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Promoting wind energy for sustainable development by precise wind speed prediction based on graph neural networks

Citations

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  1. Chen, Zhengganzhe & Zhang, Bin & Du, Chenglong & Meng, Wei & Meng, Anbo, 2024. "A novel dynamic spatio-temporal graph convolutional network for wind speed interval prediction," Energy, Elsevier, vol. 294(C).
  2. Wu, Zheng & Zhang, Yue & Dong, Ze, 2024. "NOx concentration prediction based on multi-channel fused spectral temporal graph neural network in coal-fired power plants," Energy, Elsevier, vol. 305(C).
  3. Wen-Dar Guo & Wei-Bo Chen & Chih-Hsin Chang, 2025. "A spatiotemporal watershed-scale machine-learning model for hourly and daily flood-water level prediction: the case of the tidal Beigang River, Taiwan," 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. 121(8), pages 9563-9611, May.
  4. Antonesi, Gabriel & Cioara, Tudor & Anghel, Ionut & Michalakopoulos, Vasilis & Sarmas, Elissaios & Toderean, Liana, 2025. "A systematic review of transformers and large language models in the energy sector: towards agentic digital twins," Applied Energy, Elsevier, vol. 401(PA).
  5. Zongwei Zhang & Lianlei Lin & Sheng Gao & Junkai Wang & Hanqing Zhao & Hangyi Yu, 2025. "A machine learning model for hub-height short-term wind speed prediction," Nature Communications, Nature, vol. 16(1), pages 1-18, December.
  6. Aisha Blfgeh & Hanadi Alkhudhayr, 2024. "A Machine Learning-Based Sustainable Energy Management of Wind Farms Using Bayesian Recurrent Neural Network," Sustainability, MDPI, vol. 16(19), pages 1-21, September.
  7. Ashkan Safari & Hamed Kheirandish Gharehbagh & Morteza Nazari Heris, 2023. "DeepVELOX: INVELOX Wind Turbine Intelligent Power Forecasting Using Hybrid GWO–GBR Algorithm," Energies, MDPI, vol. 16(19), pages 1-22, September.
  8. Wu, Tangjie & Ling, Qiang, 2024. "Self-supervised dynamic stochastic graph network for spatio-temporal wind speed forecasting," Energy, Elsevier, vol. 304(C).
  9. Chen, Xin & Ye, Xiaoling & Shi, Jian & Zhang, Yingchao & Xiong, Xiong, 2024. "A spatial transfer-based hybrid model for wind speed forecasting," Energy, Elsevier, vol. 313(C).
  10. Yang, Mao & Han, Chao & Zhang, Wei & Wang, Bo, 2024. "A short-term power prediction method for wind farm cluster based on the fusion of multi-source spatiotemporal feature information," Energy, Elsevier, vol. 294(C).
  11. Boudy Bilal & Kaan Yetilmezsoy & Mohammed Ouassaid, 2024. "Benchmarking of Various Flexible Soft-Computing Strategies for the Accurate Estimation of Wind Turbine Output Power," Energies, MDPI, vol. 17(3), pages 1-36, February.
  12. Leng, Zhiyuan & Chen, Lu & Yi, Bin & Liu, Fanqian & Xie, Tao & Mei, Ziyi, 2025. "Short-term wind speed forecasting based on a novel KANInformer model and improved dual decomposition," Energy, Elsevier, vol. 322(C).
  13. Ma, Long & Huang, Ling & Shi, Huifeng, 2023. "Multi-node wind speed forecasting based on a novel dynamic spatial–temporal graph network," Energy, Elsevier, vol. 285(C).
  14. Zhao, Geya & Xue, Minggao & Cheng, Li, 2023. "A new hybrid model for multi-step WTI futures price forecasting based on self-attention mechanism and spatial–temporal graph neural network," Resources Policy, Elsevier, vol. 85(PB).
  15. Wang, Li & Gao, Jinhan & Li, Yunchao & Wang, Da, 2025. "A method for ultra-short-term wind power forecasting of large-scale wind farms based on adaptive spatiotemporal graph convolution," Renewable Energy, Elsevier, vol. 249(C).
