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Evaluation of a multiple linear regression model and SARIMA model in forecasting heat demand for district heating system

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  1. Elamin, Niematallah & Fukushige, Mototsugu, 2018. "Modeling and forecasting hourly electricity demand by SARIMAX with interactions," Energy, Elsevier, vol. 165(PB), pages 257-268.
  2. Samer Chaaraoui & Matthias Bebber & Stefanie Meilinger & Silvan Rummeny & Thorsten Schneiders & Windmanagda Sawadogo & Harald Kunstmann, 2021. "Day-Ahead Electric Load Forecast for a Ghanaian Health Facility Using Different Algorithms," Energies, MDPI, vol. 14(2), pages 1-22, January.
  3. 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).
  4. Wang, Ran & Lu, Shilei & Feng, Wei, 2020. "A novel improved model for building energy consumption prediction based on model integration," Applied Energy, Elsevier, vol. 262(C).
  5. Töppel, Jannick & Tränkler, Timm, 2019. "Modeling energy efficiency insurances and energy performance contracts for a quantitative comparison of risk mitigation potential," Energy Economics, Elsevier, vol. 80(C), pages 842-859.
  6. Liu, Xiaolei & Lin, Zi & Feng, Ziming, 2021. "Short-term offshore wind speed forecast by seasonal ARIMA - A comparison against GRU and LSTM," Energy, Elsevier, vol. 227(C).
  7. Bertone, Edoardo & Sahin, Oz & Stewart, Rodney A. & Zou, Patrick X.W. & Alam, Morshed & Hampson, Keith & Blair, Evan, 2018. "Role of financial mechanisms for accelerating the rate of water and energy efficiency retrofits in Australian public buildings: Hybrid Bayesian Network and System Dynamics modelling approach," Applied Energy, Elsevier, vol. 210(C), pages 409-419.
  8. Aunedi, Marko & Pantaleo, Antonio Marco & Kuriyan, Kamal & Strbac, Goran & Shah, Nilay, 2020. "Modelling of national and local interactions between heat and electricity networks in low-carbon energy systems," Applied Energy, Elsevier, vol. 276(C).
  9. Pengwei Su & Xue Tian & Yan Wang & Shuai Deng & Jun Zhao & Qingsong An & Yongzhen Wang, 2017. "Recent Trends in Load Forecasting Technology for the Operation Optimization of Distributed Energy System," Energies, MDPI, vol. 10(9), pages 1-13, August.
  10. Zhang, Xiang & Rasmussen, Christoffer & Saelens, Dirk & Roels, Staf, 2022. "Time-dependent solar aperture estimation of a building: Comparing grey-box and white-box approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
  11. Gu, Jihao & Wang, Jin & Qi, Chengying & Min, Chunhua & Sundén, Bengt, 2018. "Medium-term heat load prediction for an existing residential building based on a wireless on-off control system," Energy, Elsevier, vol. 152(C), pages 709-718.
  12. Lemos-Vinasco, Julian & Bacher, Peder & Møller, Jan Kloppenborg, 2021. "Probabilistic load forecasting considering temporal correlation: Online models for the prediction of households’ electrical load," Applied Energy, Elsevier, vol. 303(C).
  13. Maciej Bujalski & Paweł Madejski, 2021. "Forecasting of Heat Production in Combined Heat and Power Plants Using Generalized Additive Models," Energies, MDPI, vol. 14(8), pages 1-15, April.
  14. Kaneko, Naoya & Okazawa, Kazuki & Zhao, Dafang & Nishikawa, Hiroki & Taniguchi, Ittetsu & Murayama, Hiroyuki & Yura, Yoshinori & Okamoto, Masakazu & Catthoor, Francky & Onoye, Takao, 2024. "Non-intrusive thermal load disaggregation and forecasting for effective HVAC systems," Applied Energy, Elsevier, vol. 367(C).
