Simulation models for the analysis of space heat consumption of buildings
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DOI: 10.1016/j.energy.2009.05.035
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Cited by:
- Andrea Menapace & Simone Santopietro & Rudy Gargano & Maurizio Righetti, 2021. "Stochastic Generation of District Heat Load," Energies, MDPI, vol. 14(17), pages 1-17, August.
- 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.
- Verda, Vittorio & Colella, Francesco, 2011. "Primary energy savings through thermal storage in district heating networks," Energy, Elsevier, vol. 36(7), pages 4278-4286.
- Sun, Chunhua & Chen, Jiali & Cao, Shanshan & Gao, Xiaoyu & Xia, Guoqiang & Qi, Chengying & Wu, Xiangdong, 2021. "A dynamic control strategy of district heating substations based on online prediction and indoor temperature feedback," Energy, Elsevier, vol. 235(C).
- Tian, Wei & Song, Jitian & Li, Zhanyong & de Wilde, Pieter, 2014. "Bootstrap techniques for sensitivity analysis and model selection in building thermal performance analysis," Applied Energy, Elsevier, vol. 135(C), pages 320-328.
- 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.
- 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.
- F. Marta L. Di Lascio & Andrea Menapace & Maurizio Righetti, 2018. "Joint and conditional dependence modeling of peak district heating demand and outdoor temperature: a copula-based approach," BEMPS - Bozen Economics & Management Paper Series BEMPS53, Faculty of Economics and Management at the Free University of Bozen.
- Hansen, Kenneth & Connolly, David & Lund, Henrik & Drysdale, David & Thellufsen, Jakob Zinck, 2016. "Heat Roadmap Europe: Identifying the balance between saving heat and supplying heat," Energy, Elsevier, vol. 115(P3), pages 1663-1671.
- Lund, Henrik & Østergaard, Poul Alberg & Connolly, David & Mathiesen, Brian Vad, 2017. "Smart energy and smart energy systems," Energy, Elsevier, vol. 137(C), pages 556-565.
- Kusiak, Andrew & Li, Mingyang, 2010. "Reheat optimization of the variable-air-volume box," Energy, Elsevier, vol. 35(5), pages 1997-2005.
- Prasad, Ravita D. & Bansal, R.C. & Raturi, Atul, 2014. "Multi-faceted energy planning: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 686-699.
- 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.
- Ascione, Fabrizio & Bianco, Nicola & De Stasio, Claudio & Mauro, Gerardo Maria & Vanoli, Giuseppe Peter, 2017. "Artificial neural networks to predict energy performance and retrofit scenarios for any member of a building category: A novel approach," Energy, Elsevier, vol. 118(C), pages 999-1017.
- Edwards, Richard E. & New, Joshua & Parker, Lynne E. & Cui, Borui & Dong, Jin, 2017. "Constructing large scale surrogate models from big data and artificial intelligence," Applied Energy, Elsevier, vol. 202(C), pages 685-699.
- Niu, Shu-wen & Li, Yi-xin & Ding, Yong-xia & Qin, Jing, 2010. "Energy demand for rural household heating to suitable levels in the Loess Hilly Region, Gansu Province, China," Energy, Elsevier, vol. 35(5), pages 2070-2078.
- Gouveia, João Pedro & Fortes, Patrícia & Seixas, Júlia, 2012. "Projections of energy services demand for residential buildings: Insights from a bottom-up methodology," Energy, Elsevier, vol. 47(1), pages 430-442.
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Keywords
District heating systems; Simulation model; Artificial neural networks models; Prediction; Energy savings;All these keywords.
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