| DOI | Resolve DOI: https://doi.org/10.1080/19401493.2025.2524379 |
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| Author | Search for: Gunay, BurakORCID identifier: https://orcid.org/0000-0003-3214-700X; Search for: Elehwany, Hussein; Search for: Bahiraei, Farid1ORCID identifier: https://orcid.org/0000-0003-1168-3460; Search for: Darwazeh, Darwish1 |
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| Affiliation | - National Research Council Canada. Construction
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| Funder | Search for: Natural Sciences and Engineering Research Council of Canada; Search for: Ontario Ministry of Colleges and Universities; Search for: National Research Council Canada |
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| Format | Text, Article |
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| Subject | demand response; adaptivecontrols; contextual banditsalgorithm; dynamicelectricity pricing; global optimization |
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| Abstract | Preheating / precooling the thermal mass of a building with off-peak electricity can significantly reduce demand for heating / cooling during peak periods. However, an unknown part of this load shifting process is dynamically determining the optimal preconditioning sequence. This paper puts forward a contextual bandits-based algorithm to dynamically optimize preconditioning behaviour. The analysis was conducted by employing a high-fidelity emulator in EnergyPlus, representing a generic small office building. The algorithm iteratively develops univariate change point models for different discrete preconditioning levels, enabling the estimation of a near-optimal preconditioning level for a given building and outdoor temperature forecast for the day. HVAC-related electricity cost savings achieved through this adaptive algorithm varied between 10 and 40% for different peak pricing and envelope scenarios. For all peak pricing and envelope scenarios, the adaptive algorithm was superior to the baseline preconditioning sequences and within 2% of those estimated using a global optimization approach. |
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| Publication date | 2025-07-02 |
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| Publisher | Taylor & Francis |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 670082a6-52ed-40ab-a729-121819577672 |
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| Record created | 2025-09-09 |
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| Record modified | 2025-11-28 |
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