Please use this identifier to cite or link to this item: https://doi.org/10.1145/3563357.3564077
Title: From Model-Centric to Data-Centric: A Practical MPC Implementation Framework for Buildings
Authors: Zhan, S 
Quintana, M 
Miller, C 
Chong, A 
Issue Date: 9-Nov-2022
Publisher: ACM
Citation: Zhan, S, Quintana, M, Miller, C, Chong, A (2022-11-09). From Model-Centric to Data-Centric: A Practical MPC Implementation Framework for Buildings. BuildSys '22: The 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation : 270-273. ScholarBank@NUS Repository. https://doi.org/10.1145/3563357.3564077
Abstract: The potential of using Model Predictive Control (MPC) to improve building operation has been shown in many studies. Unfortunately, real-world applications are still restricted by the high implementation cost and the unguaranteed profitability. In the traditional paradigm of "model-centric"MPC, most effort is devoted to constructing the control-oriented model given specific building properties and data availability. Due to the significant heterogeneity among buildings, the results are hardly reproducible, and a high level of customization is required for each new building. To address this issue, we propose a new "data-centric"approach for MPC, which starts with control-oriented data curation that acquires the necessary and cost-effective data concerning the intended control purpose and the building characteristics. The foundation of data-centric MPC is a standardized framework to quantify the data requirements and the established relationships between data usage and control performance. Such an end-to-end framework promotes actual MPC applications with controllable costs and reliable outcomes. We use tropical office buildings as an example to consolidate the data-centric MPC framework. Two use cases are provided to demonstrate its benefits. Over 10% of energy saving was achieved without excessive occupant-related data, and occupant-centric control significantly improved the thermal comfort only with proper data acquisition.
Source Title: BuildSys '22: The 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation
URI: https://scholarbank.nus.edu.sg/handle/10635/236542
ISBN: 9781450398909
DOI: 10.1145/3563357.3564077
Appears in Collections:Staff Publications
Elements

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
buildsys2022-final250.pdfAccepted version3.53 MBAdobe PDF

OPEN

Pre-printView/Download

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.