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Robust framework based on hybrid deep learning approach for short term load forecasting of building electricity demand

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  1. Zhao, Xiaoyu & Duan, Pengfei & Cao, Xiaodong & Xue, Qingwen & Zhao, Bingxu & Hu, Jinxue & Zhang, Chenyang & Yuan, Xiaoyang, 2025. "A probabilistic load forecasting method for multi-energy loads based on inflection point optimization and integrated feature screening," Energy, Elsevier, vol. 327(C).
  2. Xinfu Liu & Wei Liu & Wei Zhou & Yanfeng Cao & Mengxiao Wang & Wenhao Hu & Chunhua Liu & Peng Liu & Guoliang Liu, 2024. "Multi-Energy Coupling Load Forecasting in Integrated Energy System with Improved Variational Mode Decomposition-Temporal Convolutional Network-Bidirectional Long Short-Term Memory Model," Sustainability, MDPI, vol. 16(22), pages 1-18, November.
  3. Jin, Haowei & Guo, Jue & Tang, Lei & Du, Pei, 2024. "Long-term electricity demand forecasting under low-carbon energy transition: Based on the bidirectional feedback between power demand and generation mix," Energy, Elsevier, vol. 286(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. Xiaoyu Liu & Jiangfeng Song & Hai Tao & Peng Wang & Haihua Mo & Wenjie Du, 2025. "Quarter-Hourly Power Load Forecasting Based on a Hybrid CNN-BiLSTM-Attention Model with CEEMDAN, K-Means, and VMD," Energies, MDPI, vol. 18(11), pages 1-29, May.
  6. Ye, Lin & Wang, Chengyou & Zhou, Xiao & Jiang, Baocheng & Yu, Changsong & Qin, Zhiliang, 2025. "Natural gas pipeline weak leakage detection based on negative pressure wave decomposition and feature enhancement," Reliability Engineering and System Safety, Elsevier, vol. 257(PB).
  7. Afzal, Sadegh & Ziapour, Behrooz M. & Shokri, Afshar & Shakibi, Hamid & Sobhani, Behnam, 2023. "Building energy consumption prediction using multilayer perceptron neural network-assisted models; comparison of different optimization algorithms," Energy, Elsevier, vol. 282(C).
  8. Ge, Chang & Yan, Jie & Song, Weiye & Zhang, Haoran & Wang, Han & Li, Yuhao & Liu, Yongqian, 2025. "Middle-term wind power forecasting method based on long-span NWP and microscale terrain fusion correction," Renewable Energy, Elsevier, vol. 240(C).
  9. 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).
  10. Siqiong Dai & Liang Yuan & Jiayi Zhong & Xubin Liu & Zhangjie Liu, 2025. "Forecasting Residential EV Charging Pile Capacity in Urban Power Systems: A Cointegration–BiLSTM Hybrid Approach," Sustainability, MDPI, vol. 17(14), pages 1-18, July.
  11. Hisham Alghamdi & Ghulam Hafeez & Sajjad Ali & Safeer Ullah & Muhammad Iftikhar Khan & Sadia Murawwat & Lyu-Guang Hua, 2023. "An Integrated Model of Deep Learning and Heuristic Algorithm for Load Forecasting in Smart Grid," Mathematics, MDPI, vol. 11(21), pages 1-22, November.
  12. Lu, Shengdong & Yang, Xinle & Bu, Shujuan & Li, Weikang & Yu, Ning & Wang, Xin & Dai, Wenzhi & Liu, Xunan, 2024. "Performance and parameter prediction of SCR–ORC system based on data–model fusion and twin data–driven," Energy, Elsevier, vol. 290(C).
  13. Dong, Juan & Zhu, Yuanjun & Cui, Ningbo & Jia, Xiaoxu & Guo, Li & Qiu, Rangjian & Shao, Ming’an, 2024. "Estimating crop evapotranspiration of wheat-maize rotation system using hybrid convolutional bidirectional Long Short-Term Memory network with grey wolf algorithm in Chinese Loess Plateau region," Agricultural Water Management, Elsevier, vol. 301(C).
