Abstract
Smart buildings improve energy efficiency and provide ancillary services to the power grid. Such services are based on model-based mechanisms that require availability of accurate models of the different building loads such as heating, ventilation, and air conditioning (HVAC) systems. Although numerous efforts have been made in the area of constructing a thermal model for a building HVAC system, almost all models have shortcomings. In this paper, we employ the nuclear-norm-based subspace method to identify a locally accurate HVAC system model. We consider the more general case of a multi-zone building HVAC system, i.e., each zone has its own thermostat and can be set to a different temperature. The estimated HVAC system model can be used to predict the future indoor temperatures. This will assist power utility companies and building managers in estimating the upcoming load shape, especially the peak amount and duration.
Original language | English |
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Title of host publication | Proceedings - 2019 3rd International Conference on Smart Grid and Smart Cities, ICSGSC 2019 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 165-169 |
Number of pages | 5 |
ISBN (Electronic) | 9781728138480 |
DOIs | |
State | Published - Jun 2019 |
Event | 3rd International Conference on Smart Grid and Smart Cities, ICSGSC 2019 - Berkeley, United States Duration: Jun 25 2019 → Jun 28 2019 |
Publication series
Name | Proceedings - 2019 3rd International Conference on Smart Grid and Smart Cities, ICSGSC 2019 |
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Conference
Conference | 3rd International Conference on Smart Grid and Smart Cities, ICSGSC 2019 |
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Country/Territory | United States |
City | Berkeley |
Period | 06/25/19 → 06/28/19 |
Funding
This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). ACKNOWLEDGMENT This material is based upon work supported by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy.
Keywords
- Smart buildings
- alternating direction method of multipliers (ADMM)
- multi-zone HVAC systems
- multiple-input multiple-output (MIMO) systems
- nuclear norm
- state space model
- subspace identification