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A long term study of residential home heating consumption and the effect of occupant behavior on homes in the Pacific Northwest constructed according to improved thermal standards

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  • Emery, A.F.
  • Kippenhan, C.J.

Abstract

The space heating energy needed during the winter heating season in Seattle Washington, USA, was monitored over a 15-year period, 1987–2002. Two single family residence houses were constructed to building code standards in force at the time of construction and two to standards calling for envelopes with improved thermal resistance. Space conditioning energy needs are strongly affected by occupant behavior, but generally simulations ignore the behavior of the occupants in estimating the energy needed for heating and cooling. The data suggest that estimates of energy savings can be based upon envelope thermal resistance for moderate occupant behavior. For such behavior, the space heating is well characterized by the daily average difference between house average space temperature and outside air temperature. Characterizing in terms of indoor temperature, outdoor air temperature, wind speed, and insolation gives a slightly better representation but requires more information than is usually available. However, vigorous conservation tactics, which produce a thermal response that is highly transient, can lead to substantially different energy needs. No correlation could be established from the measured space heating when aggressive conservation made use of thermostat setback at every opportunity.

Suggested Citation

  • Emery, A.F. & Kippenhan, C.J., 2006. "A long term study of residential home heating consumption and the effect of occupant behavior on homes in the Pacific Northwest constructed according to improved thermal standards," Energy, Elsevier, vol. 31(5), pages 677-693.
  • Handle: RePEc:eee:energy:v:31:y:2006:i:5:p:677-693
    DOI: 10.1016/j.energy.2005.04.006
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    1. Vine, Edward L. & Craig, Paul P. & Cramer, James C. & Dietz, Thomas M. & Hackett, Bruce M. & Kowalczyk, Dan J. & Levine, Mark D., 1982. "The applicability of energy models to occupied houses: Summer electric use in Davis," Energy, Elsevier, vol. 7(11), pages 909-925.
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    1. Jain, Rishee K. & Smith, Kevin M. & Culligan, Patricia J. & Taylor, John E., 2014. "Forecasting energy consumption of multi-family residential buildings using support vector regression: Investigating the impact of temporal and spatial monitoring granularity on performance accuracy," Applied Energy, Elsevier, vol. 123(C), pages 168-178.
    2. Lee, Jae Yong & Yim, Taesu, 2021. "Energy and flow demand analysis of domestic hot water in an apartment complex using a smart meter," Energy, Elsevier, vol. 229(C).
    3. Kelly, Scott & Shipworth, Michelle & Shipworth, David & Gentry, Michael & Wright, Andrew & Pollitt, Michael & Crawford-Brown, Doug & Lomas, Kevin, 2013. "Predicting the diversity of internal temperatures from the English residential sector using panel methods," Applied Energy, Elsevier, vol. 102(C), pages 601-621.
    4. Vivian W. Y. Tam & Laura Almeida & Khoa Le, 2018. "Energy-Related Occupant Behaviour and Its Implications in Energy Use: A Chronological Review," Sustainability, MDPI, vol. 10(8), pages 1-20, July.
    5. D’Oca, Simona & Hong, Tianzhen & Langevin, Jared, 2018. "The human dimensions of energy use in buildings: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 731-742.
    6. Rouleau, Jean & Gosselin, Louis & Blanchet, Pierre, 2018. "Understanding energy consumption in high-performance social housing buildings: A case study from Canada," Energy, Elsevier, vol. 145(C), pages 677-690.
    7. Troy Malatesta & Qilin Li & Jessica K. Breadsell & Christine Eon, 2023. "Distinguishing Household Groupings within a Precinct Based on Energy Usage Patterns Using Machine Learning Analysis," Energies, MDPI, vol. 16(10), pages 1-25, May.
    8. Lin Yang & Sha Liu & Jiaqi Liu, 2021. "The Interaction Effect of Occupant Behavior-Related Factors in Office Buildings Based on the DNAS Theory," Sustainability, MDPI, vol. 13(6), pages 1-25, March.
    9. Sunčana Slijepčević & Davor Mikulić & Kristijan Horvat, 2019. "Evaluation of the Cost-Effectiveness of the Installation of Heat-Cost Allocators in Multifamily Buildings in Croatia," Energies, MDPI, vol. 12(3), pages 1-20, February.
    10. Swan, Lukas G. & Ugursal, V. Ismet, 2009. "Modeling of end-use energy consumption in the residential sector: A review of modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1819-1835, October.
    11. Singh, M.C. & Garg, S.N., 2009. "Energy rating of different glazings for Indian climates," Energy, Elsevier, vol. 34(11), pages 1986-1992.
    12. Anderson, Kyle & Lee, SangHyun, 2016. "An empirically grounded model for simulating normative energy use feedback interventions," Applied Energy, Elsevier, vol. 173(C), pages 272-282.
    13. Niu, Shu-wen & Li, Yi-xin & Ding, Yong-xia & Qin, Jing, 2010. "Energy demand for rural household heating to suitable levels in the Loess Hilly Region, Gansu Province, China," Energy, Elsevier, vol. 35(5), pages 2070-2078.
    14. Rouleau, Jean & Gosselin, Louis & Blanchet, Pierre, 2019. "Robustness of energy consumption and comfort in high-performance residential building with respect to occupant behavior," Energy, Elsevier, vol. 188(C).
    15. Piselli, Cristina & Pisello, Anna Laura, 2019. "Occupant behavior long-term continuous monitoring integrated to prediction models: Impact on office building energy performance," Energy, Elsevier, vol. 176(C), pages 667-681.
    16. Dixon, Gene & Abdel-Salam, Tarek & Kauffmann, Paul, 2010. "Evaluation of the effectiveness of an energy efficiency program for new home construction in eastern North Carolina," Energy, Elsevier, vol. 35(3), pages 1491-1496.
    17. Sun, Yannan & Hao, Weituo & Chen, Yan & Liu, Bing, 2020. "Data-driven occupant-behavior analytics for residential buildings," Energy, Elsevier, vol. 206(C).
    18. Chen Xu & Yu Li & Xueting Jin & Liang Yuan & Hao Cheng, 2017. "A Real-Time Energy Consumption Simulation and Comparison of Buildings in Different Construction Years in the Olympic Central Area in Beijing," Sustainability, MDPI, vol. 9(12), pages 1-18, December.

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