Modelling Building Energy Systems using Electric Circuit Analogy
Author
Abstract
Suggested Citation
DOI: 10.24018/ejece.2023.7.1.491
Download full text from publisher
References listed on IDEAS
- Giovanni Bianco & Stefano Bracco & Federico Delfino & Lorenzo Gambelli & Michela Robba & Mansueto Rossi, 2020. "A Building Energy Management System Based on an Equivalent Electric Circuit Model," Energies, MDPI, vol. 13(7), pages 1-23, April.
- 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.
- Li, Yanfei & O'Neill, Zheng & Zhang, Liang & Chen, Jianli & Im, Piljae & DeGraw, Jason, 2021. "Grey-box modeling and application for building energy simulations - A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
- Aulon Shabani & Orion Zavalani, 2017. "Predicting Building Energy Consumption using Engineering and Data Driven Approaches: A Review," European Journal of Engineering and Technology Research, European Open Science, vol. 2(5), pages 44-49, May.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Vallianos, Charalampos & Candanedo, José & Athienitis, Andreas, 2023. "Application of a large smart thermostat dataset for model calibration and Model Predictive Control implementation in the residential sector," Energy, Elsevier, vol. 278(PA).
- Montazeri, Mina & Remlinger, Carl & Bejar Haro, Benjamin & Heer, Philipp, 2025. "Fully data-driven and modular building thermal control with physically consistent modeling," Applied Energy, Elsevier, vol. 390(C).
- Di Natale, L. & Svetozarevic, B. & Heer, P. & Jones, C.N., 2023. "Towards scalable physically consistent neural networks: An application to data-driven multi-zone thermal building models," Applied Energy, Elsevier, vol. 340(C).
- Wang, Qiaochu & Ding, Yan & Kong, Xiangfei & Tian, Zhe & Xu, Linrui & He, Qing, 2022. "Load pattern recognition based optimization method for energy flexibility in office buildings," Energy, Elsevier, vol. 254(PC).
- Pantoš, Miloš & Lukas, Lucija, 2025. "Enhancing power system reliability through demand flexibility of Grid-Interactive Efficient Buildings: A thermal model-based optimization approach," Applied Energy, Elsevier, vol. 381(C).
- Shen, Pengyuan, 2026. "RCBldEng - a computationally efficient RC network modeling method and engine for multizone building simulation," Energy, Elsevier, vol. 346(C).
- Olamilekan E. Tijani & Sylvain Serra & Patrick Lanusse & Rachid Malti & Hugo Viot & Jean-Michel Reneaume, 2025. "Grey-Box Modelling of District Heating Networks Using Modified LPV Models," Energies, MDPI, vol. 18(7), pages 1-32, March.
- Zhang, Zhechen & Luo, Hanbin & Liu, Jiajing, 2025. "Incorporation of knowledge and data-driven models applied in shield tunneling: A review," Reliability Engineering and System Safety, Elsevier, vol. 264(PA).
- Damianakis, Nikolaos & Mouli, Gautham Ram Chandra & Bauer, Pavol & Yu, Yunhe, 2023. "Assessing the grid impact of Electric Vehicles, Heat Pumps & PV generation in Dutch LV distribution grids," Applied Energy, Elsevier, vol. 352(C).
- Tomasz Szul & Stanisław Kokoszka, 2020. "Application of Rough Set Theory (RST) to Forecast Energy Consumption in Buildings Undergoing Thermal Modernization," Energies, MDPI, vol. 13(6), pages 1-17, March.
- Zhang, Chengyu & Ma, Liangdong & Luo, Zhiwen & Han, Xing & Zhao, Tianyi, 2024. "Forecasting building plug load electricity consumption employing occupant-building interaction input features and bidirectional LSTM with improved swarm intelligent algorithms," Energy, Elsevier, vol. 288(C).
- 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).
- Zhang, Xiang & Saelens, Dirk & Roels, Staf, 2022. "Estimating dynamic solar gains from on-site measured data: An ARX modelling approach," Applied Energy, Elsevier, vol. 321(C).
- Massimiliano Manfren & Karla M. Gonzalez-Carreon & Patrick A. B. James, 2024. "Interpretable Data-Driven Methods for Building Energy Modelling—A Review of Critical Connections and Gaps," Energies, MDPI, vol. 17(4), pages 1-22, February.
- Buffat, René & Froemelt, Andreas & Heeren, Niko & Raubal, Martin & Hellweg, Stefanie, 2017. "Big data GIS analysis for novel approaches in building stock modelling," Applied Energy, Elsevier, vol. 208(C), pages 277-290.
- Morovat, Navid & Athienitis, Andreas K. & Candanedo, José Agustín & Nouanegue, Hervé Frank, 2024. "Heuristic model predictive control implementation to activate energy flexibility in a fully electric school building," Energy, Elsevier, vol. 296(C).
- Anna Kipping & Erik Trømborg, 2017. "Modeling Aggregate Hourly Energy Consumption in a Regional Building Stock," Energies, MDPI, vol. 11(1), pages 1-20, December.
- Solène Goy & François Maréchal & Donal Finn, 2020. "Data for Urban Scale Building Energy Modelling: Assessing Impacts and Overcoming Availability Challenges," Energies, MDPI, vol. 13(16), pages 1-23, August.
- Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022.
"Forecasting: theory and practice,"
International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
- Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
- Sun, Yue & Luo, Zhiwen & Li, Yu & Zhao, Tianyi, 2024. "Grey-box model-based demand side management for rooftop PV and air conditioning systems in public buildings using PSO algorithm," Energy, Elsevier, vol. 296(C).
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:epw:ejece0:v:7:y:2023:i:1:id:19491. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: support (email available below). General contact details of provider: https://eu-opensci.org/index.php/ejece .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.
Printed from https://ideas.repec.org/a/epw/ejece0/v7y2023i1id19491.html