Statistical analysis of drivers of residential peak electricity demand

Abstract Growth in peak electricity demand poses considerable challenges for utilities seeking to ensure secure, reliable yet affordable energy provision. A better understanding of the key drivers of residential peak electricity demand could assist in better managing peak demand growth through options including demand-side participation and energy efficiency programs. However, such analysis has often been constrained by the limited data available from standard household metering, as well as typically low direct engagement by utilities with households regarding their energy use. This paper presents a study analysing and modeling residential peak demand in the greater Sydney region using data from Australia’s largest Smart Grid study to date. The dataset includes household level half hour consumption matched to surveyed information including housing type, demographics and appliance ownership. A range of statistical and modeling techniques are applied to determine key drivers for household demand at times of network peaks. The analysis and model quantify how different factors drive residential peak demand on hot summer days. Key drivers identified include air-conditioning ownership, the number of household occupants, swimming pool ownership, and clothes dryer usage. Finally, the model is used to investigate the potential aggregate network peak implications of changes in household demographics and appliance ownership.

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