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Multi-step ahead forecasting of heat load in district heating systems using machine learning algorithms

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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. Liu, Xuefeng & Huang, Bin & Zheng, Yulan, 2023. "Control strategy for dynamic operation of multiple chillers under random load constraints," Energy, Elsevier, vol. 270(C).
  3. Zhang, Yunfei & Zhou, Zhihua & Liu, Junwei & Yuan, Jianjuan, 2022. "Data augmentation for improving heating load prediction of heating substation based on TimeGAN," Energy, Elsevier, vol. 260(C).
  4. 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.
  5. Nikolaos Kolokas & Dimosthenis Ioannidis & Dimitrios Tzovaras, 2021. "Multi-Step Energy Demand and Generation Forecasting with Confidence Used for Specification-Free Aggregate Demand Optimization," Energies, MDPI, vol. 14(11), pages 1-36, May.
  6. Lumbreras, Mikel & Garay-Martinez, Roberto & Arregi, Beñat & Martin-Escudero, Koldobika & Diarce, Gonzalo & Raud, Margus & Hagu, Indrek, 2022. "Data driven model for heat load prediction in buildings connected to District Heating by using smart heat meters," Energy, Elsevier, vol. 239(PD).
  7. Huang, Hai-chao & Chen, Jing-ya & Shi, Bao-cun & He, Hong-di, 2023. "Multi-step forecasting of short-term traffic flow based on Intrinsic Pattern Transform," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 621(C).
  8. Lai, Changzhi & Wang, Yu & Fan, Kai & Cai, Qilin & Ye, Qing & Pang, Haoqiang & Wu, Xi, 2022. "An improved forecasting model of short-term electric load of papermaking enterprises for production line optimization," Energy, Elsevier, vol. 245(C).
  9. Sun, Chunhua & Yuan, Lingyu & Cao, Shanshan & Xia, Guoqiang & Liu, Yanan & Wu, Xiangdong, 2023. "Identifying supply-demand mismatches in district heating system based on association rule mining," Energy, Elsevier, vol. 280(C).
  10. Liu, Zhikai & Zhang, Huang & Wang, Yaran & Fan, Xianwang & You, Shijun & Li, Ang, 2023. "Data-driven predictive model for feedback control of supply temperature in buildings with radiator heating system," Energy, Elsevier, vol. 280(C).
  11. 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).
  12. Huang, Ke & Yuan, Jianjuan & Zhou, Zhihua & Zheng, Xuejing, 2022. "Analysis and evaluation of heat source data of large-scale heating system based on descriptive data mining techniques," Energy, Elsevier, vol. 251(C).
  13. Yuan, Jianjuan & Zhou, Zhihua & Tang, Huajie & Wang, Chendong & Lu, Shilei & Han, Zhao & Zhang, Ji & Sheng, Ying, 2020. "Identification heat user behavior for improving the accuracy of heating load prediction model based on wireless on-off control system," Energy, Elsevier, vol. 199(C).
  14. Roozbeh Sadeghian Broujeny & Safa Ben Ayed & Mouadh Matalah, 2023. "Energy Consumption Forecasting in a University Office by Artificial Intelligence Techniques: An Analysis of the Exogenous Data Effect on the Modeling," Energies, MDPI, vol. 16(10), pages 1-21, May.
  15. Lange, Jelto & Kaltschmitt, Martin, 2022. "Probabilistic day-ahead forecast of available thermal storage capacities in residential households," Applied Energy, Elsevier, vol. 306(PA).
  16. Zhong, Wei & Feng, Encheng & Lin, Xiaojie & Xie, Jinfang, 2022. "Research on data-driven operation control of secondary loop of district heating system," Energy, Elsevier, vol. 239(PB).
  17. Runge, Jason & Saloux, Etienne, 2023. "A comparison of prediction and forecasting artificial intelligence models to estimate the future energy demand in a district heating system," Energy, Elsevier, vol. 269(C).
  18. Sarah Hadri & Mehdi Najib & Mohamed Bakhouya & Youssef Fakhri & Mohamed El Arroussi, 2021. "Performance Evaluation of Forecasting Strategies for Electricity Consumption in Buildings," Energies, MDPI, vol. 14(18), pages 1-17, September.
  19. 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).
  20. Gong, Mingju & Zhao, Yin & Sun, Jiawang & Han, Cuitian & Sun, Guannan & Yan, Bo, 2022. "Load forecasting of district heating system based on Informer," Energy, Elsevier, vol. 253(C).
