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Spatio-temporal wind speed forecasting using graph networks and novel Transformer architectures

Citations

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Cited by:

  1. Wang, Yun & Duan, Xiaocong & Zhang, Fan & Wu, Guang & Zou, Runmin & Wan, Jie & Hu, Qinghua, 2025. "MFFDM-WLS: A multi-granularity feature-based coherent forecasting method for temporal hierarchical wind speed time series," Applied Energy, Elsevier, vol. 400(C).
  2. Yan Chen & Miaolin Yu & Haochong Wei & Huanxing Qi & Yiming Qin & Xiaochun Hu & Rongxing Jiang, 2025. "A Lightweight Framework for Rapid Response to Short-Term Forecasting of Wind Farms Using Dual Scale Modeling and Normalized Feature Learning," Energies, MDPI, vol. 18(3), pages 1-20, January.
  3. Wang, Zhongrui & Wang, Chunbo & Chen, Liang & Yu, Min & Yuan, Wenteng, 2025. "Short-term offshore wind power multi-location multi-modal multi-step prediction model based on Informer (M3STIN)," Energy, Elsevier, vol. 322(C).
  4. 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).
  5. Wang, Jianing & Gao, Shan & Zhao, Xin & Huang, Xueliang & Lu, Jianyu & Wu, Chuanshen, 2025. "A cross-domain information fusion method for non-stationary distributed photovoltaic forecasting," Applied Energy, Elsevier, vol. 402(PA).
  6. Pei, Ming & Gong, Ruqing & Ye, Lin & Chen, Lei & Sun, Yihui & Tang, Yong, 2026. "Spatiotemporal sparse autoregressive distributed lag model with extended Regressors for regional wind power forecasting," Applied Energy, Elsevier, vol. 404(C).
  7. Li, HongYang & He, Shan & Yuan, JiaWang & Wang, Chao, 2025. "A wind power prediction method integrating dynamic multi-scale spatio-temporal modelling, adaptive multi-strategy local decomposition, and meta-learning ensemble model," Energy, Elsevier, vol. 340(C).
  8. Houndekindo, Freddy & Ouarda, Taha B.M.J., 2025. "LSTM and Transformer-based framework for bias correction of ERA5 hourly wind speeds," Energy, Elsevier, vol. 328(C).
  9. Pia Leminski & Enzo Pinheiro & Taha B. M. J. Ouarda, 2025. "Ensemble of Artificial Neural Networks for Seasonal Forecasting of Wind Speed in Eastern Canada," Energies, MDPI, vol. 18(11), pages 1-17, June.
  10. Yang, Yakai & Fan, Shuanglong & Liu, Zhenqing & Yu, Zhongze, 2025. "WD-SGformer: high-precision wind power forecasting via dual-attention dynamic spatio-temporal learning," Energy, Elsevier, vol. 337(C).
  11. Chen, Yunxiao & Liu, Jinfu & Yu, Daren, 2025. "Economically-driven spatiotemporal collaborative correction of high-precision wind power forecasting curves: aiming to more practical scheduling," Energy, Elsevier, vol. 337(C).
  12. Xu, Hao & Zhu, Zhenhao & Liu, Hongbing & Zio, Enrico & Qiu, Xiaolong & Lu, Yuchen & Qu, Xianqiang, 2025. "Spectral dynamic aggregation transformer and fitted swing-door algorithm for wind power monitoring," Energy, Elsevier, vol. 341(C).
  13. Jinhua Zhang & Hui Li & Peng Cheng & Jie Yan, 2024. "Interpretable Wind Power Short-Term Power Prediction Model Using Deep Graph Attention Network," Energies, MDPI, vol. 17(2), pages 1-16, January.
  14. Xian, Sidong & Feng, Miaomiao & Cheng, Yue, 2023. "Incremental nonlinear trend fuzzy granulation for carbon trading time series forecast," Applied Energy, Elsevier, vol. 352(C).
  15. 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).
  16. 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).
  17. Yang, Ting & Yang, Zhenning & Li, Fei & Wang, Hengyu, 2024. "A short-term wind power forecasting method based on multivariate signal decomposition and variable selection," Applied Energy, Elsevier, vol. 360(C).
  18. Qin, Rui & Chai, Hwa Kian & Liu, Kai & Yu, Hang & Huang, Jing, 2025. "A hierarchical multi-stage fusion deep learning framework for short-term wind power prediction," Renewable Energy, Elsevier, vol. 253(C).
  19. Hongxia Wang & Xiao Jin & Jianian Wang & Hongxia Hao, 2023. "Nonparametric Estimation for High-Dimensional Space Models Based on a Deep Neural Network," Mathematics, MDPI, vol. 11(18), pages 1-37, September.
  20. Dong, Xianzhou & Luo, Yongqiang & Yuan, Shuo & Tian, Zhiyong & Zhang, Limao & Wu, Xiaoying & Liu, Baobing, 2025. "Building electricity load forecasting based on spatiotemporal correlation and electricity consumption behavior information," Applied Energy, Elsevier, vol. 377(PB).
  21. Elshafei, Basem & Popov, Atanas & Giddings, Donald, 2024. "Enhanced offshore wind resource assessment using hybrid data fusion and numerical models," Energy, Elsevier, vol. 310(C).
  22. 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).
  23. Shao, Zhen & Zhu, Guowei & Han, Yating & Zha, Jianrui & Yang, Changhui & Li, Fangyi, 2025. "Multi-distribution fusion based Bayesian deep neural network for short-term probabilistic electricity price forecasting," Applied Energy, Elsevier, vol. 401(PB).
