Development and Validation of Home Comfort System for Total Performance Deficiency/Fault Detection and Optimal Comfort Control
- Univ. of Oklahoma, Norman, OK (United States); University of Oklahoma
- Univ. of Oklahoma, Norman, OK (United States); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Univ. of Oklahoma, Norman, OK (United States)
- Univ. of Miami, FL (United States)
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
In this project, we developed and tested a learning-based home thermal model that facilitates the operation of a model predictive control (MPC)-based optimization agent and an automated fault detection and diagnosis (AFDD) agent. The home thermal model was constructed using a two-node resistor-capacitor model. Moreover, two accompanying parameter identification methods were introduced, least-squares and optimization. Based on the home thermal model, the MPC-based optimization agent was developed to optimize residential HVAC operation. Using two FDD methods, the AFDD agent was constructed to detect and diagnose two prevalent residential AC faults, airflow reduction and refrigerant undercharge. The home thermal model, along with the MPC-based optimization agent and AFDD agent, were tested at the Norman Test House, Miami Test House, Pacific Northwest National Laboratory (PNNL) Test House A, and PNNL Test House B. Finally, they were also field tested in nine demonstration homes with real occupants.
- Research Organization:
- Univ. of Oklahoma, Norman, OK (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office
- DOE Contract Number:
- EE0008697
- OSTI ID:
- 2352250
- Report Number(s):
- DOE-OU--EE0008697; DOE/GO-102024-5884; DE-FOA-0001824; 1824-1515
- Country of Publication:
- United States
- Language:
- English
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