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Modeling of district load forecasting for distributed energy system

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  1. Ma, Weiwu & Xue, Xinpei & Liu, Gang, 2018. "Techno-economic evaluation for hybrid renewable energy system: Application and merits," Energy, Elsevier, vol. 159(C), pages 385-409.
  2. Andrea Menapace & Simone Santopietro & Rudy Gargano & Maurizio Righetti, 2021. "Stochastic Generation of District Heat Load," Energies, MDPI, vol. 14(17), pages 1-17, August.
  3. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
  4. Guo, Yurun & Wang, Shugang & Wang, Jihong & Zhang, Tengfei & Ma, Zhenjun & Jiang, Shuang, 2024. "Key district heating technologies for building energy flexibility: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
  5. Akeratana Noppakant & Boonyang Plangklang, 2022. "Improving Energy Management through Demand Response Programs for Low-Rise University Buildings," Sustainability, MDPI, vol. 14(21), pages 1-15, October.
  6. Qian, Fanyue & Gao, Weijun & Yang, Yongwen & Yu, Dan, 2020. "Potential analysis of the transfer learning model in short and medium-term forecasting of building HVAC energy consumption," Energy, Elsevier, vol. 193(C).
  7. Wang, Yongli & Wang, Huan & Meng, Xiao & Dong, Huanran & Chen, Xin & Xiang, Hao & Xing, Juntai, 2023. "Considering the dual endogenous-exogenous uncertainty integrated energy multiple load short-term forecast," Energy, Elsevier, vol. 285(C).
  8. Kim, Eui-Jong & He, Xi & Roux, Jean-Jacques & Johannes, Kévyn & Kuznik, Frédéric, 2019. "Fast and accurate district heating and cooling energy demand and load calculations using reduced-order modelling," Applied Energy, Elsevier, vol. 238(C), pages 963-971.
  9. Marzullo, Thibault & Keane, Marcus M. & Geron, Marco & Monaghan, Rory F.D., 2019. "A computational toolchain for the automatic generation of multiple Reduced-Order Models from CFD simulations," Energy, Elsevier, vol. 180(C), pages 511-519.
  10. Liu, Tianhao & Tian, Jun & Zhu, Hongyu & Goh, Hui Hwang & Liu, Hui & Wu, Thomas & Zhang, Dongdong, 2023. "Key technologies and developments of multi-energy system: Three-layer framework, modelling and optimisation," Energy, Elsevier, vol. 277(C).
  11. Guelpa, Elisa & Marincioni, Ludovica & Capone, Martina & Deputato, Stefania & Verda, Vittorio, 2019. "Thermal load prediction in district heating systems," Energy, Elsevier, vol. 176(C), pages 693-703.
  12. 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).
  13. 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.
  14. Meibodi, Saleh S. & Loveridge, Fleur, 2022. "The future role of energy geostructures in fifth generation district heating and cooling networks," Energy, Elsevier, vol. 240(C).
  15. 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.
  16. Selva Calixto & Marco Cozzini & Roberto Fedrizzi & Giampaolo Manzolini, 2024. "A New Method for the Techno-Economic Analysis and the Identification of Expansion Strategies of Neutral-Temperature District Heating and Cooling Systems," Energies, MDPI, vol. 17(9), pages 1-20, April.
  17. Palacios-Garcia, E.J. & Moreno-Munoz, A. & Santiago, I. & Flores-Arias, J.M. & Bellido-Outeirino, F.J. & Moreno-Garcia, I.M., 2018. "A stochastic modelling and simulation approach to heating and cooling electricity consumption in the residential sector," Energy, Elsevier, vol. 144(C), pages 1080-1091.
  18. Ahmad, Tanveer & Chen, Huanxin, 2019. "Deep learning for multi-scale smart energy forecasting," Energy, Elsevier, vol. 175(C), pages 98-112.
  19. Selva Calixto & Marco Cozzini & Giampaolo Manzolini, 2021. "Modelling of an Existing Neutral Temperature District Heating Network: Detailed and Approximate Approaches," Energies, MDPI, vol. 14(2), pages 1-16, January.
  20. Andrés M. Alonso & Francisco J. Nogales & Carlos Ruiz, 2020. "A Single Scalable LSTM Model for Short-Term Forecasting of Massive Electricity Time Series," Energies, MDPI, vol. 13(20), pages 1-19, October.
