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Short-term multi-energy load forecasting for integrated energy systems based on CNN-BiGRU optimized by attention mechanism

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Cited by:

  1. Lu, Quan & Huang, Wenxuan & Yin, Linfei, 2025. "Decomposition prediction fractional-order active disturbance rejection control deep Q network for generation control of integrated energy systems," Applied Energy, Elsevier, vol. 377(PD).
  2. Salari, Ali & Shakibi, Hamid & Soltani, Shohreh & Kazemian, Arash & Ma, Tao, 2024. "Optimization assessment and performance analysis of an ingenious hybrid parabolic trough collector: A machine learning approach," Applied Energy, Elsevier, vol. 353(PA).
  3. Ma, Xin & Peng, Bo & Ma, Xiangxue & Tian, Changbin & Yan, Yi, 2023. "Multi-timescale optimization scheduling of regional integrated energy system based on source-load joint forecasting," Energy, Elsevier, vol. 283(C).
  4. Guo, Yanhua & Wang, Ningbo & Shao, Shuangquan & Huang, Congqi & Zhang, Zhentao & Li, Xiaoqiong & Wang, Youdong, 2024. "A review on hybrid physics and data-driven modeling methods applied in air source heat pump systems for energy efficiency improvement," Renewable and Sustainable Energy Reviews, Elsevier, vol. 204(C).
  5. 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).
  6. Ren, Xiaoxiao & Tian, Xin & Wang, Kai & Yang, Sifan & Chen, Weixiong & Wang, Jinshi, 2025. "Enhanced load forecasting for distributed multi-energy system: A stacking ensemble learning method with deep reinforcement learning and model fusion," Energy, Elsevier, vol. 319(C).
  7. Song, Cairong & Yang, Haidong & Cai, Jianyang & Yang, Pan & Bao, Hao & Xu, Kangkang & Meng, Xian-Bing, 2024. "Multi-energy load forecasting via hierarchical multi-task learning and spatiotemporal attention," Applied Energy, Elsevier, vol. 373(C).
  8. Fan, Pengdan & Wang, Dan & Wang, Wei & Zhang, Xiuyu & Sun, Yuying, 2024. "A novel multi-energy load forecasting method based on building flexibility feature recognition technology and multi-task learning model integrating LSTM," Energy, Elsevier, vol. 308(C).
  9. 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).
  10. Keyong Hu & Chunyuan Lang & Zheyi Fu & Yang Feng & Shuifa Sun & Ben Wang, 2024. "Distributed Regional Photovoltaic Power Prediction Based on Stack Integration Algorithm," Mathematics, MDPI, vol. 12(16), pages 1-25, August.
  11. Zeng, Huibin & Shao, Bilin & Dai, Hongbin & Yan, Yichuan & Tian, Ning, 2023. "Prediction of fluctuation loads based on GARCH family-CatBoost-CNNLSTM," Energy, Elsevier, vol. 263(PE).
  12. Liu, Wencheng & Mao, Zhizhong, 2024. "Short-term photovoltaic power forecasting with feature extraction and attention mechanisms," Renewable Energy, Elsevier, vol. 226(C).
  13. Sun, Yang & Tian, Zhirui, 2025. "Solving few-shot problem in wind speed prediction: A novel transfer strategy based on decomposition and learning ensemble," Applied Energy, Elsevier, vol. 377(PD).
  14. Tao Liu & Xiting Ma & Ling Liu & Xin Liu & Yue Zhao & Ning Hu & Kayhan Zrar Ghafoor, 2024. "LAMBERT: Leveraging Attention Mechanisms to Improve the BERT Fine-Tuning Model for Encrypted Traffic Classification," Mathematics, MDPI, vol. 12(11), pages 1-22, May.
  15. Jiang, Yuqi & Gao, Tianlu & Dai, Yuxin & Si, Ruiqi & Hao, Jun & Zhang, Jun & Gao, David Wenzhong, 2022. "Very short-term residential load forecasting based on deep-autoformer," Applied Energy, Elsevier, vol. 328(C).
  16. Zheng Wan & Hui Li, 2023. "Short-Term Power Load Forecasting Based on Feature Filtering and Error Compensation under Imbalanced Samples," Energies, MDPI, vol. 16(10), pages 1-22, May.
  17. 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).
