Future projections of offshore wind energy resources in China using CMIP6 simulations and a deep learning-based downscaling method
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DOI: 10.1016/j.energy.2020.119321
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- Martinez, A. & Murphy, L. & Iglesias, G., 2023. "Evolution of offshore wind resources in Northern Europe under climate change," Energy, Elsevier, vol. 269(C).
- Liu, Y. & Li, Y.P. & Huang, G.H. & Lv, J. & Zhai, X.B. & Li, Y.F. & Zhou, B.Y., 2023. "Development of an integrated model on the basis of GCMs-RF-FA for predicting wind energy resources under climate change impact: A case study of Jing-Jin-Ji region in China," Renewable Energy, Elsevier, vol. 219(P2).
- 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).
- Jaime Meza-Carreto & Rosario Romero-Centeno & Bernardo Figueroa-Espinoza & Efraín Moreles & Carlos López-Villalobos, 2024. "Outlook for Offshore Wind Energy Development in Mexico from WRF Simulations and CMIP6 Projections," Energies, MDPI, vol. 17(8), pages 1-30, April.
- 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).
- Martinez, A. & Iglesias, G., 2024. "Global wind energy resources decline under climate change," Energy, Elsevier, vol. 288(C).
- 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).
- Liang, Yushi & Wu, Chunbing & Ji, Xiaodong & Zhang, Mulan & Li, Yiran & He, Jianjun & Qin, Zhiheng, 2022. "Estimation of the influences of spatiotemporal variations in air density on wind energy assessment in China based on deep neural network," Energy, Elsevier, vol. 239(PC).
- Guo, Junhong & Chen, Zhuo & Meng, Jing & Zheng, Heran & Fan, Yuri & Ji, Ling & Wang, Xiuquan & Liang, Xi, 2024. "Picturing China's photovoltaic energy future: Insights from CMIP6 climate projections," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
- Yang, Weixin & Yang, Yunpeng & Chen, Hongmin, 2022. "How to stimulate Chinese energy companies to comply with emission regulations? Evidence from four-party evolutionary game analysis," Energy, Elsevier, vol. 258(C).
- Ashok Bhansali & Namala Narasimhulu & Rocío Pérez de Prado & Parameshachari Bidare Divakarachari & Dayanand Lal Narayan, 2023. "A Review on Sustainable Energy Sources Using Machine Learning and Deep Learning Models," Energies, MDPI, vol. 16(17), pages 1-18, August.
- deCastro, M. & Rusu, L. & Arguilé-Pérez, B. & Ribeiro, A. & Costoya, X. & Carvalho, D. & Gómez-Gesteira, M., 2024. "Different approaches to analyze the impact of future climate change on the exploitation of wave energy," Renewable Energy, Elsevier, vol. 220(C).
- Miao, Haozeyu & Xu, Haiming & Huang, Gang & Yang, Kai, 2023. "Evaluation and future projections of wind energy resources over the Northern Hemisphere in CMIP5 and CMIP6 models," Renewable Energy, Elsevier, vol. 211(C), pages 809-821.
- Costoya, X. & deCastro, M. & Carvalho, D. & Gómez-Gesteira, M., 2023. "Assessing the complementarity of future hybrid wind and solar photovoltaic energy resources for North America," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
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Keywords
Deep learning; Bidirectional gated recurrent unit; Downscaling; Climate change; Coupled model intercomparison project phase 6; Offshore wind energy;All these keywords.
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