Residential Operational Energy Use

Abstract

Despite decades of debate in urban research about the effect of built form on household energy use, the empirical research on the topic is still far from conclusive. Many studies rely on small samples and fail to control for crucial variables such as household income. This article describes a detailed analysis of household energy use in Sydney that controls for major household demographic and income variables. The results demonstrate that appliance ownership, household size, dwelling size and dwelling type all affect energy consumption. Importantly, from a planning perspective, energy use in low-rise attached dwellings, after controlling for other factors, is estimated as 15–20 per cent lower than detached dwellings with the same number of bedrooms.

Keywords:

• Household energy use
• residential energy use

Acknowledgements

The author would like to thank two anonymous reviewers for providing detailed feedback. The author would also like to thank Paul Myors from Energy Australia and Bee Thompson from IPART for providing data for the study. Thanks to Peter Maganov from Randwick City Council for providing access to energy-survey data. Both UTS and CSIRO provided funding to support this research.

Notes

 1. NatHERS stands for Nationwide Housing Energy Rating Scheme. Details about the scheme, and the software (such as NatHERS, BERS and AccuRate) used in rating dwelling energy efficiency, can be found at http://www.nathers.gov.au/software/index.html

 2. Personal communication with Rob Helstroom, of the NSW BASIX team, 23 April 2006.

 3. Some appliance ownership information was available, but, after experiment, it became clear that it was not possible to use this to estimate a CDA-style regression model.

 4. Households were excluded on the basis of such irregularities as having self-reported gas consumption but zero gas consumption obtained from the utility company.

 5. That is, coefficients for variables that have been transformed to have zero mean and unit variance.

 6. The models without interaction terms are chosen because of the difficulty in interpreting unit changes in interacted variables.

 7. Data generally available from the ABS and other sources usually provide average floor space for detached/other dwellings, so do not allow for a direct comparison, as detached dwellings have more bedrooms on average than attached dwellings. Thus, while most would accept that a unit will be smaller than a house with the same number of bedrooms, the 20 per cent figure quoted is based solely on the author's judgement.

 8. Appliances differ in their end-use efficiency, and the fuel source used is often an important factor influencing the end-use efficiency of an appliance. For example, a gas water heater usually requires more MJ of energy to keep the same volume of water hot than does an electric water heater.

 9. The argument from economic theory is straightforward—high land values encourage the substitution of capital for land, to allow greater utilisation of expensive land. This means increased development intensity. There is ample empirical evidence to support the theory; see, for example, Bertaud and Malpezzi (2003).

10. This trend is strongest in Sydney, where Lenzen et al.'s work (2004) was conducted, but is also true in Canberra, where Foran performed his analysis.