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Journal article

Statistical analysis of drivers of residential peak electricity demand

16 Feb 2017
Description

    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.

    Highlights of this article:

    • Study quantifies how factors drive residential summer peak electricity demand.
    • Based on detailed demographic and housing survey of over 3000 households.
    • Model shows good fit with aggregated household consumption on multiple peaks.
    • Findings highlight key contribution of high temperatures and ducted AC to peak.
    • Findings: play a key role in advising decision and policy making for peak shaving.

    Keywords: Peak demand; Residential; Electricity demand; Energy demand; Smart grid; Peak load; Influence; Factors

    Publication Details
    Identifiers: 
    DOI: 
    10.1016/j.enbuild.2017.02.030
    ISSN: 
    0378-7788
    Volume: 
    141
    Pagination: 
    205-217
    Access Rights Type: 
    Language: 
    License Type: 
    All Rights Reserved
    Published year only: 
    2017
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