  18. Wang, Yongli & Wang, Huan & Meng, Xiao & Dong, Huanran & Chen, Xin & Xiang, Hao & Xing, Juntai, 2023. "Considering the dual endogenous-exogenous uncertainty integrated energy multiple load short-term forecast," Energy, Elsevier, vol. 285(C).
  19. Hou, Wentao & Ma, Shaojuan, 2025. "Parameter identification of the Black-Scholes model driven by multiplicative fractional Brownian motion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 660(C).
  20. Elinor Ginzburg-Ganz & Eden Dina Horodi & Omar Shadafny & Uri Savir & Ram Machlev & Yoash Levron, 2025. "Statistical Foundations of Generative AI for Optimal Control Problems in Power Systems: Comprehensive Review and Future Directions," Energies, MDPI, vol. 18(10), pages 1-54, May.
  21. Zhou, Guangzhao & Guo, Zanquan & Sun, Simin & Jin, Qingsheng, 2023. "A CNN-BiGRU-AM neural network for AI applications in shale oil production prediction," Applied Energy, Elsevier, vol. 344(C).
  22. Yongning Zhang & Xiaoying Ren & Fei Zhang & Yulei Liu & Jierui Li, 2024. "A Deep Learning-Based Dual-Scale Hybrid Model for Ultra-Short-Term Photovoltaic Power Forecasting," Sustainability, MDPI, vol. 16(17), pages 1-22, August.
  23. 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).
  24. Yin, Linfei & Wang, Nannan & Li, Jishen, 2025. "Electricity terminal multi-label recognition with a “one-versus-all” rejection recognition algorithm based on adaptive distillation increment learning and attention MobileNetV2 network for non-invasiv," Applied Energy, Elsevier, vol. 382(C).
  25. Liu, Zhi-Feng & Zhao, Shi-Xiang & Luo, Xing-Fu & Huang, Ya-He & Gu, Rui-Zheng & Li, Ji-Xiang & Li, Ling-Ling, 2025. "Two-layer energy dispatching and collaborative optimization of regional integrated energy system considering stakeholders game and flexible load management," Applied Energy, Elsevier, vol. 379(C).
  26. Lin, Zhengyang & Lin, Tao & Li, Jun & Li, Chen, 2025. "A novel short-term multi-energy load forecasting method for integrated energy system based on two-layer joint modal decomposition and dynamic optimal ensemble learning," Applied Energy, Elsevier, vol. 378(PA).
  27. Bayode, Israel A. & Ba-Alawi, Abdulrahman H. & Nguyen, Hai-Tra & Woo, Taeyong & Yoo, ChangKyoo, 2025. "Long-term policy guidance for sustainable energy transition in Nigeria: A deep learning-based peak load forecasting with econo-environmental scenario analysis," Energy, Elsevier, vol. 322(C).
  28. 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).
  29. Habib, Salman & El-Ferik, Sami & Gulzar, Muhammad Majid & Chauhdary, Sohaib Tahir & Ahmad, Hasnain & Ahmed, Emad M., 2025. "Optimizing integrated energy systems with a robust MISOCP model and C&CG algorithm for enhanced grid efficiency and profitability," Energy, Elsevier, vol. 318(C).
  30. Tian, Zhirui & Liu, Weican & Zhang, Jiahao & Sun, Wenpu & Wu, Chenye, 2025. "EDformer family: End-to-end multi-task load forecasting frameworks for day-ahead economic dispatch," Applied Energy, Elsevier, vol. 383(C).
  31. Tzu-Chia Chen & José Ricardo Nuñez Alvarez & Ngakan Ketut Acwin Dwijendra & Zainab Jawad Kadhim & Reza Alayi & Ravinder Kumar & Seepana PraveenKumar & Vladimir Ivanovich Velkin, 2023. "Modeling and Optimization of Combined Heating, Power, and Gas Production System Based on Renewable Energies," Sustainability, MDPI, vol. 15(10), pages 1-16, May.
  32. Tan, Mao & Liao, Chengchen & Chen, Jie & Cao, Yijia & Wang, Rui & Su, Yongxin, 2023. "A multi-task learning method for multi-energy load forecasting based on synthesis correlation analysis and load participation factor," Applied Energy, Elsevier, vol. 343(C).
  33. Xie, Xiangmin & Ding, Yuhao & Sun, Yuanyuan & Zhang, Zhisheng & Fan, Jianhua, 2024. "A novel time-series probabilistic forecasting method for multi-energy loads," Energy, Elsevier, vol. 306(C).
