IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i12p2908-d1414006.html

Constructing Australian Residential Electricity Load Profile for Supporting Future Network Studies

Author

Listed:
  • Umme Mumtahina

    (School of Engineering and Technology, Central Queensland University, Rockhampton 4701, Australia)

  • Sanath Alahakoon

    (School of Engineering and Technology, Central Queensland University, Rockhampton 4701, Australia)

  • Peter Wolfs

    (School of Engineering and Technology, Central Queensland University, Rockhampton 4701, Australia)

  • Jiannan Liu

    (EleXsys Ptd Ltd., Brisbane 4072, Australia)

Abstract

This paper examines how Australian residential load profiles may evolve in the short to medium term future. These profiles can be used to support simulation studies of the future Australian network within an environment that is transitioning to renewable energy and broader use of electricity as a tool for decarbonisation. The daily profiles rely heavily on the Australian Energy Market Operator (AEMO) forecasts for future annual energy usage. The period from 2024 to 2050 will be transformational. In the residential networks, two secular trends are particularly important in expanding residential generation and electrification. New daily load profiles have been constructed using historical Australian profiles and adding additional components for solar generation, battery operation and electrification activities. The entire aggregated residential network is expected to have reverse midday power flow on any average day from 2024 onwards due to the rapid increase in electric vehicle (EV) usage. The domestic energy demand forecasting methodology presented in this work related to Australia can easily be adopted to carry out similar forecasting for any country of the world.

