Deployment of rooftop photovoltaics (PV) is technically constrained by the availability of suitable roof space as well as by the ability of the distribution network to absorb exported generation. Although Australian rooftop PV installations are at record levels, deployment is uneven across different building types, with commercial, industrial and multi-occupancy residential buildings lagging behind the world-leading penetration on detached residential buildings. An understanding of the amount and distribution of usable rooftop space on different building classifications is therefore useful in guiding appropriate policy incentives to increase deployment, as well as in network planning. The APVI Solar Potential Tool (SunSPoT) contributes to this understanding by using 3D building models or LiDAR building elevation data, vegetation layers and weather data to calculate the rooftop solar potential of specific buildings. This method has been extended in a number of APVI reports to calculate the rooftop solar potential in some of Australia’s major urban centres using both 3D building models and low-resolution LiDAR data.
In this study, the authors combine these methods with residential building classification data to determine utilisation factors (the proportion of a building’s roof area that is usable for PV deployment) for different types of residential building. The potential PV capacity per dwelling and an estimate for the potential capacity per unit of floor area is also calculated for different classes of residential building. These results are combined with Australian Bureau of Statistics (ABS) census data to estimate the total residential potential for different dwelling types in each state or territory. National residential solar potential is estimated to be between 43GWp and 61GWp, of which 6.5% is on multi-occupancy buildings.
As well as the slope and orientation of the roof planes and the degree of shading from neighbouring buildings and trees, utilisation factors are also affected by the presence of rooftop obstructions (such as air-conditioning units, skylights, perimeter walls, access equipment) which are not always captured by 3D models or low-resolution LiDAR data. Using high-resolution aerial imagery, we visually assess the roofs of case study buildings to better understand the effect of these factors.