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https://doi.org/10.21256/zhaw-31129| Publikationstyp: | Konferenz: Paper |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | A simulation study on energy optimization in building control with reinforcement learning |
| Autor/-in: | Bolt, Peter Ziebart, Volker Jaeger, Christian Schmid, Nicolas Stadelmann, Thilo Füchslin, Rudolf Marcel |
| et. al: | No |
| DOI: | 10.21256/zhaw-31129 |
| Angaben zur Konferenz: | 11th IAPR TC 3 Workshop on Artificial Neural Networks for Pattern Recognition (ANNPR'24), Montreal, Canada, 10-12 October 2024 |
| Erscheinungsdatum: | 10-Okt-2024 |
| Verlag / Hrsg. Institution: | ZHAW Zürcher Hochschule für Angewandte Wissenschaften |
| Sprache: | Englisch |
| Schlagwörter: | Smart building; Building control; Reinforcement learning |
| Fachgebiet (DDC): | 006: Spezielle Computerverfahren 621.04: Energietechnik |
| Zusammenfassung: | We propose and evaluate a deep reinforcement learning control paradigm for building energy systems. In comparison to other advanced control techniques, namely Model Predictive Control, the reinforcement learning paradigm avoids the costs and uncertainties associated with the requirement for a control-oriented model. We apply a mixed agent for the Proximal Policy Optimization algorithm, similar to the algorithm proposed in as well as a non-discounted finite horizon optimization scheme. We investigate the capabilities of the proposed reinforcement learning controller regarding energy efficiency, comparing it against the most widely used rule-based control paradigm as a baseline controller. We verify our proposed paradigm in a simulation study with building models implemented in Dymola. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/31129 |
| Volltext Version: | Akzeptierte Version |
| Lizenz (gemäss Verlagsvertrag): | Lizenz gemäss Verlagsvertrag |
| Departement: | School of Engineering |
| Organisationseinheit: | Centre for Artificial Intelligence (CAI) Institut für Angewandte Mathematik und Physik (IAMP) |
| Publiziert im Rahmen des ZHAW-Projekts: | Machbarkeitsstudie Reinforcement Learning Control für Heizsysteme |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 2024_Bolt-etal_Simulation-study-energy-optimization_ANNPR.pdf | Accepted Version | 1.02 MB | Adobe PDF |  Öffnen/Anzeigen |
Zur Langanzeige
Bolt, P., Ziebart, V., Jaeger, C., Schmid, N., Stadelmann, T., & Füchslin, R. M. (2024, October 10). A simulation study on energy optimization in building control with reinforcement learning. 11th IAPR TC 3 Workshop on Artificial Neural Networks for Pattern Recognition (ANNPR′24), Montreal, Canada, 10-12 October 2024. https://doi.org/10.21256/zhaw-31129
Bolt, P. et al. (2024) ‘A simulation study on energy optimization in building control with reinforcement learning’, in 11th IAPR TC 3 Workshop on Artificial Neural Networks for Pattern Recognition (ANNPR′24), Montreal, Canada, 10-12 October 2024. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. Available at: https://doi.org/10.21256/zhaw-31129.
P. Bolt, V. Ziebart, C. Jaeger, N. Schmid, T. Stadelmann, and R. M. Füchslin, “A simulation study on energy optimization in building control with reinforcement learning,” in 11th IAPR TC 3 Workshop on Artificial Neural Networks for Pattern Recognition (ANNPR′24), Montreal, Canada, 10-12 October 2024, Oct. 2024. doi: 10.21256/zhaw-31129.
BOLT, Peter, Volker ZIEBART, Christian JAEGER, Nicolas SCHMID, Thilo STADELMANN und Rudolf Marcel FÜCHSLIN, 2024. A simulation study on energy optimization in building control with reinforcement learning. In: 11th IAPR TC 3 Workshop on Artificial Neural Networks for Pattern Recognition (ANNPR′24), Montreal, Canada, 10-12 October 2024. Conference paper. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. 10 Oktober 2024
Bolt, Peter, Volker Ziebart, Christian Jaeger, Nicolas Schmid, Thilo Stadelmann, and Rudolf Marcel Füchslin. 2024. “A Simulation Study on Energy Optimization in Building Control with Reinforcement Learning.” Conference paper. In 11th IAPR TC 3 Workshop on Artificial Neural Networks for Pattern Recognition (ANNPR′24), Montreal, Canada, 10-12 October 2024. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. https://doi.org/10.21256/zhaw-31129.
Bolt, Peter, et al. “A Simulation Study on Energy Optimization in Building Control with Reinforcement Learning.” 11th IAPR TC 3 Workshop on Artificial Neural Networks for Pattern Recognition (ANNPR′24), Montreal, Canada, 10-12 October 2024, ZHAW Zürcher Hochschule für Angewandte Wissenschaften, 2024, https://doi.org/10.21256/zhaw-31129.
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