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Assessment of future wind resources under climate change using a multi-model and multi-method ensemble approach

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  • He, J.Y.
  • Li, Q.S.
  • Chan, P.W.
  • Zhao, X.D.

Abstract

Harvesting renewable wind energy is among the most cost-efficient means of reducing carbon emissions and achieving carbon neutrality. However, wind resource is susceptible to climate change impacts since the global temperature increase will reshape atmospheric circulation patterns. To facilitate the evaluation of fine-scale wind energy potential under climate variability, this paper proposes and validates a multi-model and multi-method ensemble wind resource projection approach. Then this approach is utilized to investigate the future variation of wind resources in Hong Kong based on the combined use of global climate models from Coupled Model Intercomparison Project Phase 6 and long-term observations from meteorological stations. It is found that there is a significant increase in future wind resources during summer, while a remarkable decline is projected during autumn. Nevertheless, the variations of wind resources in winter and spring are relatively insignificant. The outcomes of this study are expected to offer a framework for fine-scale wind resource assessment under climate change, and facilitate the economic and risk assessments of future wind farm projects.

Suggested Citation

  • He, J.Y. & Li, Q.S. & Chan, P.W. & Zhao, X.D., 2023. "Assessment of future wind resources under climate change using a multi-model and multi-method ensemble approach," Applied Energy, Elsevier, vol. 329(C).
  • Handle: RePEc:eee:appene:v:329:y:2023:i:c:s0306261922015471
    DOI: 10.1016/j.apenergy.2022.120290
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    1. Costoya, X. & deCastro, M. & Carvalho, D. & Gómez-Gesteira, M., 2020. "On the suitability of offshore wind energy resource in the United States of America for the 21st century," Applied Energy, Elsevier, vol. 262(C).
    2. Wimhurst, Joshua J. & Greene, J. Scott, 2019. "Oklahoma's future wind energy resources and their relationship with the Central Plains low-level jet," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    3. Gao, Xiaoxia & Yang, Hongxing & Lu, Lin, 2014. "Study on offshore wind power potential and wind farm optimization in Hong Kong," Applied Energy, Elsevier, vol. 130(C), pages 519-531.
    4. 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).
    5. David E. H. J. Gernaat & Harmen Sytze Boer & Vassilis Daioglou & Seleshi G. Yalew & Christoph Müller & Detlef P. Vuuren, 2021. "Climate change impacts on renewable energy supply," Nature Climate Change, Nature, vol. 11(2), pages 119-125, February.
    6. 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.
    7. Lu, Lin & Yang, Hongxing & Burnett, John, 2002. "Investigation on wind power potential on Hong Kong islands—an analysis of wind power and wind turbine characteristics," Renewable Energy, Elsevier, vol. 27(1), pages 1-12.
    8. S. Pryor & R. Barthelmie, 2013. "Assessing the vulnerability of wind energy to climate change and extreme events," Climatic Change, Springer, vol. 121(1), pages 79-91, November.
    9. David E. H. J. Gernaat & Harmen Sytze Boer & Vassilis Daioglou & Seleshi G. Yalew & Christoph Müller & Detlef P. Vuuren, 2021. "Author Correction: Climate change impacts on renewable energy supply," Nature Climate Change, Nature, vol. 11(4), pages 362-362, April.
    10. 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.
    11. Martin, Sean & Jung, Sungmoon & Vanli, Arda, 2020. "Impact of near-future turbine technology on the wind power potential of low wind regions," Applied Energy, Elsevier, vol. 272(C).
    12. Liu, Fa & Sun, Fubao & Liu, Wenbin & Wang, Tingting & Wang, Hong & Wang, Xunming & Lim, Wee Ho, 2019. "On wind speed pattern and energy potential in China," Applied Energy, Elsevier, vol. 236(C), pages 867-876.
    13. Chang, Tian Pau, 2011. "Performance comparison of six numerical methods in estimating Weibull parameters for wind energy application," Applied Energy, Elsevier, vol. 88(1), pages 272-282, January.
    14. 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).
    15. Matthias Themeßl & Andreas Gobiet & Georg Heinrich, 2012. "Empirical-statistical downscaling and error correction of regional climate models and its impact on the climate change signal," Climatic Change, Springer, vol. 112(2), pages 449-468, May.
    16. Li, Yi & Wu, Xiao-Peng & Li, Qiu-Sheng & Tee, Kong Fah, 2018. "Assessment of onshore wind energy potential under different geographical climate conditions in China," Energy, Elsevier, vol. 152(C), pages 498-511.