  15. Chang, Chih-Hao & Chen, Zih-Bing & Huang, Shih-Feng, 2022. "Forecasting of high-resolution electricity consumption with stochastic climatic covariates via a functional time series approach," Applied Energy, Elsevier, vol. 309(C).
  16. Serkan Ozdemir & Sevgi Ozkan Yildirim, 2023. "Prediction of Water Level in Lakes by RNN-Based Deep Learning Algorithms to Preserve Sustainability in Changing Climate and Relationship to Microcystin," Sustainability, MDPI, vol. 15(22), pages 1-25, November.
  17. Jiang, Ping & Li, Ranran & Liu, Ningning & Gao, Yuyang, 2020. "A novel composite electricity demand forecasting framework by data processing and optimized support vector machine," Applied Energy, Elsevier, vol. 260(C).
  18. Yue Yuan & Jisoo Shim & Seungkeon Lee & Doosam Song & Joowook Kim, 2020. "Prediction for Overheating Risk Based on Deep Learning in a Zero Energy Building," Sustainability, MDPI, vol. 12(21), pages 1-20, October.
  19. Donghun Lee & Seok Mann Yoon & Jaeseung Lee & Kwanho Kim & Sang Hwa Song, 2020. "Applying Deep Learning to the Heat Production Planning Problem in a District Heating System," Energies, MDPI, vol. 13(24), pages 1-17, December.
  20. Lotta Kannari & Jussi Kiljander & Kalevi Piira & Jouko Piippo & Pekka Koponen, 2021. "Building Heat Demand Forecasting by Training a Common Machine Learning Model with Physics-Based Simulator," Forecasting, MDPI, vol. 3(2), pages 1-13, April.
  21. Xue, Puning & Jiang, Yi & Zhou, Zhigang & Chen, Xin & Fang, Xiumu & Liu, Jing, 2019. "Multi-step ahead forecasting of heat load in district heating systems using machine learning algorithms," Energy, Elsevier, vol. 188(C).
  22. Wanxing Sheng & Keyan Liu & Dongli Jia & Shuo Chen & Rongheng Lin, 2022. "Short-Term Load Forecasting Algorithm Based on LST-TCN in Power Distribution Network," Energies, MDPI, vol. 15(15), pages 1-13, August.
  23. Vanessa Zawodnik & Florian Christian Schwaiger & Christoph Sorger & Thomas Kienberger, 2024. "Tackling Uncertainty: Forecasting the Energy Consumption and Demand of an Electric Arc Furnace with Limited Knowledge on Process Parameters," Energies, MDPI, vol. 17(6), pages 1-19, March.
  24. Ahlrichs, Jakob & Rockstuhl, Sebastian & Tränkler, Timm & Wenninger, Simon, 2020. "The impact of political instruments on building energy retrofits: A risk-integrated thermal Energy Hub approach," Energy Policy, Elsevier, vol. 147(C).
  25. Nigitz, Thomas & Gölles, Markus, 2019. "A generally applicable, simple and adaptive forecasting method for the short-term heat load of consumers," Applied Energy, Elsevier, vol. 241(C), pages 73-81.
  26. 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).
  27. Zihao Li & Daniel Friedrich & Gareth P. Harrison, 2020. "Demand Forecasting for a Mixed-Use Building Using Agent-Schedule Information with a Data-Driven Model," Energies, MDPI, vol. 13(4), pages 1-20, February.
  28. Xue, Guixiang & Qi, Chengying & Li, Han & Kong, Xiangfei & Song, Jiancai, 2020. "Heating load prediction based on attention long short term memory: A case study of Xingtai," Energy, Elsevier, vol. 203(C).
  29. Dahl, Magnus & Brun, Adam & Andresen, Gorm B., 2017. "Using ensemble weather predictions in district heating operation and load forecasting," Applied Energy, Elsevier, vol. 193(C), pages 455-465.
  30. Noorollahi, Younes & Golshanfard, Aminabbas & Ansaripour, Shiva & Khaledi, Arian & Shadi, Mehdi, 2021. "Solar energy for sustainable heating and cooling energy system planning in arid climates," Energy, Elsevier, vol. 218(C).