  16. Wang, Chao & Lin, Hong & Yang, Ming & Fu, Xiaoling & Yuan, Yue & Wang, Zewei, 2024. "A novel chaotic time series wind power point and interval prediction method based on data denoising strategy and improved coati optimization algorithm," Chaos, Solitons & Fractals, Elsevier, vol. 187(C).
  17. Qingquan Lv & Jialin Zhang & Jianmei Zhang & Zhenzhen Zhang & Qiang Zhou & Pengfei Gao & Haozhe Zhang, 2025. "Short-Term Wind Power Prediction Model Based on PSO-CNN-LSTM," Energies, MDPI, vol. 18(13), pages 1-18, June.
  18. Wang, Yufeng & Yang, Zihan & Ma, Jianhua & Jin, Qun, 2024. "A wind speed forecasting framework for multiple turbines based on adaptive gate mechanism enhanced multi-graph attention networks," Applied Energy, Elsevier, vol. 372(C).
  19. Qiu, Hong & Shi, Kaikai & Wang, Renfang & Zhang, Liang & Liu, Xiufeng & Cheng, Xu, 2024. "A novel temporal–spatial graph neural network for wind power forecasting considering blockage effects," Renewable Energy, Elsevier, vol. 227(C).
  20. Agnieszka Sompolska-Rzechuła & Iwona Bąk & Aneta Becker & Henryk Marjak & Joanna Perzyńska, 2024. "The Use of Renewable Energy Sources and Environmental Degradation in EU Countries," Sustainability, MDPI, vol. 16(23), pages 1-32, November.
  21. Hu, Yue & Liu, Hanjing & Wu, Senzhen & Zhao, Yuan & Wang, Zhijin & Liu, Xiufeng, 2024. "Temporal collaborative attention for wind power forecasting," Applied Energy, Elsevier, vol. 357(C).
  22. Jiang, Wenjun & Liu, Bo & Liang, Yang & Gao, Huanxiang & Lin, Pengfei & Zhang, Dongqin & Hu, Gang, 2024. "Applicability analysis of transformer to wind speed forecasting by a novel deep learning framework with multiple atmospheric variables," Applied Energy, Elsevier, vol. 353(PB).
  23. Verdone, Alessio & Panella, Massimo & De Santis, Enrico & Rizzi, Antonello, 2025. "A review of solar and wind energy forecasting: From single-site to multi-site paradigm," Applied Energy, Elsevier, vol. 392(C).
  24. Dai, Junfeng & Fu, Li-hui, 2024. "A wind speed forecasting model using nonlinear auto-regressive model optimized by the hybrid chaos-cloud salp swarm algorithm," Energy, Elsevier, vol. 298(C).
  25. Oliveira Santos, Victor & Costa Rocha, Paulo Alexandre & Scott, John & Van Griensven Thé, Jesse & Gharabaghi, Bahram, 2023. "Spatiotemporal analysis of bidimensional wind speed forecasting: Development and thorough assessment of LSTM and ensemble graph neural networks on the Dutch database," Energy, Elsevier, vol. 278(PA).
  26. Liang, Yang & Zhang, Dongqin & Zhang, Jize & Hu, Gang, 2024. "A state-of-the-art analysis on decomposition method for short-term wind speed forecasting using LSTM and a novel hybrid deep learning model," Energy, Elsevier, vol. 313(C).
  27. Wang, Zhijin & Liu, Xiufeng & Huang, Yaohui & Zhang, Peisong & Fu, Yonggang, 2023. "A multivariate time series graph neural network for district heat load forecasting," Energy, Elsevier, vol. 278(PA).
  28. Chen, Yunxiao & Lin, Chaojing & Zhang, Yilan & Liu, Jinfu & Yu, Daren, 2024. "Proactive failure warning for wind power forecast models based on volatility indicators analysis," Energy, Elsevier, vol. 305(C).
  29. Ma, Long & Huang, Ling & Shi, Huifeng, 2023. "A novel spatial–temporal generative autoencoder for wind speed uncertainty forecasting," Energy, Elsevier, vol. 282(C).
  30. Qu, Kai & Xue, Shuangsi & Zheng, Xiaodong & Yan, Dapeng & Cao, Hui, 2026. "Learning dynamic inter-farm dependencies for wind power forecasting via adaptive sparse graph attention network," Renewable Energy, Elsevier, vol. 258(C).
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