Suggested Citation

  • Umme Mumtahina & Sanath Alahakoon & Peter Wolfs & Jiannan Liu, 2024. "Constructing Australian Residential Electricity Load Profile for Supporting Future Network Studies," Energies, MDPI, vol. 17(12), pages 1-14, June.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:12:p:2908-:d:1414006
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/12/2908/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/12/2908/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. McKenna, R. & Djapic, P. & Weinand, J. & Fichtner, W. & Strbac, G., 2018. "Assessing the implications of socioeconomic diversity for low carbon technology uptake in electrical distribution networks," Applied Energy, Elsevier, vol. 210(C), pages 856-869.
    2. Giasemidis, Georgios & Haben, Stephen & Lee, Tamsin & Singleton, Colin & Grindrod, Peter, 2017. "A genetic algorithm approach for modelling low voltage network demands," Applied Energy, Elsevier, vol. 203(C), pages 463-473.
    3. Qiu, Yueming Lucy & Wang, Yi David & Iseki, Hiroyuki & Shen, Xingchi & Xing, Bo & Zhang, Huiming, 2022. "Empirical grid impact of in-home electric vehicle charging differs from predictions," Resource and Energy Economics, Elsevier, vol. 67(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yamaguchi, Yohei & Shoda, Yuto & Yoshizawa, Shinya & Imai, Tatsuya & Perwez, Usama & Shimoda, Yoshiyuki & Hayashi, Yasuhiro, 2023. "Feasibility assessment of net zero-energy transformation of building stock using integrated synthetic population, building stock, and power distribution network framework," Applied Energy, Elsevier, vol. 333(C).
    2. Zou, Wenke & Sun, Yongjun & Gao, Dian-ce & Zhang, Xu & Liu, Junyao, 2023. "A review on integration of surging plug-in electric vehicles charging in energy-flexible buildings: Impacts analysis, collaborative management technologies, and future perspective," Applied Energy, Elsevier, vol. 331(C).
    3. Li, Yiqun & Pu, Ziyuan & Liu, Pei & Qian, Tao & Hu, Qinran & Zhang, Junyi & Wang, Yinhai, 2025. "Efficient predictive control strategy for mitigating the overlap of EV charging demand and residential load based on distributed renewable energy," Renewable Energy, Elsevier, vol. 240(C).
    4. Pampa Sinha & Kaushik Paul & Sanchari Deb & Sulabh Sachan, 2023. "Comprehensive Review Based on the Impact of Integrating Electric Vehicle and Renewable Energy Sources to the Grid," Energies, MDPI, vol. 16(6), pages 1-39, March.
    5. Ye, Tinghan & Liu, Shanshan & Kontou, Eleftheria, 2024. "Managed residential electric vehicle charging minimizes electricity bills while meeting driver and community preferences," Transport Policy, Elsevier, vol. 149(C), pages 122-138.
    6. Jansson, Evelina, 2025. "The impact of Electric Vehicle adoption on residential electricity consumption: Insights from Sweden," Energy Economics, Elsevier, vol. 152(C).
    7. Jiang, An & Qiu, Jiehong & Li, Aiyuan & Zhang, Guangnan, 2025. "An empirical analysis framework to evaluate the impact of residential electric vehicles on power grid," Transport Policy, Elsevier, vol. 173(C).
    8. Johannes Gessner & Wolfgang Habla & Benjamin Rübenacker & Ulrich J. Wagner, 2025. "No Place Like Home: Charging Infrastructure and the Environmental Advantage of Plug-in Hybrid Electric Vehicles," CRC TR 224 Discussion Paper Series crctr224_2025_663, University of Bonn and University of Mannheim, Germany, revised Apr 2026.
    9. Meunier, Simon & Protopapadaki, Christina & Baetens, Ruben & Saelens, Dirk, 2021. "Impact of residential low-carbon technologies on low-voltage grid reinforcements," Applied Energy, Elsevier, vol. 297(C).
    10. Wang, Yishi & Jin, Andrew S. & Sanders, Kelly T., 2026. "A systematic review of literature utilizing residential smart meter data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 225(C).
    11. Zou, Dexuan & Li, Steven & Kong, Xiangyong & Ouyang, Haibin & Li, Zongyan, 2019. "Solving the combined heat and power economic dispatch problems by an improved genetic algorithm and a new constraint handling strategy," Applied Energy, Elsevier, vol. 237(C), pages 646-670.
    12. Yueming (Lucy) Qiu & Nana Deng & Bo Wang & Xingchi Shen & Zhaohua Wang & Nathan Hultman & Han Shi & Jie Liu & Yi David Wang, 2024. "Power supply disruptions deter electric vehicle adoption in cities in China," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    13. Neves, Sónia Almeida & Pereira, Diogo Santos & Marques, António Cardoso, 2025. "Is electric mobility effective in smoothing the electricity load diagram? Evidence from Europe," Transport Policy, Elsevier, vol. 174(C).
    14. Ehsan, Ali & Preece, Robin, 2022. "Quantifying the impacts of heat decarbonisation pathways on the future electricity and gas demand," Energy, Elsevier, vol. 254(PA).
    15. Megan R. Bailey & David P. Brown & Blake C. Shaffer & Frank A. Wolak, 2023. "Show Me the Money! Incentives and Nudges to Shift Electric Vehicle Charge Timing," NBER Working Papers 31630, National Bureau of Economic Research, Inc.
    16. Spiller, Beia & Zhang, Roulin & Stein, Elizabeth & Kontou, Eleftheria & Yoshizumi, Alexander, 2025. "Impact of Electric Tariffs on Medium- and Heavy-Duty Vehicle Charging Costs and Loads," RFF Working Paper Series 25-22, Resources for the Future.
    17. Gharibvand, Hossein & Gharehpetian, G.B. & Anvari-Moghaddam, A., 2024. "A survey on microgrid flexibility resources, evaluation metrics and energy storage effects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 201(C).
    18. Leslie, Gordon W. & Pourkhanali, Armin & Roger, Guillaume, 2024. "Is the clean energy transition making fixed-rate electricity tariffs regressive?," Journal of Environmental Economics and Management, Elsevier, vol. 127(C).
    19. Marten Ovaere & Mark Vergouwen, 2025. "Capacity Constraints and Electrification: Evidence from Residential Electricity Demand and Pricing," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 25/1115, Ghent University, Faculty of Economics and Business Administration, revised Jun 2026.
    20. Xia, S.W. & Bu, S.Q. & Zhang, X. & Xu, Y. & Zhou, B. & Zhu, J.B., 2018. "Model reduction strategy of doubly-fed induction generator-based wind farms for power system small-signal rotor angle stability analysis," Applied Energy, Elsevier, vol. 222(C), pages 608-620.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:17:y:2024:i:12:p:2908-:d:1414006. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager The email address of this maintainer does not seem to be valid anymore. Please ask MDPI Indexing Manager to update the entry or send us the correct address (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.