  34. Max Olinto Moreira & Betania Mafra Kaizer & Takaaki Ohishi & Benedito Donizeti Bonatto & Antonio Carlos Zambroni de Souza & Pedro Paulo Balestrassi, 2022. "Multivariate Strategy Using Artificial Neural Networks for Seasonal Photovoltaic Generation Forecasting," Energies, MDPI, vol. 16(1), pages 1-30, December.
  35. Yu, Min & Niu, Dongxiao & Zhao, Jinqiu & Li, Mingyu & Sun, Lijie & Yu, Xiaoyu, 2023. "Building cooling load forecasting of IES considering spatiotemporal coupling based on hybrid deep learning model," Applied Energy, Elsevier, vol. 349(C).
  36. Li, Huanhuan & Zhang, Yu & Li, Yan & Lam, Jasmine Siu Lee & Matthews, Christian & Yang, Zaili, 2025. "Deep multi-view information-powered vessel traffic flow prediction for intelligent transportation management," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 197(C).
  37. Su, Miao & Nie, Yufei & Li, Jiankun & Yang, Lin & Kim, Woohyoung, 2024. "Futures markets and the baltic dry index: A prediction study based on deep learning," Research in International Business and Finance, Elsevier, vol. 71(C).
  38. Qingbo Hua & Zengliang Fan & Wei Mu & Jiqiang Cui & Rongxin Xing & Huabo Liu & Junwei Gao, 2024. "A Short-Term Power Load Forecasting Method Using CNN-GRU with an Attention Mechanism," Energies, MDPI, vol. 18(1), pages 1-17, December.
  39. Meng, Anbo & Xie, Zhifeng & Luo, Jianqiang & Zeng, Ying & Xu, Xuancong & Li, Yidian & Wu, Zhenbo & Zhang, Zhan & Zhu, Jianbin & Xian, Zikang & Li, Chen & Yan, Baiping & Yin, Hao, 2023. "An adaptive variational mode decomposition for wind power prediction using convolutional block attention deep learning network," Energy, Elsevier, vol. 282(C).
  40. Li, Chuang & Li, Guojie & Wang, Keyou & Han, Bei, 2022. "A multi-energy load forecasting method based on parallel architecture CNN-GRU and transfer learning for data deficient integrated energy systems," Energy, Elsevier, vol. 259(C).
  41. Peng, Daogang & Liu, Yu & Wang, Danhao & Zhao, Huirong & Qu, Bogang, 2024. "Multi-energy load forecasting for integrated energy system based on sequence decomposition fusion and factors correlation analysis," Energy, Elsevier, vol. 308(C).
  42. Mahdi Khodayar & Jacob Regan, 2023. "Deep Neural Networks in Power Systems: A Review," Energies, MDPI, vol. 16(12), pages 1-38, June.
  43. 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).
  44. 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).
  45. 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).
  46. Hu, Rong & Zhou, Kaile & Lu, Xinhui, 2025. "Integrated loads forecasting with absence of crucial factors," Energy, Elsevier, vol. 322(C).
  47. Zhao, Hongqian & Chen, Zheng & Shu, Xing & Shen, Jiangwei & Lei, Zhenzhen & Zhang, Yuanjian, 2023. "State of health estimation for lithium-ion batteries based on hybrid attention and deep learning," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
  48. Salari, Ali & Shakibi, Hamid & Soleimanzade, Mohammad Amin & Sadrzadeh, Mohtada & Hakkaki-Fard, Ali, 2024. "Application of machine learning in evaluating and optimizing the hydrogen production performance of a solar-based electrolyzer system," Renewable Energy, Elsevier, vol. 220(C).
  49. Suqi Zhang & Ningjing Zhang & Ziqi Zhang & Ying Chen, 2022. "Electric Power Load Forecasting Method Based on a Support Vector Machine Optimized by the Improved Seagull Optimization Algorithm," Energies, MDPI, vol. 15(23), pages 1-17, December.
  50. Yifei Chen & Zhihan Fu, 2023. "Multi-Step Ahead Forecasting of the Energy Consumed by the Residential and Commercial Sectors in the United States Based on a Hybrid CNN-BiLSTM Model," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
  51. Yang, Kailing & Zhang, Xi & Luo, Haojia & Hou, Xianping & Lin, Yu & Wu, Jingyu & Yu, Liang, 2024. "Predicting energy prices based on a novel hybrid machine learning: Comprehensive study of multi-step price forecasting," Energy, Elsevier, vol. 298(C).
