Short-term wind speed forecasting based on spatial-temporal graph transformer networks
Citations
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Cited by:
- Wu, Tangjie & Ling, Qiang, 2024. "STELLM: Spatio-temporal enhanced pre-trained large language model for wind speed forecasting," Applied Energy, Elsevier, vol. 375(C).
- Bentsen, Lars Ødegaard & Warakagoda, Narada Dilp & Stenbro, Roy & Engelstad, Paal, 2023. "Spatio-temporal wind speed forecasting using graph networks and novel Transformer architectures," Applied Energy, Elsevier, vol. 333(C).
- Wang, Sen & Sun, Yonghui & Zhang, Wenjie & Srinivasan, Dipti, 2025. "Optimization of deterministic and probabilistic forecasting for wind power based on ensemble learning," Energy, Elsevier, vol. 319(C).
- 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).
- Cheng, Renxuan & Shi, Jiarong, 2026. "Collaborative wind speed forecasting based on multi-strategy MVMD and RestrictedCrossformer," Energy, Elsevier, vol. 346(C).
- Zhe Dong & Yiyang Zhao & Anqi Wang & Meng Zhou, 2025. "Wind-Mambaformer: Ultra-Short-Term Wind Turbine Power Forecasting Based on Advanced Transformer and Mamba Models," Energies, MDPI, vol. 18(5), pages 1-22, February.
- Luo, Haiwei & Shi, Huifeng & Shi, Qiong & Chen, Xinjie & Duan, Yawen & Yan, Saisai, 2025. "Wind speed forecasting using dual-attention patch-based multiscale transformer," Energy, Elsevier, vol. 340(C).
- Li, Shaopeng & Li, Xin & Jiang, Yan & Yang, Qingshan & Lin, Min & Peng, Liuliu & Yu, Jianhan, 2025. "A novel frequency-domain physics-informed neural network for accurate prediction of 3D spatio-temporal wind fields in wind turbine applications," Applied Energy, Elsevier, vol. 386(C).
- Wu, Binrong & Yu, Sihao & Peng, Lu & Wang, Lin, 2024. "Interpretable wind speed forecasting with meteorological feature exploring and two-stage decomposition," Energy, Elsevier, vol. 294(C).
- 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).
- 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).
- Lu Peng & Sheng‐Xiang Lv & Lin Wang, 2024. "Explainable machine learning techniques based on attention gate recurrent unit and local interpretable model‐agnostic explanations for multivariate wind speed forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2064-2087, September.
- Lin, Shengmao & Wang, Shu & Xu, Xuefang & Li, Ruixiong & Shi, Peiming, 2024. "GAOformer: An adaptive spatiotemporal feature fusion transformer utilizing GAT and optimizable graph matrixes for offshore wind speed prediction," Energy, Elsevier, vol. 292(C).
- Yang, Mao & Huang, Yutong & Xu, Chuanyu & Liu, Chenyu & Dai, Bozhi, 2025. "Review of several key processes in wind power forecasting: Mathematical formulations, scientific problems, and logical relations," Applied Energy, Elsevier, vol. 377(PC).
- Wu, Tangjie & Ling, Qiang, 2024. "Self-supervised dynamic stochastic graph network for spatio-temporal wind speed forecasting," Energy, Elsevier, vol. 304(C).
- Liu, Ling & Wang, Jujie & Li, Jianping & Wei, Lu, 2023. "Dual-meta pool method for wind farm power forecasting with small sample data," Energy, Elsevier, vol. 267(C).
- Resifi, Sofien & Aawar, Elissar Al & Dasari, Hari Prasad & Jebari, Hatem & Hoteit, Ibrahim, 2025. "A novel deep learning approach for regional high-resolution spatio-temporal wind speed forecasting for energy applications," Energy, Elsevier, vol. 328(C).
- Ma, Long & Huang, Ling & Shi, Huifeng, 2023. "A novel spatial–temporal generative autoencoder for wind speed uncertainty forecasting," Energy, Elsevier, vol. 282(C).
- 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).
- Li, Xuehan & Wang, Wei & Fang, Fang & Liu, Jizhen & Chen, Zhe, 2025. "Improving active power regulation for wind turbine by phase leading cascaded error-based active disturbance rejection control and multi-objective optimization," Renewable Energy, Elsevier, vol. 243(C).
- Wu, Binrong & Lin, Jiacheng & Liu, Rui & Wang, Lin, 2026. "A multi-dimensional interpretable wind speed forecasting model with two-stage feature exploring," Renewable Energy, Elsevier, vol. 256(PB).
- Lv, Yunlong & Hu, Qin & Xu, Hang & Lin, Huiyao & Wu, Yufan, 2024. "An ultra-short-term wind power prediction method based on spatial-temporal attention graph convolutional model," Energy, Elsevier, vol. 293(C).
- Du, Pei & Yang, Dongchuan & Li, Yanzhao & Wang, Jianzhou, 2024. "An innovative interpretable combined learning model for wind speed forecasting," Applied Energy, Elsevier, vol. 358(C).
- Wu, Xinning & Zhan, Haolin & Hu, Jianming & Wang, Ying, 2025. "Non-stationary GNNCrossformer: Transformer with graph information for non-stationary multivariate Spatio-Temporal wind power data forecasting," Applied Energy, Elsevier, vol. 377(PB).
- Zhang, Dongqin & Hu, Gang & Song, Jie & Gao, Huanxiang & Ren, Hehe & Chen, Wenli, 2024. "A novel spatio-temporal wind speed forecasting method based on the microscale meteorological model and a hybrid deep learning model," Energy, Elsevier, vol. 288(C).
- Ma, Jiawei & Du, Jie & Chen, Qixian & Jiang, Xinyu & Pan, Linlin, 2025. "Multi-feature extraction spatio-temporal interaction graph network for wind speed forecasting in windfarm," Energy, Elsevier, vol. 333(C).
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