  21. Amin, Amin & Mourshed, Monjur, 2024. "Community stochastic domestic electricity forecasting," Applied Energy, Elsevier, vol. 355(C).
  22. 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).
  23. Yang, Xining & Hu, Mingming & Heeren, Niko & Zhang, Chunbo & Verhagen, Teun & Tukker, Arnold & Steubing, Bernhard, 2020. "A combined GIS-archetype approach to model residential space heating energy: A case study for the Netherlands including validation," Applied Energy, Elsevier, vol. 280(C).
  24. Huang, Yunyou & Zhan, Jianfeng & Luo, Chunjie & Wang, Lei & Wang, Nana & Zheng, Daoyi & Fan, Fanda & Ren, Rui, 2019. "An electricity consumption model for synthesizing scalable electricity load curves," Energy, Elsevier, vol. 169(C), pages 674-683.
  25. Yongming Zhang & Zhe Yan & Li Li & Jiawei Yao, 2018. "A Hybrid Building Power Distribution System in Consideration of Supply and Demand-Side: A Short Overview and a Case Study," Energies, MDPI, vol. 11(11), pages 1-19, November.
  26. Adam Maryniak & Marian Banaś & Piotr Michalak & Jakub Szymiczek, 2024. "Forecasting of Daily Heat Production in a District Heating Plant Using a Neural Network," Energies, MDPI, vol. 17(17), pages 1-19, September.
  27. Izanloo, Milad & Noorollahi, Younes & Aslani, Alireza, 2021. "Future energy planning to maximize renewable energy share for the south Caspian Sea climate," Renewable Energy, Elsevier, vol. 175(C), pages 660-675.
  28. Mei, Fei & Zhang, Jiatang & Lu, Jixiang & Lu, Jinjun & Jiang, Yuhan & Gu, Jiaqi & Yu, Kun & Gan, Lei, 2021. "Stochastic optimal operation model for a distributed integrated energy system based on multiple-scenario simulations," Energy, Elsevier, vol. 219(C).
  29. Ma, Weiwu & Fang, Song & Liu, Gang, 2017. "Hybrid optimization method and seasonal operation strategy for distributed energy system integrating CCHP, photovoltaic and ground source heat pump," Energy, Elsevier, vol. 141(C), pages 1439-1455.
  30. Bracco, Stefano & Delfino, Federico & Ferro, Giulio & Pagnini, Luisa & Robba, Michela & Rossi, Mansueto, 2018. "Energy planning of sustainable districts: Towards the exploitation of small size intermittent renewables in urban areas," Applied Energy, Elsevier, vol. 228(C), pages 2288-2297.
  31. Pagnini, Luisa & Bracco, Stefano & Delfino, Federico & de-Simón-Martín, Miguel, 2024. "Levelized cost of electricity in renewable energy communities: Uncertainty propagation analysis," Applied Energy, Elsevier, vol. 366(C).
  32. Huang, Tian-en & Guo, Qinglai & Sun, Hongbin & Tan, Chin-Woo & Hu, Tianyu, 2019. "A deep spatial-temporal data-driven approach considering microclimates for power system security assessment," Applied Energy, Elsevier, vol. 237(C), pages 36-48.
  33. Shengzeng Li & Yiwen Zhong & Jiaxiang Lin, 2022. "AWS-DAIE: Incremental Ensemble Short-Term Electricity Load Forecasting Based on Sample Domain Adaptation," Sustainability, MDPI, vol. 14(21), pages 1-16, October.
  34. 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).
  35. Li, Guannan & Li, Fan & Ahmad, Tanveer & Liu, Jiangyan & Li, Tao & Fang, Xi & Wu, Yubei, 2022. "Performance evaluation of sequence-to-sequence-Attention model for short-term multi-step ahead building energy predictions," Energy, Elsevier, vol. 259(C).
  36. Ye, Chengjin & Ding, Yi & Song, Yonghua & Lin, Zhenzhi & Wang, Lei, 2018. "A data driven multi-state model for distribution system flexible planning utilizing hierarchical parallel computing," Applied Energy, Elsevier, vol. 232(C), pages 9-25.
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