  52. Siting Li & Huafeng Cai, 2024. "Short-Term Power Load Forecasting Using a VMD-Crossformer Model," Energies, MDPI, vol. 17(11), pages 1-18, June.
  53. Liao, Chengchen & Tan, Mao & Li, Kang & Chen, Jie & Wang, Rui & Su, Yongxin, 2024. "Sequence signal prediction and reconstruction for multi-energy load forecasting in integrated energy systems: A bi-level multi-task learning method," Energy, Elsevier, vol. 313(C).
  54. Qizhuan Shao & Rungang Bao & Shuangquan Liu & Kaixiang Fu & Li Mo & Wenjing Xiao, 2025. "Short-Term Electric Load Probability Forecasting Based on the BiGRU-GAM-GPR Model," Sustainability, MDPI, vol. 17(12), pages 1-23, June.
  55. Zhang, Jinlai & Yang, Wenjie & Chen, Yumei & Ding, Mingkang & Huang, Huiling & Wang, Bingkun & Gao, Kai & Chen, Shuhan & Du, Ronghua, 2024. "Fast object detection of anomaly photovoltaic (PV) cells using deep neural networks," Applied Energy, Elsevier, vol. 372(C).
  56. Yuvaraj Natarajan & Sri Preethaa K. R. & Gitanjali Wadhwa & Young Choi & Zengshun Chen & Dong-Eun Lee & Yirong Mi, 2024. "Enhancing Building Energy Efficiency with IoT-Driven Hybrid Deep Learning Models for Accurate Energy Consumption Prediction," Sustainability, MDPI, vol. 16(5), pages 1-23, February.
  57. Tang, Telu & Yang, Xiangguo & Li, Muheng & Li, Xin & Huang, Hai & Guan, Cong & Huang, Jiangfan & Wang, Yufan & Zhou, Chaobin, 2025. "Deep learning model-based real-time state-of-health estimation of lithium-ion batteries under dynamic operating conditions," Energy, Elsevier, vol. 317(C).
  58. Jinming Gao & Xianlong Su & Changsu Kim & Kerang Cao & Hoekyung Jung, 2024. "A Parallel Prediction Model for Photovoltaic Power Using Multi-Level Attention and Similar Day Clustering," Energies, MDPI, vol. 17(16), pages 1-17, August.
  59. Guanqun Wang & Haibo Teng & Lei Qiao & Hongtao Yu & You Cui & Kun Xiao, 2024. "Well Logging Reconstruction Based on a Temporal Convolutional Network and Bidirectional Gated Recurrent Unit Network with Attention Mechanism Optimized by Improved Sand Cat Swarm Optimization," Energies, MDPI, vol. 17(11), pages 1-15, June.
  60. Hua, Pengmin & Wang, Haichao & Xie, Zichan & Lahdelma, Risto, 2024. "District heating load patterns and short-term forecasting for buildings and city level," Energy, Elsevier, vol. 289(C).
  61. Yin, Linfei & Ju, Linyi, 2025. "ShuffleTransformerMulti-headAttentionNet network for user load forecasting," Energy, Elsevier, vol. 322(C).
  62. Shi, Jian & Teh, Jiashen & Alharbi, Bader & Lai, Ching-Ming, 2024. "Load forecasting for regional integrated energy system based on two-phase decomposition and mixture prediction model," Energy, Elsevier, vol. 297(C).
  63. Liu, Liqi & Liu, Yanli, 2022. "Load image inpainting: An improved U-Net based load missing data recovery method," Applied Energy, Elsevier, vol. 327(C).
  64. Ting Zhu & Wenbo Wang & Yu Cao & Xia Liu & Zhongyuan Lai & Hui Lan, 2025. "An Innovative Framework for Forecasting the State of Health of Lithium-Ion Batteries Based on an Improved Signal Decomposition Method," Sustainability, MDPI, vol. 17(11), pages 1-25, May.
  65. Wan, Anping & Chang, Qing & AL-Bukhaiti, Khalil & He, Jiabo, 2023. "Short-term power load forecasting for combined heat and power using CNN-LSTM enhanced by attention mechanism," Energy, Elsevier, vol. 282(C).
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  67. Shi, Jian & Teh, Jiashen, 2024. "Load forecasting for regional integrated energy system based on complementary ensemble empirical mode decomposition and multi-model fusion," Applied Energy, Elsevier, vol. 353(PB).
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