skip to main content
research-article

Modeling building thermal response to HVAC zoning

Published:01 July 2012Publication History
Skip Abstract Section

Abstract

HVAC systems account for 38% of building energy usage. Studies have indicated at least 5-15% waste due to unoccupied spaces being conditioned. Our goal is to minimize this waste by retrofitting HVAC systems to enable room-level zoning where each room is conditioned individually based on its occupancy. This will allow only occupied rooms to be conditioned while saving the energy used to condition unoccupied rooms. In order to achieve this goal, the effect of opening or closing air vent registers on room temperatures has to be predicted. Making such a prediction is complicated by the fact that weather has a larger effect on room temperatures than the settings of air vent registers, making it hard to isolate the influence of the HVAC system. We present a technique for dynamically estimating the heat load due to weather on room temperatures and subtracting it out in order to predict the effect of the HVAC system more directly.

References

  1. A. Aswani, N. Master, J. Taneja, D. Culler, and C. Tomlin. Reducing transient and steady state electricity consumption in hvac using learning-based model predictive control. In Proceedings of the IEEE, 2011.Google ScholarGoogle Scholar
  2. N. Ben-Aissa. Heating, ventilation, and air conditioning (hvac) controls: Variable air volume (vav) systems. Johnson Controls, Inc.Google ScholarGoogle Scholar
  3. K. Deng, P. Barooah, P. Mehta, and S. Meyn. Building thermal model reduction via aggregation of state. In American Control Conference, pages 5118--5123, 2010.Google ScholarGoogle Scholar
  4. U. DoE. Buildings energy data book, 2011.Google ScholarGoogle Scholar
  5. Energy Information Administration. 2005 residential energy consumption survey. http://www.eia.doe.gov/emeu/recs/contents.html.Google ScholarGoogle Scholar
  6. Energy Policy Branch Energy Sector Energy Forecasting Division. Canada's energy outlook, 1996-2020. Natural Resources Canada, 1997.Google ScholarGoogle Scholar
  7. G. Henze, C. Felsmann, and G. Knabe. Evaluation of optimal control for active and passive building thermal storage. International Journal of Thermal Sciences, 43(2):173--183, 2004.Google ScholarGoogle ScholarCross RefCross Ref
  8. Y. Ma, G. Anderson, and F. Borrelli. A distributed predictive control approach to building temperature regulation. In American Control Conference, 2011.Google ScholarGoogle Scholar
  9. J. McQuade. A system approach to high performance buildings. Technical report, United Technologies Corporation, 2009.Google ScholarGoogle Scholar
  10. T. Nghiem and G. Pappas. Receding-horizon supervisory control of green buildings. In American Control Conference, 2011.Google ScholarGoogle ScholarCross RefCross Ref
  11. F. Oldewurtel, A. Parisio, C. Jones, M. Morari, D. Gyalistras, M. Gwerder, V. Stauch, B. Lehmann, and K. Wirth. Energy efficient building climate control using stochastic model predictive control and weather predictions. In American Control Conference, pages 5100--5105, 2010.Google ScholarGoogle ScholarCross RefCross Ref
  12. K. Rathouse and B. Young. Domestic heating: Use of controls. Technical Report RPDH 15, Building Research Establishment, UK, 2004.Google ScholarGoogle Scholar
  13. T. Sookoor, B. Holben, and K. Whitehouse. Feasibility of retrofitting centralized hvac systems for room-level zoning.Google ScholarGoogle Scholar

Index Terms

  1. Modeling building thermal response to HVAC zoning

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in

      Full Access

      • Published in

        cover image ACM SIGBED Review
        ACM SIGBED Review  Volume 9, Issue 3
        Special Issue on the 3rd International Workshop on Networks of Cooperating Objects (CONET 2012)
        July 2012
        42 pages
        EISSN:1551-3688
        DOI:10.1145/2367580
        Issue’s Table of Contents

        Copyright © 2012 Authors

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 1 July 2012

        Check for updates

        Qualifiers

        • research-article

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader