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Building thermal load prediction through shallow machine learning and deep learning

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  1. Huang, Yaohui & Zhao, Yuan & Wang, Zhijin & Liu, Xiufeng & Liu, Hanjing & Fu, Yonggang, 2023. "Explainable district heat load forecasting with active deep learning," Applied Energy, Elsevier, vol. 350(C).
  2. Jia, Lizhi & Liu, Junjie & Chong, Adrian & Dai, Xilei, 2022. "Deep learning and physics-based modeling for the optimization of ice-based thermal energy systems in cooling plants," Applied Energy, Elsevier, vol. 322(C).
  3. Lu, Chujie & Li, Sihui & Reddy Penaka, Santhan & Olofsson, Thomas, 2023. "Automated machine learning-based framework of heating and cooling load prediction for quick residential building design," Energy, Elsevier, vol. 274(C).
  4. Neubauer, Alexander & Brandt, Stefan & Kriegel, Martin, 2024. "Relationship between feature importance and building characteristics for heating load predictions," Applied Energy, Elsevier, vol. 359(C).
  5. Kgothatso Makubyane & Daniel Maposa, 2024. "Forecasting Short- and Long-Term Wind Speed in Limpopo Province Using Machine Learning and Extreme Value Theory," Forecasting, MDPI, vol. 6(4), pages 1-23, October.
  6. Sun, Fangyuan & Kong, Xiangyu & Wu, Jianzhong & Gao, Bixuan & Chen, Ke & Lu, Ning, 2022. "DSM pricing method based on A3C and LSTM under cloud-edge environment," Applied Energy, Elsevier, vol. 315(C).
  7. Kyoungcheol Oh & Eui-Jong Kim & Chang-Young Park, 2022. "A Physical Model-Based Data-Driven Approach to Overcome Data Scarcity and Predict Building Energy Consumption," Sustainability, MDPI, vol. 14(15), pages 1-14, August.
  8. Jason Runge & Radu Zmeureanu, 2021. "A Review of Deep Learning Techniques for Forecasting Energy Use in Buildings," Energies, MDPI, vol. 14(3), pages 1-26, January.
  9. Mateo Jesper & Felix Pag & Klaus Vajen & Ulrike Jordan, 2022. "Heat Load Profiles in Industry and the Tertiary Sector: Correlation with Electricity Consumption and Ex Post Modeling," Sustainability, MDPI, vol. 14(7), pages 1-32, March.
  10. Zhou, Yuan & Wang, Jiangjiang & Liu, Yi & Yan, Rujing & Ma, Yanpeng, 2021. "Incorporating deep learning of load predictions to enhance the optimal active energy management of combined cooling, heating and power system," Energy, Elsevier, vol. 233(C).
  11. Li, Sihui & Peng, Jinqing & Zou, Bin & Li, Bojia & Lu, Chujie & Cao, Jingyu & Luo, Yimo & Ma, Tao, 2021. "Zero energy potential of photovoltaic direct-driven air conditioners with considering the load flexibility of air conditioners," Applied Energy, Elsevier, vol. 304(C).
  12. Bruck, Axel & Díaz Ruano, Santiago & Auer, Hans, 2022. "One piece of the puzzle towards 100 Positive Energy Districts (PEDs) across Europe by 2025: An open-source approach to unveil favourable locations of PV-based PEDs from a techno-economic perspective," Energy, Elsevier, vol. 254(PA).
  13. Liu, Yiren & Zhao, Xiangyu & Qin, S. Joe, 2024. "Dynamically engineered multi-modal feature learning for predictions of office building cooling loads," Applied Energy, Elsevier, vol. 355(C).
  14. Seyfi, Mohammad & Mehdinejad, Mehdi & Mohammadi-Ivatloo, Behnam & Shayanfar, Heidarali, 2022. "Deep learning-based scheduling of virtual energy hubs with plug-in hybrid compressed natural gas-electric vehicles," Applied Energy, Elsevier, vol. 321(C).
  15. Huang, Guizao & Wu, Guangning & Yang, Zefeng & Chen, Xing & Wei, Wenfu, 2023. "Development of surrogate models for evaluating energy transfer quality of high-speed railway pantograph-catenary system using physics-based model and machine learning," Applied Energy, Elsevier, vol. 333(C).
