IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v217y2023ics0960148123008959.html
   My bibliography  Save this article

Validating EURO-CORDEX climate simulations for modelling European wind power generation

Author

Listed:
  • Luzia, Graziela
  • Koivisto, Matti J.
  • Hahmann, Andrea N.

Abstract

As the energy system becomes increasingly dependent on intermittent meteorological sources, there is a need to understand better the possible consequences of a changing climate on weather variability and how it will affect wind power generation in the future. Most previous validation studies of regional climate datasets focus on the distributional properties or, in fewer cases, the variability at lower frequencies, such as interannual and seasonal. However, accurate wind variability at a high-enough resolution (e.g., hourly) is crucial for many aspects of power and energy system analyses. Using European country-level wind generation data and metrics relevant to power and energy system applications, we validate the wind speed output from seven regional climate models from the EURO-CORDEX project. We show that the EURO-CORDEX models adjusted with the Global Wind Atlas (GWA2) can simulate temporal dependencies and generation distributions with accuracy similar to or better than the ERA5 reanalysis. The spatial correlations, however, are overestimated compared to observations by most analysed models. Assuming the GWA2 scaling is also valid for the future, the projections under the RCP8.5 scenario show a slight negative trend (2026–2065) in capacity factors for most analysed European countries.

Suggested Citation

  • Luzia, Graziela & Koivisto, Matti J. & Hahmann, Andrea N., 2023. "Validating EURO-CORDEX climate simulations for modelling European wind power generation," Renewable Energy, Elsevier, vol. 217(C).
  • Handle: RePEc:eee:renene:v:217:y:2023:i:c:s0960148123008959
    DOI: 10.1016/j.renene.2023.118989
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148123008959
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2023.118989?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gruber, Katharina & Klöckl, Claude & Regner, Peter & Baumgartner, Johann & Schmidt, Johannes, 2019. "Assessing the Global Wind Atlas and local measurements for bias correction of wind power generation simulated from MERRA-2 in Brazil," Energy, Elsevier, vol. 189(C).
    2. Davy, Richard & Gnatiuk, Natalia & Pettersson, Lasse & Bobylev, Leonid, 2018. "Climate change impacts on wind energy potential in the European domain with a focus on the Black Sea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 1652-1659.
    3. González-Aparicio, I. & Monforti, F. & Volker, P. & Zucker, A. & Careri, F. & Huld, T. & Badger, J., 2017. "Simulating European wind power generation applying statistical downscaling to reanalysis data," Applied Energy, Elsevier, vol. 199(C), pages 155-168.
    4. 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.
    5. Ravestein, P. & van der Schrier, G. & Haarsma, R. & Scheele, R. & van den Broek, M., 2018. "Vulnerability of European intermittent renewable energy supply to climate change and climate variability," Renewable and Sustainable Energy Reviews, Elsevier, vol. 97(C), pages 497-508.
    6. Schlott, Markus & Kies, Alexander & Brown, Tom & Schramm, Stefan & Greiner, Martin, 2018. "The impact of climate change on a cost-optimal highly renewable European electricity network," Applied Energy, Elsevier, vol. 230(C), pages 1645-1659.
    7. Matti Koivisto & Kaushik Das & Feng Guo & Poul Sørensen & Edgar Nuño & Nicolaos Cutululis & Petr Maule, 2019. "Using time series simulation tools for assessing the effects of variable renewable energy generation on power and energy systems," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 8(3), May.
    8. Brown, T. & Schlachtberger, D. & Kies, A. & Schramm, S. & Greiner, M., 2018. "Synergies of sector coupling and transmission reinforcement in a cost-optimised, highly renewable European energy system," Energy, Elsevier, vol. 160(C), pages 720-739.
    9. Omrani, Hiba & Drobinski, Philippe & Arsouze, Thomas & Bastin, Sophie & Lebeaupin-Brossier, Cindy & Mailler, Sylvain, 2017. "Spatial and temporal variability of wind energy resource and production over the North Western Mediterranean Sea: Sensitivity to air-sea interactions," Renewable Energy, Elsevier, vol. 101(C), pages 680-689.
    10. Murcia, Juan Pablo & Koivisto, Matti Juhani & Luzia, Graziela & Olsen, Bjarke T. & Hahmann, Andrea N. & Sørensen, Poul Ejnar & Als, Magnus, 2022. "Validation of European-scale simulated wind speed and wind generation time series," Applied Energy, Elsevier, vol. 305(C).
