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Simple model for prediction of loads in district-heating systems

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  1. Guixiang Xue & Yu Pan & Tao Lin & Jiancai Song & Chengying Qi & Zhipan Wang, 2019. "District Heating Load Prediction Algorithm Based on Feature Fusion LSTM Model," Energies, MDPI, vol. 12(11), pages 1-21, June.
  2. Ahmad, Tanveer & Chen, Huanxin, 2019. "Deep learning for multi-scale smart energy forecasting," Energy, Elsevier, vol. 175(C), pages 98-112.
  3. Gadd, Henrik & Werner, Sven, 2013. "Daily heat load variations in Swedish district heating systems," Applied Energy, Elsevier, vol. 106(C), pages 47-55.
  4. Madlener, Reinhard & Lohaus, Mathias, 2015. "Well Drainage Management in Abandoned Mines: Optimizing Energy Costs and Heat Use Under Uncertainty," FCN Working Papers 12/2015, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), revised Jul 2020.
  5. Guelpa, Elisa & Deputato, Stefania & Verda, Vittorio, 2018. "Thermal request optimization in district heating networks using a clustering approach," Applied Energy, Elsevier, vol. 228(C), pages 608-617.
  6. Rech, Sergio & Toffolo, Andrea & Lazzaretto, Andrea, 2012. "TSO-STO: A two-step approach to the optimal operation of heat storage systems with variable temperature tanks," Energy, Elsevier, vol. 45(1), pages 366-374.
  7. Keçebaş, Ali & Alkan, Mehmet Ali & Yabanova, İsmail & Yumurtacı, Mehmet, 2013. "Energetic and economic evaluations of geothermal district heating systems by using ANN," Energy Policy, Elsevier, vol. 56(C), pages 558-567.
  8. Chow, T. T. & Chan, Apple L. S. & Song, C. L., 2004. "Building-mix optimization in district cooling system implementation," Applied Energy, Elsevier, vol. 77(1), pages 1-13, January.
  9. Difs, Kristina & Bennstam, Marcus & Trygg, Louise & Nordenstam, Lena, 2010. "Energy conservation measures in buildings heated by district heating – A local energy system perspective," Energy, Elsevier, vol. 35(8), pages 3194-3203.
  10. Goia, Aldo & May, Caterina & Fusai, Gianluca, 2010. "Functional clustering and linear regression for peak load forecasting," International Journal of Forecasting, Elsevier, vol. 26(4), pages 700-711, October.
  11. Fu, Xueqian & Zhang, Xiurong, 2019. "Estimation of building energy consumption using weather information derived from photovoltaic power plants," Renewable Energy, Elsevier, vol. 130(C), pages 130-138.
  12. Koschwitz, D. & Frisch, J. & van Treeck, C., 2018. "Data-driven heating and cooling load predictions for non-residential buildings based on support vector machine regression and NARX Recurrent Neural Network: A comparative study on district scale," Energy, Elsevier, vol. 165(PA), pages 134-142.
  13. Eliasson, Lars & Eriksson, Anders & Mohtashami, Sima, 2017. "Analysis of factors affecting productivity and costs for a high-performance chip supply system," Applied Energy, Elsevier, vol. 185(P1), pages 497-505.
  14. 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).
  15. Popescu, Daniela & Ungureanu, Florina & Hernández-Guerrero, Abel, 2009. "Simulation models for the analysis of space heat consumption of buildings," Energy, Elsevier, vol. 34(10), pages 1447-1453.
  16. Dahl, Magnus & Brun, Adam & Andresen, Gorm B., 2017. "Decision rules for economic summer-shutdown of production units in large district heating systems," Applied Energy, Elsevier, vol. 208(C), pages 1128-1138.
  17. Potocnik, Primoz & Thaler, Marko & Govekar, Edvard & Grabec, Igor & Poredos, Alojz, 2007. "Forecasting risks of natural gas consumption in Slovenia," Energy Policy, Elsevier, vol. 35(8), pages 4271-4282, August.
  18. Tschopp, Daniel & Tian, Zhiyong & Berberich, Magdalena & Fan, Jianhua & Perers, Bengt & Furbo, Simon, 2020. "Large-scale solar thermal systems in leading countries: A review and comparative study of Denmark, China, Germany and Austria," Applied Energy, Elsevier, vol. 270(C).
  19. Piotr Pałka & Marcin Malec & Przemysław Kaszyński & Jacek Kamiński & Piotr Saługa, 2023. "District Heating System Optimisation: A Three-Phase Thermo-Hydraulic Linear Model," Energies, MDPI, vol. 16(8), pages 1-18, April.
  20. Guelpa, Elisa & Marincioni, Ludovica & Verda, Vittorio, 2019. "Towards 4th generation district heating: Prediction of building thermal load for optimal management," Energy, Elsevier, vol. 171(C), pages 510-522.
  21. 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.