  16. Manuel Jaramillo & Wilson Pavón & Lisbeth Jaramillo, 2024. "Adaptive Forecasting in Energy Consumption: A Bibliometric Analysis and Review," Data, MDPI, vol. 9(1), pages 1-23, January.
  17. Fu, Chun & Miller, Clayton, 2022. "Using Google Trends as a proxy for occupant behavior to predict building energy consumption," Applied Energy, Elsevier, vol. 310(C).
  18. Luo, Yongqiang & Yan, Tian & Zhang, Nan, 2020. "Study on dynamic thermal characteristics of thermoelectric radiant cooling panel system through a hybrid method," Energy, Elsevier, vol. 208(C).
  19. Zhou, Xinlei & Lin, Wenye & Kumar, Ritunesh & Cui, Ping & Ma, Zhenjun, 2022. "A data-driven strategy using long short term memory models and reinforcement learning to predict building electricity consumption," Applied Energy, Elsevier, vol. 306(PB).
  20. Chun-Wei Chen & Chun-Chang Li & Chen-Yu Lin, 2020. "Combine Clustering and Machine Learning for Enhancing the Efficiency of Energy Baseline of Chiller System," Energies, MDPI, vol. 13(17), pages 1-20, August.
  21. Saima Akhtar & Sulman Shahzad & Asad Zaheer & Hafiz Sami Ullah & Heybet Kilic & Radomir Gono & Michał Jasiński & Zbigniew Leonowicz, 2023. "Short-Term Load Forecasting Models: A Review of Challenges, Progress, and the Road Ahead," Energies, MDPI, vol. 16(10), pages 1-29, May.
  22. Ji, Ying & Chen, Xiang & Yang, Xinyu & Wang, Xinyue & Wang, Xiaoxia & Xie, Jingchao & Ju, Guidong, 2024. "Research on the framework and meteorological parameter optimization method of dynamic heating load prediction model for heat-exchange stations," Energy, Elsevier, vol. 309(C).
  23. Cui, Mianshan, 2022. "District heating load prediction algorithm based on bidirectional long short-term memory network model," Energy, Elsevier, vol. 254(PA).
  24. Ng, Rong Wang & Begam, Kasim Mumtaj & Rajkumar, Rajprasad Kumar & Wong, Yee Wan & Chong, Lee Wai, 2021. "An improved self-organizing incremental neural network model for short-term time-series load prediction," Applied Energy, Elsevier, vol. 292(C).
  25. Li, Guannan & Wu, Yubei & Yoon, Sungmin & Fang, Xi, 2024. "Comprehensive transferability assessment of short-term cross-building-energy prediction using deep adversarial network transfer learning," Energy, Elsevier, vol. 299(C).
  26. Tomaž Čegovnik & Andrej Dobrovoljc & Janez Povh & Matic Rogar & Pavel Tomšič, 2023. "Electricity consumption prediction using artificial intelligence," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(3), pages 833-851, September.
  27. Lian, Huihui & Ji, Ying & Niu, Menghan & Gu, Jiefan & Xie, Jingchao & Liu, Jiaping, 2025. "A hybrid load prediction method of office buildings based on physical simulation database and LightGBM algorithm," Applied Energy, Elsevier, vol. 377(PC).
  28. Lu, Yakai & Tian, Zhe & Zhou, Ruoyu & Liu, Wenjing, 2021. "A general transfer learning-based framework for thermal load prediction in regional energy system," Energy, Elsevier, vol. 217(C).
  29. Cao, Hui & Lin, Jiajing & Li, Nan, 2023. "Optimal control and energy efficiency evaluation of district ice storage system," Energy, Elsevier, vol. 276(C).
  30. Xiangxu Chen & Jinjin Mu & Zihan Shang & Xinnan Gao, 2025. "The Prediction of Civil Building Energy Consumption Using a Hybrid Model Combining Wavelet Transform with SVR and ELM: A Case Study of Jiangsu Province," Mathematics, MDPI, vol. 13(14), pages 1-20, July.
  31. Tan, Daniel & Suvarna, Manu & Shee Tan, Yee & Li, Jie & Wang, Xiaonan, 2021. "A three-step machine learning framework for energy profiling, activity state prediction and production estimation in smart process manufacturing," Applied Energy, Elsevier, vol. 291(C).
