Abstract
The availability of large-area sensing, scalable algorithms, and high-performance computing has enabled the possibility of urban-scale building energy modeling using new methods not limited to the scalability of manual building energy model creation or retrieval of county-by-county tax assessor's data. Automatic Building detection and Energy Model creation (AutoBEM) has created 178,368 building energy models for the Electric Power Board (EPB) of Chattanooga, TN, and compared simulation performance to 15-minute data from each building. These models leverage several data sources (e.g. imagery, GIS, utility), software tools to extract building properties (e.g. footprint, height, façade type, window-to-wall ratio, occupancy, building type), simulate at scale on two of the world's #1 fastest supercomputers, and provide web-based visual analytics. Grid-interactive efficient buildings offer the potential to reduce utility and rate-payer energy costs during each calendar month's hour of critical generation - when the least efficient, most costly, and often dirtiest generation assets must be brought online. In this paper, EnergyPlus is used to simulate over 150,000 buildings to assess the technical potential of utility-controlled smart thermostats. This is analyzed under a couple scenarios leveraging buildings as thermal batteries via pre-conditioning to coast through peak hours. Results are provided in box and whisker plots assessing the distribution of peak demand reduction at the utility-scale along with breakouts of energy and demand savings by building type and vintage.
| Original language | English |
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| Title of host publication | UrbSys 2019 - Proceedings of the 1st ACM International Workshop on Urban Building Energy Sensing, Controls, Big Data Analysis, and Visualization, Part of BuildSys 2019 |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 82-86 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781450370141 |
| DOIs | |
| State | Published - Nov 13 2019 |
| Event | 1st ACM International Workshop on Urban Building Energy Sensing, Controls, Big Data Analysis, and Visualization, UrbSys 2019 - Part of BuildSys 2019 - New York, United States Duration: Nov 10 2019 → … |
Publication series
| Name | UrbSys 2019 - Proceedings of the 1st ACM International Workshop on Urban Building Energy Sensing, Controls, Big Data Analysis, and Visualization, Part of BuildSys 2019 |
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Conference
| Conference | 1st ACM International Workshop on Urban Building Energy Sensing, Controls, Big Data Analysis, and Visualization, UrbSys 2019 - Part of BuildSys 2019 |
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| Country/Territory | United States |
| City | New York |
| Period | 11/10/19 → … |
Funding
This work was funded by field work proposal CEBT105 under DOE Building Technology Activity Number BT0201000. This research used resources of the Oak Ridge Leadership Computing Facility at ORNL, which is supported by the Office of Science of the DOE under Contract No. DE-AC05-00OR22725. This work was funded by field work proposal CEBT105 under DOE Building Technology Activity Number BT0201000. This research used resources of the Oak Ridge Leadership Computing Facility at ORNL, which is supported by the Office of Science of the DOE under Contract No. DE-AC05-00OR22725. ORNL is managed by UT-Battelle, LLC, for DOE under contract DE-AC05-00OR22725. This manuscript has been authored by UT-Battelle, LLC, under Contract Number DEAC05-00OR22725 with DOE. 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.
Keywords
- Peak demand reduction
- Smart thermostats
- Urban scale building energy modeling