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Copula-based projections of wind power: Ireland as a case study

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  • Moradian, Sogol
  • Olbert, Agnieszka I.
  • Gharbia, Salem
  • Iglesias, Gregorio

Abstract

Wind energy is a key element in the ongoing push to decarbonize the energy supply. The first step in the development of a wind farm at a specific site is to conduct feasibility studies including accurate long-term wind potential assessments and estimates of the annual energy production. However, as evidence of climate change becomes more apparent recently, concerns about the planning and utilization of wind resources in the face of these new conditions have increased. Accurate projections are needed to determine the frequency distribution of wind speeds in an area and, on this basis, estimate the energy production. The purpose of this study is to analyze the wind resource, to estimate its potential and to prepare zoning maps of wind energy production to determine the most suitable sites for wind farms in Ireland. For this purpose, wind data from ten Global Circulation Models and different climate-change scenarios were used during the historical and future period of 1981–2010 and 2021–2050, respectively. These data were evaluated in the study area and then a multi-criteria decision-making method was applied to choose the best representative climate models over the area. In order to post-process the outputs of the selected models, 17 statistical distributions and 26 Copula families were applied. Results showed that the average wind speed in the region during the historical period is expected to decrease in 2021–2050 by approximately 2–7% based on the climate scenarios. Additionally, wind power density maps were produced for the study area.

Suggested Citation

  • Moradian, Sogol & Olbert, Agnieszka I. & Gharbia, Salem & Iglesias, Gregorio, 2023. "Copula-based projections of wind power: Ireland as a case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 175(C).
  • Handle: RePEc:eee:rensus:v:175:y:2023:i:c:s1364032123000035
    DOI: 10.1016/j.rser.2023.113147
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    References listed on IDEAS

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    1. James W. K. Nash & Iasonas Zekos & Margaret M. Stack, 2021. "Mapping of Meteorological Observations over the Island of Ireland to Enhance the Understanding and Prediction of Rain Erosion in Wind Turbine Blades," Energies, MDPI, vol. 14(15), pages 1-34, July.
    2. Martinez, A. & Iglesias, G., 2022. "Mapping of the levelised cost of energy for floating offshore wind in the European Atlantic," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    3. Foley, A.M. & Ó Gallachóir, B.P. & McKeogh, E.J. & Milborrow, D. & Leahy, P.G., 2013. "Addressing the technical and market challenges to high wind power integration in Ireland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 692-703.
    4. Zhao, Xinyu & Bai, Mingliang & Yang, Xusheng & Liu, Jinfu & Yu, Daren & Chang, Juntao, 2021. "Short-term probabilistic predictions of wind multi-parameter based on one-dimensional convolutional neural network with attention mechanism and multivariate copula distribution estimation," Energy, Elsevier, vol. 234(C).
    5. Han, Shuang & Qiao, Yan-hui & Yan, Jie & Liu, Yong-qian & Li, Li & Wang, Zheng, 2019. "Mid-to-long term wind and photovoltaic power generation prediction based on copula function and long short term memory network," Applied Energy, Elsevier, vol. 239(C), pages 181-191.
    6. Hdidouan, Daniel & Staffell, Iain, 2017. "The impact of climate change on the levelised cost of wind energy," Renewable Energy, Elsevier, vol. 101(C), pages 575-592.
    7. Kubik, M.L. & Brayshaw, D.J. & Coker, P.J. & Barlow, J.F., 2013. "Exploring the role of reanalysis data in simulating regional wind generation variability over Northern Ireland," Renewable Energy, Elsevier, vol. 57(C), pages 558-561.
    8. Roch, Oriol & Alegre, Antonio, 2006. "Testing the bivariate distribution of daily equity returns using copulas. An application to the Spanish stock market," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1312-1329, November.
    9. Boškoski, Pavle & Debenjak, Andrej & Mileva Boshkoska, Biljana, 2018. "Rayleigh copula for describing impedance data—with application to condition monitoring of proton exchange membrane fuel cells," European Journal of Operational Research, Elsevier, vol. 266(1), pages 269-277.
    10. Majidi Nezhad, M. & Groppi, D. & Marzialetti, P. & Fusilli, L. & Laneve, G. & Cumo, F. & Garcia, D. Astiaso, 2019. "Wind energy potential analysis using Sentinel-1 satellite: A review and a case study on Mediterranean islands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 499-513.
    11. Ali, Mir M. & Mikhail, N. N. & Haq, M. Safiul, 1978. "A class of bivariate distributions including the bivariate logistic," Journal of Multivariate Analysis, Elsevier, vol. 8(3), pages 405-412, September.
    12. Edward Frees & Emiliano Valdez, 1998. "Understanding Relationships Using Copulas," North American Actuarial Journal, Taylor & Francis Journals, vol. 2(1), pages 1-25.
    13. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 827-853, August.
    14. Sogol Moradian & Farhad Yazdandoost, 2021. "Seasonal meteorological drought projections over Iran using the NMME data," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 108(1), pages 1089-1107, August.
    15. Majidi Nezhad, Meysam & Neshat, Mehdi & Piras, Giuseppe & Astiaso Garcia, Davide, 2022. "Sites exploring prioritisation of offshore wind energy potential and mapping for wind farms installation: Iranian islands case studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
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