Licensing Opportunity: Autonomous Anomaly Detection of Model Forecasts of Controllable Devices in Residential Communities
Closed Special Notice Posted
- Solicitation number
- 2024-09-11-P
- Agency
-
Department of Energy
- Responses due
- Set-aside
- No set-aside
Opportunity facts
- Place of performance
- Oak Ridge, Tennessee 37830, United States
- Points of contact
Notice details come from SAM.gov. Updated .
About this opportunity
This Special Notice is from the Department of Energy (DOE) and describes a licensing opportunity for an autonomous anomaly detection system for model forecasts of controllable devices in residential communities. The technology is software based on machine learning that can automatically identify anomalies in HVAC and water heater systems, perform data curation and cleaning, conduct error analysis, and classify anomalies for different building types and usage profiles. This can help manage peak demand, carbon emissions, energy consumption, and integrate distributed renewables into the grid.
The purpose of this Special Notice is to offer a licensing opportunity for this autonomous anomaly detection technology. The due date for interested parties is October 26, 2024. There are no set-aside requirements, so the opportunity is open to all eligible contractors. The technology can be used by electric utilities, HVAC/plumbing companies, and the construction industry to improve the efficiency and performance of residential and commercial building systems.
Notice text
Invention Reference Number: 202405628
Water heaters and heating, ventilation, and air conditioning (HVAC) systems collectively consume about 58% of home energy use. Managing these systems is crucial for managing peak demand, carbon emission, energy consumption, electricity price and integrating distributed renewables into older grid systems. However, model forecasts lack anomaly detection systems which are essential for efficient use of devices as they can allow to study the behavior of the model, improve forecasting load accuracy, and implement error correction schemes. This technology is an autonomous system that can perform data curation, data cleaning, conduct error analysis, and detect anomalies of model forecasts of HVAC and water heater systems.
Description
This technology is software based on machine learning that autonomously identifies anomalies in HVAC and water heater systems in homes and commercial buildings. It is time-consuming and intensive to detect these anomalies manually as a residential neighborhood often contains several homes. The complexity further increases with the increasing time period of analysis. This is an autonomous system that can perform data curation, data cleaning, conduct error analysis, and detect anomalies of model forecasts of HVAC and water heater systems, and can classify anomalies for subgroups such as different floors, fan use, corner units, basement and water usage profiles.
Benefits
- Only method to automatically detect anomalies in predictive control and correct them without human intervention
- Saves time and money
- More efficient
- Can run on laptop or cloud
- Increases occupant comfort
- Can detect anomalies in power grid
Applications and Industries
- Electric utilities
- HVAC/Plumbing
- Construction
Contact
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.
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