Energy Efficient Homes

To find the region with the most energy-efficient homes in Australia, we analysed every Local Government Area (LGA) across the country with at least 750 dwellings (a total of 452 areas), scoring each one across six categories that collectively determine how much energy a home is likely to use. The index draws on data from eight independent sources, including the Australian Photovoltaic Institute (APVI), the Clean Energy Regulator, the CSIRO, the Bureau of Meteorology, and the Australian Bureau of Statistics, with all figures representing the most recently available data at the time of analysis.

Renewable Energy Adoption (35%) is the biggest driver in the index, reflecting the central role solar technology plays in reducing household energy bills. This category combines three metrics: the percentage of dwellings in each LGA with a rooftop solar PV system installed (sourced from the APVI), the average solar generating capacity per dwelling in kilowatts (also APVI), and the proportion of homes fitted with a solar water heater or air source heat pump (sourced from the Clean Energy Regulator). LGAs where solar adoption is widespread and generating capacity is high scored strongly here.

Residential Construction Efficiency (25%) looks at the quality of new homes being built in each area, using two metrics from the CSIRO Australian Housing Data portal. The first is the average NatHERS energy star rating of new homes, a nationally recognised rating out of ten that measures how much energy a home needs for heating and cooling based on its design, orientation, and materials. The second is average floor area: all else being equal, larger homes cost more to heat and cool, so this acts as a proxy for the inherent energy demand of new residential construction. To ensure reliable averages, LGAs with fewer than 30 NatHERS certificates were excluded from this category.

Legacy Housing Stock (15%) captures the drag that older housing places on energy efficiency. Homes built before 1980 predate the introduction of minimum energy efficiency standards in Australian building codes and are significantly more likely to have inadequate insulation, single-glazed windows, and outdated heating and cooling systems. Using building counts from the Geoscience Australia National Exposure Information System, we calculated the number of pre-1980 structures per 1,000 residents in each LGA. Areas carrying a heavy legacy burden score lower, reflecting the structural inefficiency of their existing housing stock.

Urban Form and Density (15%) reflects the energy efficiency gains associated with compact, higher-density housing. Apartments and townhouses typically use less energy per household than detached homes, share walls that reduce heat loss, and tend to sit in areas with more efficient infrastructure. This category combines dwelling density, the number of dwellings per square kilometre, with the proportion of compact or higher-density dwellings in each LGA, both sourced from the ABS 2021 Census.

Environmental Efficiency (5%) measures tree canopy coverage: the proportion of each LGA covered by woody vegetation taller than two metres, drawn from the Terrestrial Ecosystem Research Network (TERN) 2025 Woody Canopy Cover dataset. Canopy cover reduces the urban heat island effect — the tendency of built-up areas to retain heat — thereby lowering cooling demand during summer. LGAs with higher canopy coverage score better on this measure.

Climate Adjustment (5%) ensures LGAs are not disadvantaged simply for being located in a hotter or colder part of the country. Using gridded climate data from the Bureau of Meteorology’s Australian Gridded Climate Dataset, representing the 30-year average from 1991 to 2020, we calculated total annual degree days for each LGA, combining both heating degree days (how much warming is needed in cooler periods) and cooling degree days (how much cooling is needed in warmer periods) at a base temperature of 18°C. This provides a single figure for the total thermal demand of each area’s climate, which is factored into the final score to account for regional differences in geography.

Scoring and Comparability

All metrics were normalised to a score out of 100 using min-max normalisation, rescaling each value relative to the best and worst performing LGA in the dataset. For metrics where a lower value is better, such as floor area and pre-1980 buildings, scoring is inverted so that smaller values produce higher scores. Four metrics with heavily skewed distributions, including dwelling density and legacy housing stock, had a log transformation applied before normalisation to prevent extreme outliers from compressing the scores of the majority of LGAs. Where an LGA had no data for a particular metric, that metric was excluded, and the remaining metrics were reweighted proportionally, ensuring all LGAs remain comparable. Final scores were standardised across the full dataset using z-score normalisation, meaning every score reflects an LGA’s performance relative to all others, and is not an absolute measure of energy efficiency.

Median House Prices

Median house prices are included as a supplementary data point to contextualise the cost of living in Australia’s most and least energy-efficient areas. Figures represent the median sale price for all dwelling types and bedroom configurations combined, sourced from Microburbs as a rolling median as at June 2025. Where insufficient transaction volume exists to produce a reliable median, no price is recorded for that LGA. House price data is not used in the calculation of the Energy Efficiency Index and is provided for contextual purposes only.