  31. Ma, Weiwu & Fang, Song & Liu, Gang & Zhou, Ruoyu, 2017. "Modeling of district load forecasting for distributed energy system," Applied Energy, Elsevier, vol. 204(C), pages 181-205.
  32. Lei, Lei & Shao, Suola & Liang, Lixia, 2024. "An evolutionary deep learning model based on EWKM, random forest algorithm, SSA and BiLSTM for building energy consumption prediction," Energy, Elsevier, vol. 288(C).
  33. Ana Lagos & Joaquín E. Caicedo & Gustavo Coria & Andrés Romero Quete & Maximiliano Martínez & Gastón Suvire & Jesús Riquelme, 2022. "State-of-the-Art Using Bibliometric Analysis of Wind-Speed and -Power Forecasting Methods Applied in Power Systems," Energies, MDPI, vol. 15(18), pages 1-40, September.
  34. 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).
  35. Li, Yiyan & Zhang, Si & Hu, Rongxing & Lu, Ning, 2021. "A meta-learning based distribution system load forecasting model selection framework," Applied Energy, Elsevier, vol. 294(C).
  36. Mengting Jiang & Camilo Rindt & David M. J. Smeulders, 2022. "Optimal Planning of Future District Heating Systems—A Review," Energies, MDPI, vol. 15(19), pages 1-38, September.
  37. Wang, Chendong & Yuan, Jianjuan & Zhang, Ji & Deng, Na & Zhou, Zhihua & Gao, Feng, 2020. "Multi-criteria comprehensive study on predictive algorithm of heating energy consumption of district heating station based on timeseries processing," Energy, Elsevier, vol. 202(C).
  38. Magnus Dahl & Adam Brun & Oliver S. Kirsebom & Gorm B. Andresen, 2018. "Improving Short-Term Heat Load Forecasts with Calendar and Holiday Data," Energies, MDPI, vol. 11(7), pages 1-16, June.
  39. 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).
  40. Maciej Slowik & Wieslaw Urban, 2022. "Machine Learning Short-Term Energy Consumption Forecasting for Microgrids in a Manufacturing Plant," Energies, MDPI, vol. 15(9), pages 1-16, May.
  41. Abdus Samad Azad & Rajalingam Sokkalingam & Hanita Daud & Sajal Kumar Adhikary & Hifsa Khurshid & Siti Nur Athirah Mazlan & Muhammad Babar Ali Rabbani, 2022. "Water Level Prediction through Hybrid SARIMA and ANN Models Based on Time Series Analysis: Red Hills Reservoir Case Study," Sustainability, MDPI, vol. 14(3), pages 1-20, February.
  42. 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).
  43. Peng Lu & Lin Ye & Bohao Sun & Cihang Zhang & Yongning Zhao & Jingzhu Teng, 2018. "A New Hybrid Prediction Method of Ultra-Short-Term Wind Power Forecasting Based on EEMD-PE and LSSVM Optimized by the GSA," Energies, MDPI, vol. 11(4), pages 1-23, March.
  44. 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).
  45. 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).
  46. Wang, Lei & Wang, Xinyu & Zhao, Zhongchao, 2024. "Mid-term electricity demand forecasting using improved multi-mode reconstruction and particle swarm-enhanced support vector regression," Energy, Elsevier, vol. 304(C).
  47. Abdollahi, Elnaz & Lahdelma, Risto, 2020. "Decomposition method for optimizing long-term multi-area energy production with heat and power storages," Applied Energy, Elsevier, vol. 260(C).
  48. M. K. Islam & N. M. S. Hassan & M. G. Rasul & Kianoush Emami & Ashfaque Ahmed Chowdhury, 2023. "Forecasting of Solar and Wind Resources for Power Generation," Energies, MDPI, vol. 16(17), pages 1-23, August.