    11. Chen, Liang, 2020. "Impacts of climate change on wind resources over North America based on NA-CORDEX," Renewable Energy, Elsevier, vol. 153(C), pages 1428-1438.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Houndekindo, Freddy & Ouarda, Taha B.M.J., 2024. "Prediction of hourly wind speed time series at unsampled locations using machine learning," Energy, Elsevier, vol. 299(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Plaga, Leonie Sara & Bertsch, Valentin, 2023. "Methods for assessing climate uncertainty in energy system models — A systematic literature review," Applied Energy, Elsevier, vol. 331(C).
    2. Gualtieri, G., 2022. "Analysing the uncertainties of reanalysis data used for wind resource assessment: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    3. Nagababu, Garlapati & Srinivas, Bhasuru Abhinaya & Kachhwaha, Surendra Singh & Puppala, Harish & Kumar, Surisetty V.V.Arun, 2023. "Can offshore wind energy help to attain carbon neutrality amid climate change? A GIS-MCDM based analysis to unravel the facts using CORDEX-SA," Renewable Energy, Elsevier, vol. 219(P1).
    4. Kies, Alexander & Schyska, Bruno U. & Bilousova, Mariia & El Sayed, Omar & Jurasz, Jakub & Stoecker, Horst, 2021. "Critical review of renewable generation datasets and their implications for European power system models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    5. Jung, Christopher & Schindler, Dirk, 2022. "A review of recent studies on wind resource projections under climate change," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
    6. McKenna, Russell & Pfenninger, Stefan & Heinrichs, Heidi & Schmidt, Johannes & Staffell, Iain & Bauer, Christian & Gruber, Katharina & Hahmann, Andrea N. & Jansen, Malte & Klingler, Michael & Landwehr, 2022. "High-resolution large-scale onshore wind energy assessments: A review of potential definitions, methodologies and future research needs," Renewable Energy, Elsevier, vol. 182(C), pages 659-684.
    7. Murcia, Juan Pablo & Koivisto, Matti Juhani & Luzia, Graziela & Olsen, Bjarke T. & Hahmann, Andrea N. & Sørensen, Poul Ejnar & Als, Magnus, 2022. "Validation of European-scale simulated wind speed and wind generation time series," Applied Energy, Elsevier, vol. 305(C).
    8. Justė Jankevičienė & Arvydas Kanapickas, 2021. "Projected Near-Surface Wind Speed Trends in Lithuania," Energies, MDPI, vol. 14(17), pages 1-13, August.
    9. Vu Dinh, Quang & Doan, Quang-Van & Ngo-Duc, Thanh & Nguyen Dinh, Van & Dinh Duc, Nguyen, 2022. "Offshore wind resource in the context of global climate change over a tropical area," Applied Energy, Elsevier, vol. 308(C).
    10. Gallo Cassarino, Tiziano & Barrett, Mark, 2022. "Meeting UK heat demands in zero emission renewable energy systems using storage and interconnectors," Applied Energy, Elsevier, vol. 306(PB).
    11. Pflugfelder, Yannik & Kramer, Hendrik & Weber, Christoph, 2024. "A novel approach to generate bias-corrected regional wind infeed timeseries based on reanalysis data," Applied Energy, Elsevier, vol. 361(C).
    12. Markus Schlott & Omar El Sayed & Mariia Bilousova & Fabian Hofmann & Alexander Kies & Horst Stocker, 2021. "Carbon Leakage in a European Power System with Inhomogeneous Carbon Prices," Papers 2105.05669, arXiv.org.
    13. Guanying Chen & Zhenming Ji, 2024. "A Review of Solar and Wind Energy Resource Projection Based on the Earth System Model," Sustainability, MDPI, vol. 16(8), pages 1-19, April.
    14. Schyska, Bruno U. & Kies, Alexander, 2020. "How regional differences in cost of capital influence the optimal design of power systems," Applied Energy, Elsevier, vol. 262(C).
    15. Wehrle, Sebastian & Gruber, Katharina & Schmidt, Johannes, 2021. "The cost of undisturbed landscapes," Energy Policy, Elsevier, vol. 159(C).
    16. Jung, Christopher & Schindler, Dirk, 2018. "On the inter-annual variability of wind energy generation – A case study from Germany," Applied Energy, Elsevier, vol. 230(C), pages 845-854.
    17. Zhu, K. & Victoria, M. & Andresen, G.B. & Greiner, M., 2020. "Impact of climatic, technical and economic uncertainties on the optimal design of a coupled fossil-free electricity, heating and cooling system in Europe," Applied Energy, Elsevier, vol. 262(C).
    18. Chang, Miguel & Thellufsen, Jakob Zink & Zakeri, Behnam & Pickering, Bryn & Pfenninger, Stefan & Lund, Henrik & Østergaard, Poul Alberg, 2021. "Trends in tools and approaches for modelling the energy transition," Applied Energy, Elsevier, vol. 290(C).
    19. Houndekindo, Freddy & Ouarda, Taha B.M.J., 2024. "Prediction of hourly wind speed time series at unsampled locations using machine learning," Energy, Elsevier, vol. 299(C).
    20. Hansen, Kenneth & Breyer, Christian & Lund, Henrik, 2019. "Status and perspectives on 100% renewable energy systems," Energy, Elsevier, vol. 175(C), pages 471-480.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:217:y:2023:i:c:s0960148123008959. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.