  21. Huang, Ke & Lu, Shilei & Han, Zhao & Yuan, Jianjuan, 2023. "Research on heat consumption detection, restoration and prediction methods for discontinuous heating substation," Energy, Elsevier, vol. 266(C).
  22. Wang, Bin & Wang, Jun, 2020. "Energy futures and spots prices forecasting by hybrid SW-GRU with EMD and error evaluation," Energy Economics, Elsevier, vol. 90(C).
  23. Chen, Si-Yuan & Xue, Meng-Tian & Wang, Zhao-Hua & Tian, Xin & Zhang, Bin, 2022. "Exploring pathways of phasing out clean heating subsidies for rural residential buildings in China," Energy Economics, Elsevier, vol. 116(C).
  24. Finkenrath, Matthias & Faber, Till & Behrens, Fabian & Leiprecht, Stefan, 2022. "Holistic modelling and optimisation of thermal load forecasting, heat generation and plant dispatch for a district heating network," Energy, Elsevier, vol. 250(C).
  25. Angelina D. Bintoudi & Lampros Zyglakis & Apostolos C. Tsolakis & Paschalis A. Gkaidatzis & Athanasios Tryferidis & Dimosthenis Ioannidis & Dimitrios Tzovaras, 2021. "OptiMEMS: An Adaptive Lightweight Optimal Microgrid Energy Management System Based on the Novel Virtual Distributed Energy Resources in Real-Life Demonstration," Energies, MDPI, vol. 14(10), pages 1-19, May.
  26. Yuan, Jianjuan & Huang, Ke & Han, Zhao & Wang, Chendong & Lu, Shilei & Zhou, Zhihua, 2022. "Evaluation of the operation data for improving the prediction accuracy of heating parameters in heating substation," Energy, Elsevier, vol. 238(PB).
  27. Ahmad, Tanveer & Zhang, Hongcai, 2020. "Novel deep supervised ML models with feature selection approach for large-scale utilities and buildings short and medium-term load requirement forecasts," Energy, Elsevier, vol. 209(C).
  28. Yuan, Jianjuan & Huang, Ke & Lu, Shilei & Zhang, Ji & Han, Zhao & Zhou, Zhihua, 2022. "Analysis of influencing factors on heat consumption of large residential buildings with different occupancy rates-Tianjin case study," Energy, Elsevier, vol. 238(PC).
  29. Zhao, Yin & Gong, Mingju & Sun, Jiawang & Han, Cuitian & Jing, Lei & Li, Bo & Zhao, Zhixuan, 2023. "A new hybrid optimization prediction strategy based on SH-Informer for district heating system," Energy, Elsevier, vol. 282(C).
  30. Zhang, Qiang & Tian, Zhe & Ma, Zhijun & Li, Genyan & Lu, Yakai & Niu, Jide, 2020. "Development of the heating load prediction model for the residential building of district heating based on model calibration," Energy, Elsevier, vol. 205(C).
  31. Sun, Chunhua & Liu, Yanan & Gao, Xiaoyu & Wang, Jinda & Yang, Lan & Qi, Chengyong, 2022. "Research on control strategy integrated with characteristics of user's energy-saving behavior of district heating system," Energy, Elsevier, vol. 245(C).
  32. Kristensen, Martin Heine & Hedegaard, Rasmus Elbæk & Petersen, Steffen, 2020. "Long-term forecasting of hourly district heating loads in urban areas using hierarchical archetype modeling," Energy, Elsevier, vol. 201(C).
  33. Ahmad, Tanveer & Huanxin, Chen & Zhang, Dongdong & Zhang, Hongcai, 2020. "Smart energy forecasting strategy with four machine learning models for climate-sensitive and non-climate sensitive conditions," Energy, Elsevier, vol. 198(C).
  34. Wang, Yanmin & Li, Zhiwei & Liu, Junjie & Pei, Mingzhe & Zhao, Yan & Lu, Xuan, 2023. "Data-driven analysis and prediction of indoor characteristic temperature in district heating systems," Energy, Elsevier, vol. 282(C).
  35. 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.
  36. Chung, Won Hee & Gu, Yeong Hyeon & Yoo, Seong Joon, 2022. "District heater load forecasting based on machine learning and parallel CNN-LSTM attention," Energy, Elsevier, vol. 246(C).
  37. Yuan, Jianjuan & Zhou, Zhihua & Huang, Ke & Han, Zhao & Wang, Chendong & Lu, Shilei, 2021. "Analysis and evaluation of the operation data for achieving an on-demand heating consumption prediction model of district heating substation," Energy, Elsevier, vol. 214(C).
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