Multi-floor building heating models in MATLAB and Modelica environments
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DOI: 10.1016/j.apenergy.2016.02.143
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- Zhao, Hai-xiang & Magoulès, Frédéric, 2012. "A review on the prediction of building energy consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 3586-3592.
- Lü, Xiaoshu & Lu, Tao & Kibert, Charles J. & Viljanen, Martti, 2015. "Modeling and forecasting energy consumption for heterogeneous buildings using a physical–statistical approach," Applied Energy, Elsevier, vol. 144(C), pages 261-275.
- Harish, V.S.K.V. & Kumar, Arun, 2016. "Reduced order modeling and parameter identification of a building energy system model through an optimization routine," Applied Energy, Elsevier, vol. 162(C), pages 1010-1023.
- De Rosa, Mattia & Bianco, Vincenzo & Scarpa, Federico & Tagliafico, Luca A., 2014. "Heating and cooling building energy demand evaluation; a simplified model and a modified degree days approach," Applied Energy, Elsevier, vol. 128(C), pages 217-229.
- Lü, Xiaoshu & Lu, Tao & Kibert, Charles J. & Viljanen, Martti, 2014. "A novel dynamic modeling approach for predicting building energy performance," Applied Energy, Elsevier, vol. 114(C), pages 91-103.
- Foucquier, Aurélie & Robert, Sylvain & Suard, Frédéric & Stéphan, Louis & Jay, Arnaud, 2013. "State of the art in building modelling and energy performances prediction: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 272-288.
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Cited by:
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- 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).
- Ghiaus, Christian & Ahmad, Naveed, 2020. "Thermal circuits assembling and state-space extraction for modelling heat transfer in buildings," Energy, Elsevier, vol. 195(C).
- Gokhale, Gargya & Claessens, Bert & Develder, Chris, 2022. "Physics informed neural networks for control oriented thermal modeling of buildings," Applied Energy, Elsevier, vol. 314(C).
- Enghok Leang & Pierre Tittelein & Laurent Zalewski & Stéphane Lassue, 2020. "Impact of a Composite Trombe Wall Incorporating Phase Change Materials on the Thermal Behavior of an Individual House with Low Energy Consumption," Energies, MDPI, vol. 13(18), pages 1-32, September.
- Spiliotis, Konstantinos & Gonçalves, Juliana E. & Van De Sande, Wieland & Ravyts, Simon & Daenen, Michael & Saelens, Dirk & Baert, Kris & Driesen, Johan, 2019. "Modeling and validation of a DC/DC power converter for building energy simulations: Application to BIPV systems," Applied Energy, Elsevier, vol. 240(C), pages 646-665.
- Bünning, Felix & Sangi, Roozbeh & Müller, Dirk, 2017. "A Modelica library for the agent-based control of building energy systems," Applied Energy, Elsevier, vol. 193(C), pages 52-59.
- Jannesari, Hamid & Babaei, Banafsheh, 2018. "Optimization of solar assisted heating system for electro-winning process in the copper complex," Energy, Elsevier, vol. 158(C), pages 957-966.
- Pochwała, Sławomir & Anweiler, Stanisław & Tańczuk, Mariusz & Klementowski, Igor & Przysiężniuk, Dawid & Adrian, Łukasz & McNamara, Greg & Stevanović, Žana, 2023. "Energy source impact on the economic and environmental effects of retrofitting a heritage building with a heat pump system," Energy, Elsevier, vol. 278(PB).
- Artur Wyrwa & Yi-kuang Chen, 2017. "Mapping Urban Heat Demand with the Use of GIS-Based Tools," Energies, MDPI, vol. 10(5), pages 1-15, May.
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Keywords
BEMS; Building heating models; MATLAB modelling; Modelica Buildings Library; Physics-based models;All these keywords.
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