  14. Yan, Yi & Wang, Xuerui & Li, Ke & Li, Chengdong & Tian, Chongyi & Shao, Zhuliang & Li, Ji, 2024. "Stochastic optimisation of district integrated energy systems based on a hybrid probability forecasting model," Energy, Elsevier, vol. 306(C).
  15. Filipe Rodrigues & Carlos Cardeira & João M. F. Calado & Rui Melicio, 2023. "Short-Term Load Forecasting of Electricity Demand for the Residential Sector Based on Modelling Techniques: A Systematic Review," Energies, MDPI, vol. 16(10), pages 1-26, May.
  16. Akash Mahajan & Srijita Das & Wencong Su & Van-Hai Bui, 2024. "Bayesian-Neural-Network-Based Approach for Probabilistic Prediction of Building-Energy Demands," Sustainability, MDPI, vol. 16(22), pages 1-21, November.
  17. Pesantez, Jorge E. & Li, Binbin & Lee, Christopher & Zhao, Zhizhen & Butala, Mark & Stillwell, Ashlynn S., 2023. "A Comparison Study of Predictive Models for Electricity Demand in a Diverse Urban Environment," Energy, Elsevier, vol. 283(C).
  18. Atif Maqbool Khan & Artur Wyrwa, 2024. "A Survey of Quantitative Techniques in Electricity Consumption—A Global Perspective," Energies, MDPI, vol. 17(19), pages 1-38, September.
  19. 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).
  20. Hribar, Jernej & Fortuna, Carolina & Mohorčič, Mihael, 2025. "The role of age of information in enhancing short-term energy forecasting," Energy, Elsevier, vol. 318(C).
  21. Sepideh Radhoush & Bradley M. Whitaker & Hashem Nehrir, 2023. "An Overview of Supervised Machine Learning Approaches for Applications in Active Distribution Networks," Energies, MDPI, vol. 16(16), pages 1-29, August.
  22. Lu, Wanbo & Liu, Qibo & Wang, Jie, 2024. "Effect of electricity policy uncertainty and carbon emission prices on electricity demand in China based on mixed-frequency data models," Utilities Policy, Elsevier, vol. 91(C).
  23. Mustafa Saglam & Catalina Spataru & Omer Ali Karaman, 2023. "Forecasting Electricity Demand in Turkey Using Optimization and Machine Learning Algorithms," Energies, MDPI, vol. 16(11), pages 1-23, June.
  24. Chuyi Luo & Liang Xia & Sung-Hugh Hong, 2025. "A Method for Selecting the Appropriate Source Domain Buildings for Building Energy Prediction in Transfer Learning: Using the Euclidean Distance and Pearson Coefficient," Energies, MDPI, vol. 18(14), pages 1-27, July.
  25. Aristeidis Mystakidis & Paraskevas Koukaras & Nikolaos Tsalikidis & Dimosthenis Ioannidis & Christos Tjortjis, 2024. "Energy Forecasting: A Comprehensive Review of Techniques and Technologies," Energies, MDPI, vol. 17(7), pages 1-33, March.
  26. Xue, Haiteng & Wang, Gongda & Li, Xijian & Du, Feng, 2024. "Predictive combination model for CH4 separation and CO2 sequestration with CO2 injection into coal seams: VMD-STA-BiLSTM-ELM hybrid neural network modeling," Energy, Elsevier, vol. 313(C).
  27. Renxi Gong & Zhihuan Wei & Yan Qin & Tao Liu & Jiawei Xu, 2024. "Short-Term Electrical Load Forecasting Based on IDBO-PTCN-GRU Model," Energies, MDPI, vol. 17(18), pages 1-24, September.
  28. Paraskevas Koukaras & Akeem Mustapha & Aristeidis Mystakidis & Christos Tjortjis, 2024. "Optimizing Building Short-Term Load Forecasting: A Comparative Analysis of Machine Learning Models," Energies, MDPI, vol. 17(6), pages 1-26, March.
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