• DocumentCode
    3754184
  • Title

    Non-intrusive load monitoring of HVAC components using signal unmixing

  • Author

    Alireza Rahimpour;Hairong Qi;David Fugate;Teja Kuruganti

  • Author_Institution
    Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN 37996, USA
  • fYear
    2015
  • Firstpage
    1012
  • Lastpage
    1016
  • Abstract
    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 high efficiency in energy consumption. In this paper, a novel non-intrusive method based on constrained non-negative matrix factorization is proposed for monitoring the different components of HVAC unit by only having access to 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 to estimate 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 disaggregation task.
  • Keywords
    "Buildings","Power demand","Monitoring","Training","Hidden Markov models","Energy consumption","Matrix decomposition"
  • Publisher
    ieee
  • Conference_Titel
    Signal and Information Processing (GlobalSIP), 2015 IEEE Global Conference on
  • Type

    conf

  • DOI
    10.1109/GlobalSIP.2015.7418350
  • Filename
    7418350