  32. Xuesong Tian & Yuping Zou & Xin Wang & Minglang Tseng & Hua Li & Huijuan Zhang, 2022. "Improving the Efficiency and Sustainability of Intelligent Electricity Inspection: IMFO-ELM Algorithm for Load Forecasting," Sustainability, MDPI, vol. 14(21), pages 1-19, October.
  33. Taboga, Vincent & Gehring, Clement & Cam, Mathieu Le & Dagdougui, Hanane & Bacon, Pierre-Luc, 2024. "Neural differential equations for temperature control in buildings under demand response programs," Applied Energy, Elsevier, vol. 368(C).
  34. Hu, Zehuan & Gao, Yuan & Sun, Luning & Mae, Masayuki & Imaizumi, Taiji, 2024. "Self-learning dynamic graph neural network with self-attention based on historical data and future data for multi-task multivariate residential air conditioning forecasting," Applied Energy, Elsevier, vol. 364(C).
  35. Luca Brunelli & Emiliano Borri & Anna Laura Pisello & Andrea Nicolini & Carles Mateu & Luisa F. Cabeza, 2024. "Thermal Energy Storage in Energy Communities: A Perspective Overview through a Bibliometric Analysis," Sustainability, MDPI, vol. 16(14), pages 1-27, July.
  36. Zhang, Chaobo & Li, Junyang & Zhao, Yang & Li, Tingting & Chen, Qi & Zhang, Xuejun & Qiu, Weikang, 2021. "Problem of data imbalance in building energy load prediction: Concept, influence, and solution," Applied Energy, Elsevier, vol. 297(C).
  37. Tan, Quanwei & Cao, Chunhua & Xue, Guijun & Xie, Wenju, 2024. "Short-term heating load forecasting model based on SVMD and improved informer," Energy, Elsevier, vol. 312(C).
  38. Lange, Jelto & Kaltschmitt, Martin, 2022. "Probabilistic day-ahead forecast of available thermal storage capacities in residential households," Applied Energy, Elsevier, vol. 306(PA).
  39. Liu, Chi & Xu, Zhezhuang & Yuan, Meng & Xie, Junwei & Yuan, Yazhou & Ma, Kai, 2025. "Building electrical load forecasting with occupancy data based on wireless sensing," Applied Energy, Elsevier, vol. 380(C).
  40. Chen, Minghao & Xie, Zhiyuan & Sun, Yi & Zheng, Shunlin, 2023. "The predictive management in campus heating system based on deep reinforcement learning and probabilistic heat demands forecasting," Applied Energy, Elsevier, vol. 350(C).
  41. Sheiati, Shohreh & Chen, Xiao, 2025. "Advances in computer vision-based structural health monitoring techniques for wind turbine blades," Renewable and Sustainable Energy Reviews, Elsevier, vol. 224(C).
  42. Yang, Yizhou & Duan, Qiuhua & Samadi, Forooza, 2025. "A systematic review of building energy performance forecasting approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 223(C).
  43. Jieyun Zheng & Linyao Zhang & Jinpeng Chen & Guilian Wu & Shiyuan Ni & Zhijian Hu & Changhong Weng & Zhi Chen, 2021. "Multiple-Load Forecasting for Integrated Energy System Based on Copula-DBiLSTM," Energies, MDPI, vol. 14(8), pages 1-14, April.
  44. Zhang, Xu & Sun, Yongjun & Gao, Dian-ce & Zou, Wenke & Fu, Jianping & Ma, Xiaowen, 2022. "Similarity-based grouping method for evaluation and optimization of dataset structure in machine-learning based short-term building cooling load prediction without measurable occupancy information," Applied Energy, Elsevier, vol. 327(C).
  45. Yue, Naihua & Caini, Mauro & Li, Lingling & Zhao, Yang & Li, Yu, 2023. "A comparison of six metamodeling techniques applied to multi building performance vectors prediction on gymnasiums under multiple climate conditions," Applied Energy, Elsevier, vol. 332(C).
  46. Peng Ye & Bin Yu & Wenhong Chen & Kan Liu & Longzhen Ye, 2022. "Rainfall-induced landslide susceptibility mapping using machine learning algorithms and comparison of their performance in Hilly area of Fujian Province, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 113(2), pages 965-995, September.
  47. Zhang, Lidong & Li, Jiao & Xu, Xiandong & Liu, Fengrui & Guo, Yuanjun & Yang, Zhile & Hu, Tianyu, 2023. "High spatial granularity residential heating load forecast based on Dendrite net model," Energy, Elsevier, vol. 269(C).
  48. Venkatraj, V. & Dixit, M.K., 2022. "Challenges in implementing data-driven approaches for building life cycle energy assessment: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
  49. William Mounter & Chris Ogwumike & Huda Dawood & Nashwan Dawood, 2021. "Machine Learning and Data Segmentation for Building Energy Use Prediction—A Comparative Study," Energies, MDPI, vol. 14(18), pages 1-42, September.
  50. Yu Zhang & Keyong Hu & Lei Lu & Qingqing Yang & Min Fang, 2025. "Seasonally Adaptive VMD-SSA-LSTM: A Hybrid Deep Learning Framework for High-Accuracy District Heating Load Forecasting," Mathematics, MDPI, vol. 13(15), pages 1-30, July.
  51. Wei, Ziqing & Zhang, Tingwei & Yue, Bao & Ding, Yunxiao & Xiao, Ran & Wang, Ruzhu & Zhai, Xiaoqiang, 2021. "Prediction of residential district heating load based on machine learning: A case study," Energy, Elsevier, vol. 231(C).
  52. 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).
  53. Christos D. Kaskouras & Konstantinos F. Krommydas & Ioannis Baltas & George P. Papaioannou & Georgios I. Papayiannis & Athanasios N. Yannacopoulos, 2024. "Assessing the Flexibility of Power Systems through Neural Networks: A Study of the Hellenic Transmission System," Sustainability, MDPI, vol. 16(14), pages 1-21, July.
  54. Li, Guannan & Zhan, Lei & Fang, Xi & Gao, Jiajia & Xu, Chengliang & He, Xin & Deng, Jiahui & Xiong, Chenglong, 2024. "Performance comparison on improved data-driven building energy prediction under data shortage scenarios in four perspectives: Data generation, incremental learning, transfer learning, and physics-info," Energy, Elsevier, vol. 312(C).
  55. Lin, Xiaojie & Mao, Yihui & Chen, Jiaying & Zhong, Wei, 2023. "Dynamic modeling and uncertainty quantification of district heating systems considering renewable energy access," Applied Energy, Elsevier, vol. 349(C).
  56. Xiaoyu Lin & Hang Yu & Meng Wang & Chaoen Li & Zi Wang & Yin Tang, 2021. "Electricity Consumption Forecast of High-Rise Office Buildings Based on the Long Short-Term Memory Method," Energies, MDPI, vol. 14(16), pages 1-21, August.
  57. Semmelmann, Leo & Hertel, Matthias & Kircher, Kevin J. & Mikut, Ralf & Hagenmeyer, Veit & Weinhardt, Christof, 2024. "The impact of heat pumps on day-ahead energy community load forecasting," Applied Energy, Elsevier, vol. 368(C).
  58. Ferdaus, Md Meftahul & Dam, Tanmoy & Anavatti, Sreenatha & Das, Sarobi, 2024. "Digital technologies for a net-zero energy future: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 202(C).
  59. Connor Scott & Mominul Ahsan & Alhussein Albarbar, 2021. "Machine Learning Based Vehicle to Grid Strategy for Improving the Energy Performance of Public Buildings," Sustainability, MDPI, vol. 13(7), pages 1-22, April.
  60. Dalia Mohammed Talat Ebrahim Ali & Violeta Motuzienė & Rasa Džiugaitė-Tumėnienė, 2024. "AI-Driven Innovations in Building Energy Management Systems: A Review of Potential Applications and Energy Savings," Energies, MDPI, vol. 17(17), pages 1-35, August.
  61. Li, Tian & Bie, Haipei & Lu, Yi & Sawyer, Azadeh Omidfar & Loftness, Vivian, 2024. "MEBA: AI-powered precise building monthly energy benchmarking approach," Applied Energy, Elsevier, vol. 359(C).
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  64. Yuwen You & Zhonghua Wang & Zhihao Liu & Chunmei Guo & Bin Yang, 2024. "Load Prediction of Regional Heat Exchange Station Based on Fuzzy Clustering Based on Fourier Distance and Convolutional Neural Network–Bidirectional Long Short-Term Memory Network," Energies, MDPI, vol. 17(16), pages 1-19, August.
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