  24. Xu, Xuefang & Hu, Shiting & Shao, Huaishuang & Shi, Peiming & Li, Ruixiong & Li, Deguang, 2023. "A spatio-temporal forecasting model using optimally weighted graph convolutional network and gated recurrent unit for wind speed of different sites distributed in an offshore wind farm," Energy, Elsevier, vol. 284(C).
  25. Zhang, Jun & Zhang, Yagang & Liu, Ke & Zhao, Chunyang, 2025. "Multi-step prediction of spatio-temporal wind speed based on the multimodal coupled ST-DFNet model," Energy, Elsevier, vol. 334(C).
  26. Chen, Fuhao & Yan, Jie & Liu, Yongqian & Yan, Yamin & Tjernberg, Lina Bertling, 2024. "A novel meta-learning approach for few-shot short-term wind power forecasting," Applied Energy, Elsevier, vol. 362(C).
  27. Xu, Ningke & Li, Shuang & Xu, Kun & Lu, Cheng, 2025. "Research on methane Hazard interval prediction method based on hybrid “model-data”driven strategy," Applied Energy, Elsevier, vol. 377(PC).
  28. Wu, Tangjie & Ling, Qiang, 2024. "STELLM: Spatio-temporal enhanced pre-trained large language model for wind speed forecasting," Applied Energy, Elsevier, vol. 375(C).
  29. Niu, Zhewen & Han, Xiaoqing & Zhang, Dongxia & Wu, Yuxiang & Lan, Songyan, 2024. "Interpretable wind power forecasting combining seasonal-trend representations learning with temporal fusion transformers architecture," Energy, Elsevier, vol. 306(C).
  30. Wu, Binrong & Wang, Lin, 2024. "Two-stage decomposition and temporal fusion transformers for interpretable wind speed forecasting," Energy, Elsevier, vol. 288(C).
  31. Wu Xu & Wenjing Dai & Dongyang Li & Qingchang Wu, 2024. "Short-Term Wind Power Prediction Based on a Variational Mode Decomposition–BiTCN–Psformer Hybrid Model," Energies, MDPI, vol. 17(16), pages 1-17, August.
  32. Lars Ødegaard Bentsen & Narada Dilp Warakagoda & Roy Stenbro & Paal Engelstad, 2023. "A Unified Graph Formulation for Spatio-Temporal Wind Forecasting," Energies, MDPI, vol. 16(20), pages 1-23, October.
  33. Li, Mingjun & Zhang, Kequan & Kou, Menggang & Ma, Yining, 2025. "An offshore wind speed forecasting system based on feature enhancement, deep time series clustering, and extended LSTM," Energy, Elsevier, vol. 333(C).
  34. Liu, Yuqi & Yuan, Weimin & Chen, Weilong & Li, Wenming & Yang, Han & Zhang, Yanru, 2025. "CPLLM-WPF: A multi-scale prompting framework for generalizable wind power forecasting with LLMs," Applied Energy, Elsevier, vol. 402(PA).
  35. 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).
  36. Gao, Huanxiang & Hu, Gang & Zhang, Dongqin & Jiang, Wenjun & Ren, Hehe & Chen, Wenli, 2024. "Prediction of wind fields in mountains at multiple elevations using deep learning models," Applied Energy, Elsevier, vol. 353(PA).
  37. 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).
  38. Wang, Shuangxin & Shi, Jiarong & Yang, Wei & Yin, Qingyan, 2024. "High and low frequency wind power prediction based on Transformer and BiGRU-Attention," Energy, Elsevier, vol. 288(C).
  39. Gomez, William & Wang, Fu-Kwun & Sheu, Shey-Huei, 2025. "Short-term smart grid energy forecasting using a hybrid deep learning method on univariate and multivariate data sets," Energy, Elsevier, vol. 335(C).
  40. Wang, Han & Li, Yunzhou & Yan, Jie & Xiao, Wuyang & Han, Shuang & Liu, Yongqian, 2025. "A novel minute-scale prediction method of incoming wind conditions with limited LiDAR data," Renewable Energy, Elsevier, vol. 240(C).
  41. Mo, Yipeng & Wang, Haoxin & Yang, Chengteng & Yao, Zuhua & Li, Bixiong & Fan, Songhai & Mo, Site, 2024. "FDNet: Frequency filter enhanced dual LSTM network for wind power forecasting," Energy, Elsevier, vol. 312(C).
  42. Shi, Jian & Teh, Jiashen & Lai, Ching-Ming, 2025. "Wind power prediction based on improved self-attention mechanism combined with Bi-directional Temporal Convolutional Network," Energy, Elsevier, vol. 322(C).
  43. 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).
  44. Junhao Zhao & Xiaodong Shen & Youbo Liu & Junyong Liu & Xisheng Tang, 2024. "Enhancing Aggregate Load Forecasting Accuracy with Adversarial Graph Convolutional Imputation Network and Learnable Adjacency Matrix," Energies, MDPI, vol. 17(18), pages 1-28, September.
  45. Shi, Peiming & Lin, Shengmao & Song, Dongran & Xu, Xuefang & Wu, Jie, 2024. "TRNet: A trend and residual network utilizing novel hilly attention mechanism for wind speed prediction in complex scenario," Energy, Elsevier, vol. 309(C).
  46. Zhu, Nanyang & Wang, Ying & Yuan, Kun & Yan, Jiahao & Li, Yaping & Zhang, Kaifeng, 2024. "GGNet: A novel graph structure for power forecasting in renewable power plants considering temporal lead-lag correlations," Applied Energy, Elsevier, vol. 364(C).
  47. 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).
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