Quantification of HVAC Energy Savings

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Program:
SENSOR
Award:
$610,039
Location:
Tuscaloosa, Alabama
Status:
ALUMNI
Project Term:
08/16/2018 - 08/15/2021

Technology Description:

The University of Alabama and their partners will develop a new testing and validation protocol for advanced occupancy sensor technologies. A barrier to wide adoption of new occupancy sensors is the lack of rigorous and widely accepted methodologies for evaluating the energy savings and reliability of these systems. To address this need, the Alabama team will develop a testing protocol and simulation suite for these advanced sensors. The protocol and simulation suite will take into account eight levels of diversity: 1) occupant profile, 2) building type and floor plan, 3) sensor type, 4) HVAC controls and modes (e.g., temperature and/or ventilation setback), 5) functional testing diversity, 6) deployment diversity (e.g., sensor location), 7) software diversity (e.g., computation at local vs. hub), and 8) diagnostic diversity (e.g., interpret missing data). The regime's simulation tools will take advantage of data analytics with built-in machine learning algorithms to accurately determine energy savings. Technical results from the testing and validation work will support technology to market efforts, including codes and standards updates.

Potential Impact:

If successful, SENSOR projects will dramatically reduce the amount of energy needed to effectively heat, cool, and ventilate buildings without sacrificing occupant comfort.

Security:

Lower electricity consumption by buildings eases strain on the grid, helping to improve resilience and reduce demand during peak hours, when the threat of blackouts is greatest.

Environment:

Using significantly less energy could help reduce emissions attributed to power generation. In addition, improved interior air quality could help prevent negative effects on human health.

Economy:

Buildings will require less energy to operate, reducing heating, cooling, and ventilation costs for businesses and families. In addition, better controlled ventilation may lead to improved indoor air quality (ensured by an accurate occupant count, and validated via widespread CO2 detection) may lead to improved worker productivity and academic performance.

Contact

ARPA-E Program Director:
Dr. Marina Sofos
Project Contact:
Dr. Zheng O'Neill
Press and General Inquiries Email:
ARPA-E-Comms@hq.doe.gov
Project Contact Email:
zoneill@eng.ua.edu

Partners

University of Texas, San Antonio
Pacific Northwest National Laboratory

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Release Date:
01/18/2017