Quantification of HVAC Energy Savings for Occupancy Sensing in Buildings Through an Innovative Testing Methodology

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College Station, Texas
Project Term:
09/25/2020 - 06/30/2023

Technology Description:

The Texas A&M University team will develop a testing protocol and simulation suite for assessing the performance of advanced occupancy sensors. The testing protocol and simulation suite will address eight levels of building/occupant scenario 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 simulation tools will leverage data analytics with built-in machine learning algorithms to determine energy savings. Technical results from the testing and validation work will support technology to market efforts, including codes and standards updates, and help to validate the performance of systems developed through Categories A and B of the SENSOR program.

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.


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.


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) that may, in turn, lead to improved occupant productivity.


ARPA-E Program Director:
Dr. Marina Sofos
Project Contact:
Zheng O'Neill
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