IDEAS home Printed from https://ideas.repec.org/r/eee/energy/v282y2023ics0360544223016687.html
   My bibliography  Save this item

Short-term power load forecasting for combined heat and power using CNN-LSTM enhanced by attention mechanism

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Luca Di Persio & Mohammed Alruqimi & Matteo Garbelli, 2024. "Stochastic Approaches to Energy Markets: From Stochastic Differential Equations to Mean Field Games and Neural Network Modeling," Energies, MDPI, vol. 17(23), pages 1-46, December.
  2. Gong, Zhipeng & Wan, Anping & Ji, Yunsong & AL-Bukhaiti, Khalil & Yao, Zhehe, 2024. "Improving short-term offshore wind speed forecast accuracy using a VMD-PE-FCGRU hybrid model," Energy, Elsevier, vol. 295(C).
  3. Fargalla, Mandella Ali M. & Yan, Wei & Deng, Jingen & Wu, Tao & Kiyingi, Wyclif & Li, Guangcong & Zhang, Wei, 2024. "TimeNet: Time2Vec attention-based CNN-BiGRU neural network for predicting production in shale and sandstone gas reservoirs," Energy, Elsevier, vol. 290(C).
  4. Wang, Jun & Cao, Junxing, 2024. "Reservoir properties inversion using attention-based parallel hybrid network integrating feature selection and transfer learning," Energy, Elsevier, vol. 304(C).
  5. Minan Tang & Changyou Wang & Jiandong Qiu & Hanting Li & Xi Guo & Wenxin Sheng, 2024. "Short-Term Load Forecasting of Electric Vehicle Charging Stations Accounting for Multifactor IDBO Hybrid Models," Energies, MDPI, vol. 17(12), pages 1-19, June.
  6. Prajowal Manandhar & Hasan Rafiq & Edwin Rodriguez-Ubinas & Themis Palpanas, 2024. "New Forecasting Metrics Evaluated in Prophet, Random Forest, and Long Short-Term Memory Models for Load Forecasting," Energies, MDPI, vol. 17(23), pages 1-30, December.
  7. Yan, Xiuying & Ji, Xingxing & Meng, Qinglong & Sun, Hang & Lei, Yu, 2024. "A hybrid prediction model of improved bidirectional long short-term memory network for cooling load based on PCANet and attention mechanism," Energy, Elsevier, vol. 292(C).
  8. Jiang, Ben & Li, Yu & Rezgui, Yacine & Zhang, Chengyu & Wang, Peng & Zhao, Tianyi, 2024. "Multi-source domain generalization deep neural network model for predicting energy consumption in multiple office buildings," Energy, Elsevier, vol. 299(C).
  9. Wang, Han & Yan, Jie & Zhang, Jiawei & Liu, Shihua & Liu, Yongqian & Han, Shuang & Qu, Tonghui, 2024. "Short-term integrated forecasting method for wind power, solar power, and system load based on variable attention mechanism and multi-task learning," Energy, Elsevier, vol. 304(C).
  10. Chen, Haoyu & Huang, Hai & Zheng, Yong & Yang, Bing, 2024. "A load forecasting approach for integrated energy systems based on aggregation hybrid modal decomposition and combined model," Applied Energy, Elsevier, vol. 375(C).
  11. Huiqun Yu & Haoyi Sun & Yueze Li & Chunmei Xu & Chenkun Du, 2024. "Enhanced Short-Term Load Forecasting: Error-Weighted and Hybrid Model Approach," Energies, MDPI, vol. 17(21), pages 1-22, October.
  12. Gomez, William & Wang, Fu-Kwun & Lo, Shih-Che, 2024. "A hybrid approach based machine learning models in electricity markets," Energy, Elsevier, vol. 289(C).
  13. Hu, Likun & Cao, Yi & Yin, Linfei, 2024. "Long-term price guidance mechanism for integrated energy systems based on gated recurrent unit - vision transformer prediction and fractional-order stochastic dynamic calculus control," Energy, Elsevier, vol. 312(C).
  14. Xu, Huifeng & Hu, Feihu & Liang, Xinhao & Zhao, Guoqing & Abugunmi, Mohammad, 2024. "A framework for electricity load forecasting based on attention mechanism time series depthwise separable convolutional neural network," Energy, Elsevier, vol. 299(C).