    17. Liu, Yichao & Chen, Daoyi & Li, Sunwei & Chan, P.W., 2018. "Discerning the spatial variations in offshore wind resources along the coast of China via dynamic downscaling," Energy, Elsevier, vol. 160(C), pages 582-596.
    18. Li, Jiale & Wang, Xuefei & Yu, Xiong (Bill), 2018. "Use of spatio-temporal calibrated wind shear model to improve accuracy of wind resource assessment," Applied Energy, Elsevier, vol. 213(C), pages 469-485.
    19. Crippa, Paola & Alifa, Mariana & Bolster, Diogo & Genton, Marc G. & Castruccio, Stefano, 2021. "A temporal model for vertical extrapolation of wind speed and wind energy assessment," Applied Energy, Elsevier, vol. 301(C).
    20. Solaun, Kepa & Cerdá, Emilio, 2020. "Impacts of climate change on wind energy power – Four wind farms in Spain," Renewable Energy, Elsevier, vol. 145(C), pages 1306-1316.
    21. Shu, Z.R. & Li, Q.S. & Chan, P.W., 2015. "Investigation of offshore wind energy potential in Hong Kong based on Weibull distribution function," Applied Energy, Elsevier, vol. 156(C), pages 362-373.
    22. 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).
    23. Lun, Isaac Y.F & Lam, Joseph C, 2000. "A study of Weibull parameters using long-term wind observations," Renewable Energy, Elsevier, vol. 20(2), pages 145-153.
    24. He, J.Y. & Chan, P.W. & Li, Q.S. & Lee, C.W., 2022. "Characterizing coastal wind energy resources based on sodar and microwave radiometer observations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    25. Jung, Christopher & Schindler, Dirk, 2019. "Wind speed distribution selection – A review of recent development and progress," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    26. Santos, F. & Gómez-Gesteira, M. & deCastro, M. & Añel, J.A. & Carvalho, D. & Costoya, Xurxo & Dias, J.M., 2018. "On the accuracy of CORDEX RCMs to project future winds over the Iberian Peninsula and surrounding ocean," Applied Energy, Elsevier, vol. 228(C), pages 289-300.
    27. Douglas Maraun & Theodore G. Shepherd & Martin Widmann & Giuseppe Zappa & Daniel Walton & José M. Gutiérrez & Stefan Hagemann & Ingo Richter & Pedro M. M. Soares & Alex Hall & Linda O. Mearns, 2017. "Towards process-informed bias correction of climate change simulations," Nature Climate Change, Nature, vol. 7(11), pages 764-773, November.
    28. Xiaoxia Gao & Lu Xia & Lin Lu & Yonghua Li, 2019. "Analysis of Hong Kong’s Wind Energy: Power Potential, Development Constraints, and Experiences from Other Countries for Local Wind Energy Promotion Strategies," Sustainability, MDPI, vol. 11(3), pages 1-20, February.
    29. Gualtieri, Giovanni, 2019. "A comprehensive review on wind resource extrapolation models applied in wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 102(C), pages 215-233.
    30. Soares, Pedro M.M. & Lima, Daniela C.A. & Cardoso, Rita M. & Nascimento, Manuel L. & Semedo, Alvaro, 2017. "Western Iberian offshore wind resources: More or less in a global warming climate?," Applied Energy, Elsevier, vol. 203(C), pages 72-90.
    31. Chang, Tian Pau, 2011. "Estimation of wind energy potential using different probability density functions," Applied Energy, Elsevier, vol. 88(5), pages 1848-1856, May.
    32. Fant, Charles & Adam Schlosser, C. & Strzepek, Kenneth, 2016. "The impact of climate change on wind and solar resources in southern Africa," Applied Energy, Elsevier, vol. 161(C), pages 556-564.
    33. Lira-Loarca, Andrea & Ferrari, Francesco & Mazzino, Andrea & Besio, Giovanni, 2021. "Future wind and wave energy resources and exploitability in the Mediterranean Sea by 2100," Applied Energy, Elsevier, vol. 302(C).
    34. He, Junyi & Chan, P.W. & Li, Qiusheng & Lee, C.W., 2020. "Spatiotemporal analysis of offshore wind field characteristics and energy potential in Hong Kong," Energy, Elsevier, vol. 201(C).
    35. Shu, Z.R. & Li, Q.S. & He, Y.C. & Chan, P.W., 2016. "Observations of offshore wind characteristics by Doppler-LiDAR for wind energy applications," Applied Energy, Elsevier, vol. 169(C), pages 150-163.
    36. Johnson, Dana L. & Erhardt, Robert J., 2016. "Projected impacts of climate change on wind energy density in the United States," Renewable Energy, Elsevier, vol. 85(C), pages 66-73.
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    Cited by:

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    2. Liu, Zhiyuan & Li, Yan & Sun, Yong & Feng, Fang & Tagawa, Kotaro, 2023. "Preparation of biochar-based photothermal superhydrophobic coating based on corn straw biogas residue and blade anti-icing performance by wind tunnel test," Renewable Energy, Elsevier, vol. 210(C), pages 618-626.

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