  49. Wang, Shaomin & Wang, Shouxiang & Chen, Haiwen & Gu, Qiang, 2020. "Multi-energy load forecasting for regional integrated energy systems considering temporal dynamic and coupling characteristics," Energy, Elsevier, vol. 195(C).
  50. Xue, Puning & Zhou, Zhigang & Fang, Xiumu & Chen, Xin & Liu, Lin & Liu, Yaowen & Liu, Jing, 2017. "Fault detection and operation optimization in district heating substations based on data mining techniques," Applied Energy, Elsevier, vol. 205(C), pages 926-940.
  51. Gholami, M. & Barbaresi, A. & Torreggiani, D. & Tassinari, P., 2020. "Upscaling of spatial energy planning, phases, methods, and techniques: A systematic review through meta-analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
  52. Triebs, Merlin Sebastian & Tsatsaronis, George, 2022. "From heat demand to heat supply: How to obtain more accurate feed-in time series for district heating systems," Applied Energy, Elsevier, vol. 311(C).
  53. Arabzadeh, Vahid & Miettinen, Panu & Kotilainen, Titta & Herranen, Pasi & Karakoc, Alp & Kummu, Matti & Rautkari, Lauri, 2023. "Urban vertical farming with a large wind power share and optimised electricity costs," Applied Energy, Elsevier, vol. 331(C).
  54. Vahid Arabzadeh & Peter D. Lund, 2020. "Effect of Heat Demand on Integration of Urban Large-Scale Renewable Schemes—Case of Helsinki City (60 °N)," Energies, MDPI, vol. 13(9), pages 1-17, May.
  55. Lange, Jelto & Kaltschmitt, Martin, 2022. "Probabilistic day-ahead forecast of available thermal storage capacities in residential households," Applied Energy, Elsevier, vol. 306(PA).
  56. Vu, D.H. & Muttaqi, K.M. & Agalgaonkar, A.P. & Bouzerdoum, A., 2017. "Short-term electricity demand forecasting using autoregressive based time varying model incorporating representative data adjustment," Applied Energy, Elsevier, vol. 205(C), pages 790-801.
  57. Eltoukhy, Abdelrahman E.E. & Wang, Z.X. & Chan, Felix T.S. & Fu, X., 2019. "Data analytics in managing aircraft routing and maintenance staffing with price competition by a Stackelberg-Nash game model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 143-168.
  58. Yuan, Jianjuan & Huang, Ke & Han, Zhao & Zhou, Zhihua & Lu, Shilei, 2021. "A new feedback predictive model for improving the operation efficiency of heating station based on indoor temperature," Energy, Elsevier, vol. 222(C).
  59. Jianguo Zhou & Xiaolei Xu & Xuejing Huo & Yushuo Li, 2019. "Forecasting Models for Wind Power Using Extreme-Point Symmetric Mode Decomposition and Artificial Neural Networks," Sustainability, MDPI, vol. 11(3), pages 1-23, January.
  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. Ifaei, Pouya & Nazari-Heris, Morteza & Tayerani Charmchi, Amir Saman & Asadi, Somayeh & Yoo, ChangKyoo, 2023. "Sustainable energies and machine learning: An organized review of recent applications and challenges," Energy, Elsevier, vol. 266(C).
  62. Huang, Yaohui & Zhao, Yuan & Wang, Zhijin & Liu, Xiufeng & Fu, Yonggang, 2024. "Sparse dynamic graph learning for district heat load forecasting," Applied Energy, Elsevier, vol. 371(C).
  63. 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).
  64. Rafati, Amir & Joorabian, Mahmood & Mashhour, Elaheh, 2020. "An efficient hour-ahead electrical load forecasting method based on innovative features," Energy, Elsevier, vol. 201(C).
  65. Kurek, Teresa & Bielecki, Artur & Świrski, Konrad & Wojdan, Konrad & Guzek, Michał & Białek, Jakub & Brzozowski, Rafał & Serafin, Rafał, 2021. "Heat demand forecasting algorithm for a Warsaw district heating network," Energy, Elsevier, vol. 217(C).
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