When we talk about how much energy our homes in Australia and New Zealand consume, chances are the data underpinning those discussions comes from the Residential Baseline Study (RBS). As highlighted in the recent methodology report for the 2021 update (RBS2.0), this study is a bottom-up engineering, end-use energy model of our residential sectors. Essentially, it builds up a picture of total energy use by looking at all the different appliances and equipment in our homes, their efficiency, and how we use them. This detailed approach allows researchers and policymakers to understand the contribution of individual end-uses and product groups to our national energy consumption.
Thinking beyond just measuring current consumption, what if we could design our homes to better manage energy peaks? The RBS2.0 methodology does look at modelling potential residential electricity peak demand. While the provided excerpts don’t show a specific graph illustrating typical peak duration, this kind of analysis – understanding when and how high those peaks are – is crucial. If we think about the duck curve (where the electricity demand in homes is shaped like a duck) shown in the graph below – knowing it is heavily shaped by water heating and space heating we can focus on flattening those demands. If we build homes that stay warm all day and night (rather than heating them up when wake up and again when we get home) this shifts the demand meaning we can potentially not upgrade the electrical grid – saving our society a huge investment.
This data is averages and it’s hard to map it to design choices on individual homes but if you want data with energy use by category and over time (not just annual) it’s the best place I know to go looking.
It raises an interesting question: could we leverage the thermal lag inherent in a well-insulated home to naturally balance energy consumption? The idea would be to design buildings with enough thermal mass and insulation so that even during peak demand periods, the indoor temperature only drops by a small amount – say, from 22 to 20 degrees Celsius – over the duration of that peak. The RBS model, with its ability to analyse building shell efficiency separately from appliance efficiency, could theoretically be used to explore the impact of different building designs on this thermal lag.
While water heating with storage tanks offers a degree of energy balancing, the focus here is on the building fabric itself. This concept of using the home as a thermal battery leads us to consider actual batteries. The RBS methodology doesn’t delve deeply into the economics of battery storage, but it does acknowledge the increasing relevance of battery storage in residential energy use. From an environmental perspective, the logic is clear: the priority should be on decarbonising electricity generation by offsetting fossil fuels to zero before heavily investing in batteries solely for grid stabilisation or individual household economics.
The financial viability of batteries often comes down to simple economics. Do the savings from using stored energy outweigh the upfront and lifecycle costs of the battery? However, the most significant environmental impact comes from reducing our reliance on carbon-intensive generation. The RBS, in its projections of energy consumption, provides a vital tool for understanding how different technologies and policies, including the growth of solar PV and potentially battery storage, could contribute to that goal.
Ultimately, understanding the granular detail provided by the RBS is the first step in exploring innovative solutions like leveraging thermal lag and strategically deploying battery storage to create a more balanced and sustainable residential energy system.