  22. Talebi, Behrang & Haghighat, Fariborz & Tuohy, Paul & Mirzaei, Parham A., 2018. "Validation of a community district energy system model using field measured data," Energy, Elsevier, vol. 144(C), pages 694-706.
  23. Wang, Hai & Wang, Haiying & Haijian, Zhou & Zhu, Tong, 2017. "Optimization modeling for smart operation of multi-source district heating with distributed variable-speed pumps," Energy, Elsevier, vol. 138(C), pages 1247-1262.
  24. Bergsteinsson, Hjörleifur G. & Sørensen, Mikkel Lindstrøm & Møller, Jan Kloppenborg & Madsen, Henrik, 2023. "Heat load forecasting using adaptive spatial hierarchies," Applied Energy, Elsevier, vol. 350(C).
  25. 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).
  26. Abolfazl Rezaei & Bahador Samadzadegan & Hadise Rasoulian & Saeed Ranjbar & Soroush Samareh Abolhassani & Azin Sanei & Ursula Eicker, 2021. "A New Modeling Approach for Low-Carbon District Energy System Planning," Energies, MDPI, vol. 14(5), pages 1-22, March.
  27. Felten, Björn, 2020. "An integrated model of coupled heat and power sectors for large-scale energy system analyses," Applied Energy, Elsevier, vol. 266(C).
  28. Daniilidis, Alexandros & Scholten, Tjardo & Hooghiem, Joram & De Persis, Claudio & Herber, Rien, 2017. "Geochemical implications of production and storage control by coupling a direct-use geothermal system with heat networks," Applied Energy, Elsevier, vol. 204(C), pages 254-270.
  29. Vogler–Finck, P.J.C. & Bacher, P. & Madsen, H., 2017. "Online short-term forecast of greenhouse heat load using a weather forecast service," Applied Energy, Elsevier, vol. 205(C), pages 1298-1310.
  30. 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.
  31. Ferbar Tratar, Liljana & Strmčnik, Ervin, 2016. "The comparison of Holt–Winters method and Multiple regression method: A case study," Energy, Elsevier, vol. 109(C), pages 266-276.
  32. 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).
  33. 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.
  34. Jiménez Navarro, Juan Pablo & Cejudo López, José Manuel & Connolly, David, 2017. "The effect of feed-in-tariff supporting schemes on the viability of a district heating and cooling production system," Energy, Elsevier, vol. 134(C), pages 438-448.
  35. 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.
  36. Protić, Milan & Shamshirband, Shahaboddin & Anisi, Mohammad Hossein & Petković, Dalibor & Mitić, Dragan & Raos, Miomir & Arif, Muhammad & Alam, Khubaib Amjad, 2015. "Appraisal of soft computing methods for short term consumers' heat load prediction in district heating systems," Energy, Elsevier, vol. 82(C), pages 697-704.
  37. Mestekemper, Thomas & Kauermann, Göran & Smith, Michael S., 2013. "A comparison of periodic autoregressive and dynamic factor models in intraday energy demand forecasting," International Journal of Forecasting, Elsevier, vol. 29(1), pages 1-12.
  38. Danica Djurić Ilić, 2020. "Classification of Measures for Dealing with District Heating Load Variations—A Systematic Review," Energies, MDPI, vol. 14(1), pages 1-27, December.
  39. Pinson, P. & Nielsen, T.S. & Nielsen, H.Aa. & Poulsen, N.K. & Madsen, H., 2009. "Temperature prediction at critical points in district heating systems," European Journal of Operational Research, Elsevier, vol. 194(1), pages 163-176, April.
  40. 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.
  41. 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).
  42. Soheil Kavian & Mohsen Saffari Pour & Ali Hakkaki-Fard, 2019. "Optimized Design of the District Heating System by Considering the Techno-Economic Aspects and Future Weather Projection," Energies, MDPI, vol. 12(9), pages 1-30, May.
  43. 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).
  44. Lund, H. & Siupsinskas, G. & Martinaitis, V., 2005. "Implementation strategy for small CHP-plants in a competitive market: the case of Lithuania," Applied Energy, Elsevier, vol. 82(3), pages 214-227, November.
  45. Eriksson, Anders & Eliasson, Lars & Sikanen, Lauri & Hansson, Per-Anders & Jirjis, Raida, 2017. "Evaluation of delivery strategies for forest fuels applying a model for Weather-driven Analysis of Forest Fuel Systems (WAFFS)," Applied Energy, Elsevier, vol. 188(C), pages 420-430.
  46. Manfren, Massimiliano & Caputo, Paola & Costa, Gaia, 2011. "Paradigm shift in urban energy systems through distributed generation: Methods and models," Applied Energy, Elsevier, vol. 88(4), pages 1032-1048, April.