  15. Cui, Xuyang & Zhu, Junda & Jia, Lifu & Wang, Jiahui & Wu, Yusen, 2024. "A novel heat load prediction model of district heating system based on hybrid whale optimization algorithm (WOA) and CNN-LSTM with attention mechanism," Energy, Elsevier, vol. 312(C).
  16. Hu, Likun & Cao, Yi & Yin, Linfei, 2024. "Fractional-order long-term price guidance mechanism based on bidirectional prediction with attention mechanism for electric vehicle charging," Energy, Elsevier, vol. 293(C).
  17. Fengtian Chang & Guanghui Zhou & Kai Ding & Jintao Li & Yanzhen Jing & Jizhuang Hui & Chao Zhang, 2023. "A CNN-LSTM and Attention-Mechanism-Based Resistance Spot Welding Quality Online Detection Method for Automotive Bodies," Mathematics, MDPI, vol. 11(22), pages 1-19, November.
  18. Tian, Zhirui & Liu, Weican & Jiang, Wenqian & Wu, Chenye, 2024. "CNNs-Transformer based day-ahead probabilistic load forecasting for weekends with limited data availability," Energy, Elsevier, vol. 293(C).
  19. Dong, Juan & Xing, Liwen & Cui, Ningbo & Zhao, Lu & Guo, Li & Wang, Zhihui & Du, Taisheng & Tan, Mingdong & Gong, Daozhi, 2024. "Estimating reference crop evapotranspiration using improved convolutional bidirectional long short-term memory network by multi-head attention mechanism in the four climatic zones of China," Agricultural Water Management, Elsevier, vol. 292(C).
  20. Li, Shoujiang & Wang, Jianzhou & Zhang, Hui & Liang, Yong, 2024. "Enhancing hourly electricity forecasting using fuzzy cognitive maps with sample entropy," Energy, Elsevier, vol. 298(C).
  21. Zhang, Chengyu & Luo, Zhiwen & Rezgui, Yacine & Zhao, Tianyi, 2024. "Enhancing building energy consumption prediction introducing novel occupant behavior models with sparrow search optimization and attention mechanisms: A case study for forty-five buildings in a univer," Energy, Elsevier, vol. 294(C).
  22. Moreno, Sinvaldo Rodrigues & Seman, Laio Oriel & Stefenon, Stefano Frizzo & Coelho, Leandro dos Santos & Mariani, Viviana Cocco, 2024. "Enhancing wind speed forecasting through synergy of machine learning, singular spectral analysis, and variational mode decomposition," Energy, Elsevier, vol. 292(C).
  23. Ma, Kai & Nie, Xuefeng & Yang, Jie & Zha, Linlin & Li, Guoqiang & Li, Haibin, 2025. "A power load forecasting method in port based on VMD-ICSS-hybrid neural network," Applied Energy, Elsevier, vol. 377(PB).
  24. He, Yan & Zhang, Hongli & Dong, Yingchao & Wang, Cong & Ma, Ping, 2024. "Residential net load interval prediction based on stacking ensemble learning," Energy, Elsevier, vol. 296(C).
  25. Saini, Priyesh & Parida, S.K., 2024. "A novel probabilistic gradient boosting model with multi-approach feature selection and iterative seasonal trend decomposition for short-term load forecasting," Energy, Elsevier, vol. 294(C).
  26. Farid Moazzen & M. J. Hossain, 2024. "Multivariate Deep Learning Long Short-Term Memory-Based Forecasting for Microgrid Energy Management Systems," Energies, MDPI, vol. 17(17), pages 1-16, August.
  27. Peng, Shiliang & Fan, Lin & Zhang, Li & Su, Huai & He, Yuxuan & He, Qian & Wang, Xiao & Yu, Dejun & Zhang, Jinjun, 2024. "Spatio-temporal prediction of total energy consumption in multiple regions using explainable deep neural network," Energy, Elsevier, vol. 301(C).
  28. Li, Feng & Liu, Shiheng & Wang, Tianhu & Liu, Ranran, 2024. "Optimal planning for integrated electricity and heat systems using CNN-BiLSTM-Attention network forecasts," Energy, Elsevier, vol. 309(C).
  29. Yang, Yi & Xing, Qianyi & Wang, Kang & Li, Caihong & Wang, Jianzhou & Huang, Xiaojia, 2024. "A novel combined probabilistic load forecasting system integrating hybrid quantile regression and knee improved multi-objective optimization strategy," Applied Energy, Elsevier, vol. 356(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.