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Explaining domestic energy consumption – The comparative contribution of building factors, socio-demographics, behaviours and attitudes

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  • Huebner, Gesche M.
  • Hamilton, Ian
  • Chalabi, Zaid
  • Shipworth, David
  • Oreszczyn, Tadj

Abstract

This paper tests to what extent different types of variables (building factors, socio-demographics, attitudes and self-reported behaviours) explain annualized energy consumption in residential buildings, and goes on to show which individual variables have the highest explanatory power. In contrast to many other studies, the problem of multicollinearity between predictors is recognised, and addressed using Lasso regression to perform variable selection.

Suggested Citation

  • Huebner, Gesche M. & Hamilton, Ian & Chalabi, Zaid & Shipworth, David & Oreszczyn, Tadj, 2015. "Explaining domestic energy consumption – The comparative contribution of building factors, socio-demographics, behaviours and attitudes," Applied Energy, Elsevier, vol. 159(C), pages 589-600.
    • Handle: RePEc:eee:appene:v:159:y:2015:i:c:p:589-600
    DOI: 10.1016/j.apenergy.2015.09.028
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    References listed on IDEAS

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    1. Scott Kelly, 2011. "Do homes that are more energy efficient consume less energy?: A structural equation model for England's residential sector," Working Papers EPRG 1117, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    2. Liao, Huei-Chu & Chang, Tsai-Feng, 2002. "Space-heating and water-heating energy demands of the aged in the US," Energy Economics, Elsevier, vol. 24(3), pages 267-284, May.
    3. Vringer, Kees & Aalbers, Theo & Blok, Kornelis, 2007. "Household energy requirement and value patterns," Energy Policy, Elsevier, vol. 35(1), pages 553-566, January.
    4. Menezes, Anna Carolina & Cripps, Andrew & Bouchlaghem, Dino & Buswell, Richard, 2012. "Predicted vs. actual energy performance of non-domestic buildings: Using post-occupancy evaluation data to reduce the performance gap," Applied Energy, Elsevier, vol. 97(C), pages 355-364.
    5. Kelly, Scott, 2011. "Do homes that are more energy efficient consume less energy?: A structural equation model of the English residential sector," Energy, Elsevier, vol. 36(9), pages 5610-5620.
    6. Druckman, A. & Jackson, T., 2008. "Household energy consumption in the UK: A highly geographically and socio-economically disaggregated model," Energy Policy, Elsevier, vol. 36(8), pages 3167-3182, August.
    7. Palmborg, Christer, 1986. "Social habits and energy consumption in single-family homes," Energy, Elsevier, vol. 11(7), pages 643-650.
    8. Aydinalp, Merih & Ismet Ugursal, V. & Fung, Alan S., 2004. "Modeling of the space and domestic hot-water heating energy-consumption in the residential sector using neural networks," Applied Energy, Elsevier, vol. 79(2), pages 159-178, October.
    9. Fikru, Mahelet G. & Gautier, Luis, 2015. "The impact of weather variation on energy consumption in residential houses," Applied Energy, Elsevier, vol. 144(C), pages 19-30.
    10. Baker, Keith J. & Rylatt, R. Mark, 2008. "Improving the prediction of UK domestic energy-demand using annual consumption-data," Applied Energy, Elsevier, vol. 85(6), pages 475-482, June.
    11. Kialashaki, Arash & Reisel, John R., 2013. "Modeling of the energy demand of the residential sector in the United States using regression models and artificial neural networks," Applied Energy, Elsevier, vol. 108(C), pages 271-280.
    12. Abrahamse, Wokje & Steg, Linda, 2009. "How do socio-demographic and psychological factors relate to households' direct and indirect energy use and savings?," Journal of Economic Psychology, Elsevier, vol. 30(5), pages 711-720, October.
    13. Baglivo, Cristina & Congedo, Paolo Maria & D'Agostino, Delia & Zacà, Ilaria, 2015. "Cost-optimal analysis and technical comparison between standard and high efficient mono-residential buildings in a warm climate," Energy, Elsevier, vol. 83(C), pages 560-575.
    14. Hamilton, Ian G. & Steadman, Philip J. & Bruhns, Harry & Summerfield, Alex J. & Lowe, Robert, 2013. "Energy efficiency in the British housing stock: Energy demand and the Homes Energy Efficiency Database," Energy Policy, Elsevier, vol. 60(C), pages 462-480.
    15. Koo, Choongwan & Park, Sungki & Hong, Taehoon & Park, Hyo Seon, 2014. "An estimation model for the heating and cooling demand of a residential building with a different envelope design using the finite element method," Applied Energy, Elsevier, vol. 115(C), pages 205-215.
    16. Forouzanfar, Mehdi & Doustmohammadi, Ali & Menhaj, M. Bagher & Hasanzadeh, Samira, 2010. "Modeling and estimation of the natural gas consumption for residential and commercial sectors in Iran," Applied Energy, Elsevier, vol. 87(1), pages 268-274, January.
    17. Liu, Mingzhe & Wittchen, Kim Bjarne & Heiselberg, Per Kvols, 2015. "Control strategies for intelligent glazed façade and their influence on energy and comfort performance of office buildings in Denmark," Applied Energy, Elsevier, vol. 145(C), pages 43-51.
    18. Majcen, D. & Itard, L.C.M. & Visscher, H., 2013. "Theoretical vs. actual energy consumption of labelled dwellings in the Netherlands: Discrepancies and policy implications," Energy Policy, Elsevier, vol. 54(C), pages 125-136.
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