  47. Bergsteinsson, Hjörleifur G. & Møller, Jan Kloppenborg & Nystrup, Peter & Pálsson, Ólafur Pétur & Guericke, Daniela & Madsen, Henrik, 2021. "Heat load forecasting using adaptive temporal hierarchies," Applied Energy, Elsevier, vol. 292(C).
  48. Difs, Kristina & Danestig, Maria & Trygg, Louise, 2009. "Increased use of district heating in industrial processes - Impacts on heat load duration," Applied Energy, Elsevier, vol. 86(11), pages 2327-2334, November.
  49. Fragaki, Aikaterini & Andersen, Anders N. & Toke, David, 2008. "Exploration of economical sizing of gas engine and thermal store for combined heat and power plants in the UK," Energy, Elsevier, vol. 33(11), pages 1659-1670.
  50. F. Marta L. Di Lascio & Andrea Menapace & Maurizio Righetti, 2020. "Joint and conditional dependence modelling of peak district heating demand and outdoor temperature: a copula-based approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(2), pages 373-395, June.
  51. Hou, Zhijian & Lian, Zhiwei & Yao, Ye & Yuan, Xinjian, 2006. "Cooling-load prediction by the combination of rough set theory and an artificial neural-network based on data-fusion technique," Applied Energy, Elsevier, vol. 83(9), pages 1033-1046, September.
  52. Guo, Yabin & Wang, Jiangyu & Chen, Huanxin & Li, Guannan & Liu, Jiangyan & Xu, Chengliang & Huang, Ronggeng & Huang, Yao, 2018. "Machine learning-based thermal response time ahead energy demand prediction for building heating systems," Applied Energy, Elsevier, vol. 221(C), pages 16-27.
  53. Shamshirband, Shahaboddin & Petković, Dalibor & Enayatifar, Rasul & Hanan Abdullah, Abdul & Marković, Dušan & Lee, Malrey & Ahmad, Rodina, 2015. "Heat load prediction in district heating systems with adaptive neuro-fuzzy method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 760-767.
  54. Gajda, Janusz & Bartnicki, Grzegorz & Burnecki, Krzysztof, 2018. "Modeling of water usage by means of ARFIMA–GARCH processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 644-657.
  55. 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.
  56. 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).
  57. Jae-Ki Byun & Young-Don Choi & Jong-Keun Shin & Myung-Ho Park & Dong-Kurl Kwak, 2012. "Study on the Development of an Optimal Heat Supply Control Algorithm for Group Energy Apartment Buildings According to the Variation of Outdoor Air Temperature," Energies, MDPI, vol. 5(5), pages 1-19, May.
  58. Michael-Allan Millar & Neil M. Burnside & Zhibin Yu, 2019. "District Heating Challenges for the UK," Energies, MDPI, vol. 12(2), pages 1-21, January.
  59. Saletti, Costanza & Zimmerman, Nathan & Morini, Mirko & Kyprianidis, Konstantinos & Gambarotta, Agostino, 2021. "Enabling smart control by optimally managing the State of Charge of district heating networks," Applied Energy, Elsevier, vol. 283(C).
  60. Fang, Tingting & Lahdelma, Risto, 2016. "Evaluation of a multiple linear regression model and SARIMA model in forecasting heat demand for district heating system," Applied Energy, Elsevier, vol. 179(C), pages 544-552.
  61. Powell, Kody M. & Sriprasad, Akshay & Cole, Wesley J. & Edgar, Thomas F., 2014. "Heating, cooling, and electrical load forecasting for a large-scale district energy system," Energy, Elsevier, vol. 74(C), pages 877-885.
  62. 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).
  63. Wang, Zhe & Hong, Tianzhen & Piette, Mary Ann, 2019. "Data fusion in predicting internal heat gains for office buildings through a deep learning approach," Applied Energy, Elsevier, vol. 240(C), pages 386-398.
  64. Ferrari, Simone & Zagarella, Federica & Caputo, Paola & D'Amico, Antonino, 2019. "Results of a literature review on methods for estimating buildings energy demand at district level," Energy, Elsevier, vol. 175(C), pages 1130-1137.
  65. Chendong Wang & Lihong Zheng & Jianjuan Yuan & Ke Huang & Zhihua Zhou, 2022. "Building Heat Demand Prediction Based on Reinforcement Learning for Thermal Comfort Management," Energies, MDPI, vol. 15(21), pages 1-20, October.
  66. Short, Michael & Crosbie, Tracey & Dawood, Muneeb & Dawood, Nashwan, 2017. "Load forecasting and dispatch optimisation for decentralised co-generation plant with dual energy storage," Applied Energy, Elsevier, vol. 186(P3), pages 304-320.
  67. Cai, Hanmin & Ziras, Charalampos & You, Shi & Li, Rongling & Honoré, Kristian & Bindner, Henrik W., 2018. "Demand side management in urban district heating networks," Applied Energy, Elsevier, vol. 230(C), pages 506-518.
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