Statistical analysis of driving factors of residential energy demand in the greater Sydney region, Australia

• Study using empirical individual residential data span across more than 1 year.
• Study based on 3446 households’ survey matched with half-hour electricity reading.
• Households with ducted AC shown increase of demand by 6.5 kW h/day.
• Households with a pool shown an increase of demand over 8 kW h/day.
• Households with gas hot water show a decrease in demand over 3.7 kW h/day.

The residential sector represents some 30% of global electricity consumption but the underlying composition and drivers are still only poorly understood. The drivers are many, varied, and complex, including local climate, household demographics, household behaviour, building stock and the type and number of appliances. There is considerable variation across households and, until recently, often a lack of good data. This study draws upon a detailed household dataset from the Australian Smart Grid Smart City project to build a household electricity consumption model. A statistical linear regression model for household energy demand was established and tested for both individual households and regional aggregations of households. The model showed only reasonable performance in forecasting the consumption of individual households – highlighting the influence of factors beyond those surveyed – but good performance for aggregated household consumption. Models such as this would seem highly useful for a range of stakeholders including individual households trying to understand the potential implications of different choices, utilities looking to better forecast the impact of different possible residential trends and policy makers seeking to assist households in improving their energy efficiency through targeted policies and programs.