Abstract
Electric utilities are driving towards enabling automatic scheduling and control of the consumption pattern of appliances such as heating, ventilation, and air conditioning (HVAC) and water heater (WH) systems (e.g., through preheating and pre-cooling, etc.) within smart neighborhoods to minimize energy cost and peak load demand. Quantifying economic savings through direct comparison of the optimized energy usage profile on a specific day with the typical non-optimized usage profile on another day is not a fair comparison because energy usage highly depends on weather conditions and human behaviour especially appliance like HVAC on those days. In this paper, we propose a novel approach of identifying similar weather day pairs which can then be used to compare the energy use profiles within homes between the identified pairs. We then demonstrate how the proposed approach can be used to compute cost savings due to optimization and control of smart appliances at home and neighborhood-level within a future-focused smart neighborhood of 62 residential homes. We also demonstrate a simulation based approach to quantify cost savings and showcase our findings through customized and interactive visualizations.
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 | 59-68 |
Number of pages | 10 |
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 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 nonexclusive, 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).
Keywords
- Furnace
- HVAC
- Internet of Things
- Sensors
- Smart neighborhood
- Water heater