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Title: Non-Intrusive Load Monitoring of HVAC Components using Signal Unmixing

Heating, Ventilating and Air Conditioning units (HVAC) are a major electrical energy consumer in buildings. Monitoring of the operation and energy consumption of HVAC would increase the awareness of building owners and maintenance service providers of the condition and quality of performance of these units, enabling conditioned-based maintenance which would help achieving higher energy efficiency. In this paper, a novel non-intrusive load monitoring method based on group constrained non-negative matrix factorization is proposed for monitoring the different components of HVAC unit by only measuring the whole building aggregated power signal. At the first level of this hierarchical approach, power consumption of the building is decomposed to energy consumption of the HVAC unit and all the other electrical devices operating in the building such as lighting and plug loads. Then, the estimated power signal of the HVAC is used for estimating the power consumption profile of the HVAC major electrical loads such as compressors, condenser fans and indoor blower. Experiments conducted on real data collected from a building testbed maintained at the Oak Ridge National Laboratory (ORNL) demonstrate high accuracy on the disaggregation task.
 [1] ;  [2] ;  [2] ;  [2]
  1. University of Tennessee, Knoxville (UTK)
  2. ORNL
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Conference: 3rd IEEE Global Conference on Signal and Information Processing, 1st International Symposium on Signal Processing Applications in Smart Buildings, Orlando, FL, USA, 20151214, 20151216
Research Org:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Building Technologies Research and Integration Center (BTRIC)
Sponsoring Org:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
Country of Publication:
United States
HVAC power disaggregation; Non-Intrusive Load Monitoring (NILM); Non-negative Matrix Factorization Constraints; Flexible Research Platform