction techniques have been applied over wind speed climatic projections. The first one was based on quantile mapping approach, while the second one was based on the correction in the frequency domain. It was found that the combination of bias correction techniques reduced biases both in terms of temporal variability and in the distribution of wind series. Regarding the sensitivity of WPD to bias correction techniques, it was detected that not corrected simulations tended to overestimate offshore wind energy in the area selected as case study, the Iberian Peninsula. Thus, a WPD reduction higher than 200 W m−2 at an annual scale for the end of the 21st century was observed in most of the Western Iberia coastal areas when comparing the median WPD from not corrected and corrected simulations. A WPD reduction was observed for near, mid and far future by means of corrected projections, except for the northwestern corner of the Iberian Peninsula. At seasonal scale, an increase of about 20% was projected in summer, while a WPD decrease was observed in spring and, especially in autumn (20%).

Suggested Citation

  • Costoya, X. & Rocha, A. & Carvalho, D., 2020. "Using bias-correction to improve future projections of offshore wind energy resource: A case study on the Iberian Peninsula," Applied Energy, Elsevier, vol. 262(C).
    • Handle: RePEc:eee:appene:v:262:y:2020:i:c:s030626192030074x
    DOI: 10.1016/j.apenergy.2020.114562
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    Cited by:

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    5. Carreno-Madinabeitia, Sheila & Ibarra-Berastegi, Gabriel & Sáenz, Jon & Ulazia, Alain, 2021. "Long-term changes in offshore wind power density and wind turbine capacity factor in the Iberian Peninsula (1900–2010)," Energy, Elsevier, vol. 226(C).
    6. Katopodis, Theodoros & Markantonis, Iason & Vlachogiannis, Diamando & Politi, Nadia & Sfetsos, Athanasios, 2021. "Assessing climate change impacts on wind characteristics in Greece through high resolution regional climate modelling," Renewable Energy, Elsevier, vol. 179(C), pages 427-444.
    7. André Claro & João A. Santos & David Carvalho, 2023. "Assessing the Future wind Energy Potential in Portugal Using a CMIP6 Model Ensemble and WRF High-Resolution Simulations," Energies, MDPI, vol. 16(2), pages 1-19, January.
    8. Kena Likassa Nefabas & Lennart Söder & Mengesha Mamo & Jon Olauson, 2021. "Modeling of Ethiopian Wind Power Production Using ERA5 Reanalysis Data," Energies, MDPI, vol. 14(9), pages 1-17, April.
    9. D Carvalho & S Cardoso Pereira & A Rocha, 2021. "Future surface temperatures over Europe according to CMIP6 climate projections: an analysis with original and bias-corrected data," Climatic Change, Springer, vol. 167(1), pages 1-17, July.
    10. Laura Castro-Santos & Maite deCastro & Xurxo Costoya & Almudena Filgueira-Vizoso & Isabel Lamas-Galdo & Americo Ribeiro & João M. Dias & Moncho Gómez-Gesteira, 2021. "Economic Feasibility of Floating Offshore Wind Farms Considering Near Future Wind Resources: Case Study of Iberian Coast and Bay of Biscay," IJERPH, MDPI, vol. 18(5), pages 1-16, March.
    11. He, J.Y. & Chan, P.W. & Li, Q.S. & Tong, H.W., 2023. "Mapping future offshore wind resources in the South China Sea under climate change by regional climate modeling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    12. Carvalho, D. & Rocha, A. & Costoya, X. & deCastro, M. & Gómez-Gesteira, M., 2021. "Wind energy resource over Europe under CMIP6 future climate projections: What changes from CMIP5 to CMIP6," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    13. Costoya, X. & deCastro, M. & Carvalho, D. & Arguilé-Pérez, B. & Gómez-Gesteira, M., 2022. "Combining offshore wind and solar photovoltaic energy to stabilize energy supply under climate change scenarios: A case study on the western Iberian Peninsula," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    14. Costoya, X. & deCastro, M. & Carvalho, D. & Feng, Z. & Gómez-Gesteira, M., 2021. "Climate change impacts on the future offshore wind energy resource in China," Renewable Energy, Elsevier, vol. 175(C), pages 731-747.
    15. Zhang, Shuangyi & Li, Xichen, 2021. "Future projections of offshore wind energy resources in China using CMIP6 simulations and a deep learning-based downscaling method," Energy, Elsevier, vol. 217(C).

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