Building Simulation

, Volume 8, Issue 5, pp 515–528 | Cite as

Development of a home energy audit methodology for determining energy-efficient, cost-effective measures in existing single-family houses using an easy-to-use simulation

Research Article Building Thermal, Lighting, and Acoustics Modeling

Abstract

This study developed a home energy audit methodology for determining energy-efficient, cost-effective measures in existing single-family houses using an easy-to-use simulation. The overall goal of this study was to provide an easy-to-use, time-saving home energy audit for users who are not familiar with building physics and building energy simulation programs such as homeowners, etc. The methodology that was developed can identify the cause of over-consumption in a house prior to a walk-through investigation by showing where the energy is inefficiently being used when compared to houses of similar sizes in similar climates. In order to accomplish this, a methodology for an easy-to-use, calibrated simulation that can determine potential energy conservation measures for existing single-family houses was developed. In addition, to verify the methodology, the results were compared to those obtained from a detailed, as-built residential energy simulation to determine if both the simulation results identified the same potential energy conservation measures. As a result, it was found that the easy-to-use simulation can be used as an as-built simulation for a home energy audit procedure with acceptable results for the case-study house.

Keywords

home energy audits easy-to-use simulation calibrated simulation energy conservation measure (ECM) pay-back period 

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References

  1. Apogee (2012). Energy Insights. Available at http://www.apogee.net/products/energyInsights.aspx.Google Scholar
  2. ASHRAE (2014). ASHRAE Guideline 14-2014: Measurement of Energy and Demand Savings. Atlanta, USA: American Society of Heating, Refrigerating, and Air-Conditioning Engineers.Google Scholar
  3. ASHRAE (2009). ASHRAE Handbook—Fundamentals. Atlanta, USA: American Society of Heating, Refrigerating, and Air-Conditioning Engineers.Google Scholar
  4. Christman K, Haberl J, Claridge D (2009). Analysis of energy recovery ventilator savings for Texas buildings. In: Proceedings of the 9th International Conference for Enhanced Building Operations (ICEBO), Austin, TX, USA.Google Scholar
  5. Doty S, Turner W (2009). Energy Management Handbook, 7th edn. Lilburn, GA, USA: The Fairmont Press.Google Scholar
  6. Faithful+Gould (2012). Residential Energy Efficiency Measures-Prototype Estimate and Cost Data, Revision 6.0. Beaverton, OR, USA: Faithful+Gould.Google Scholar
  7. Gettings M, Krigger J, Fishbaugher M (2001). National Energy Audit (NEAT) User’s Manual, Version 7. Oak Ridge, TN, USA: Oak Ridge National Laboratory.Google Scholar
  8. Heat and Cool (2014). Cost Estimates for SEER 13 Klimaire Air-conditioner. Available at http://www.heatandcool.com/Klimaire-Condensing-Unit-p/csm60c2p13-aram60h2p-hk152c.htm.MATHGoogle Scholar
  9. ICC (2009). International Energy Conservation Code. International Code Council, Inc.Google Scholar
  10. ICC (2009). International Energy Conservation Code. International Code Council.Google Scholar
  11. Kim KH (2014). Development of an improved methodology for analyzing existing single-family residential energy use. Ph.D. Thesis, Texas A&M University, USA.Google Scholar
  12. Kim KH, Baltazar-Cervantes J-C (2010). Procedure for packing weather files for DOE-2.1e. Report ESL-TR-10-09-03. College Station, TX, USA: Energy Systems Laboratory.Google Scholar
  13. Kim KH, Haberl JS (2015). Development of methodology for calibrated simulation in single-family residential buildings using three-parameter change-point regression model. Energy and Buildings, 99: 140–152.CrossRefGoogle Scholar
  14. Kim S, Haberl JS (2007). Comparative testing of the combined radiant barrier and duct models in the ESL’s code-compliant simulation model. Report ESL-TR-07-02-01. College Station, TX, USA: Energy Systems Laboratory.Google Scholar
  15. Kissock K, Haberl J, Claridge D (2002). Development of a toolkit for calculating linear, change-point linear and multiple-linear inverse building energy analysis models. ASHRAE Research Project 1050-RP.Google Scholar
  16. LBL (1991). DOE-2 Basics. Berkeley, CA, USA: Lawrence Berkeley Laboratory.Google Scholar
  17. Marshall K, Moss M, Malhotra M, Liu B, Culp C, Haberl J, Herbert C (2010). AIM: Web-based, residential energy calculator for homeowners. Report ESL-PA-10-08-02. College Station, TX, USA: Energy Systems Laboratory.Google Scholar
  18. Mendon V, Lucas R, Goel S (2013). Cost-effectiveness analysis of the 2009 and 2012 IECC residential provisions. Report PNNL-220068. Richland, WA, USA: Pacific Northwest National Laboratory.Google Scholar
  19. Mills E, Brown R, Pinckard M, Warner J, Moezzi M, et al. (2007). Home Energy Saver: Documentation of calculation methodology, input data, and infrastructure. Report No. 51938. Berkeley, CA, USA: Lawrence Berkeley National Laboratory.MATHGoogle Scholar
  20. Mukhopadhyay J, Baltazar-Cervantes J-C, Haberl J, Ellis S (2013). Comparing the implementation of the 2012 IECC to the 2009 Michigan uniform energy code for residential construction. Report ESL-ITR-13-12-01. College Station, TX, USA: Energy Systems Laboratory.Google Scholar
  21. NAHB (2012). The Builders Practices Survey Reports. Upper Marlboro, MD, USA: National Association of Home Builders Research Center.Google Scholar
  22. RESNET (2006). Procedures for verification of RESNET accredited HERS software tools. Report RESNET Publication No. 06-002. Residential Energy Servicer Network.Google Scholar
  23. SENTECH (2010). Review of Selected Home Energy Auditing Tools: In Support of the Development of National Building Performance Assessment and Rating Program. Glenside, PA, USA: SENTECH, Inc.Google Scholar
  24. USDOE (2012). Home Energy Saver. US Department of Energy. Available at http://hes.lbl.gov/consumer.Google Scholar
  25. USEIA (2012). Annual Energy Outlook. Washington DC: US Energy Information Administration.Google Scholar

Copyright information

© Tsinghua University Press and Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Research Institute of Industrial ScienceHanyang UniversitySeoulR.O. Korea
  2. 2.Department of ArchitectureTexas A&M UniversityCollege StationUSA

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