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An Empirical Energy Demand Flexibility Metric for Residential Properties

Author

Listed:
  • Jenny Crawley

    (UCL Energy Institute, University College London, London WC1H 0NN, UK)

  • Despina Manouseli

    (UCL Energy Institute, University College London, London WC1H 0NN, UK)

  • Peter Mallaburn

    (UCL Energy Institute, University College London, London WC1H 0NN, UK)

  • Cliff Elwell

    (UCL Energy Institute, University College London, London WC1H 0NN, UK)

Abstract

Shifting from heating using fossil fuel combustion to electrified heating, dominated by heat pumps, is central to many countries’ decarbonisation strategy. The consequent increase in electricity demand, combined with that from electric vehicles, and the shift from non-renewable to renewable generation requires increased demand flexibility to support system operation. Demand side response through interrupting heating during peak demands has been widely proposed and simulation modelling has been used to determine the technical potential. This paper proposes an empirical approach to quantifying a building’s potential to operate flexibly, presenting a metric based on measured temperature drop in a dwelling under standard conditions after heating is switched off, using smart meter and internal temperature data. A result was derived for 96% of 193 homes within a test dataset, mean temperature drop of 1.5 °C in 3 h at 15 °C inside-outside temperature differential. An empirical flexibility metric may support decision making and decarbonisation. For households it may support the transition to heat pumps, enabling time of use costs and tariffs to be better understood and system to be specified by installers. Electricity system stakeholders, such as aggregators and DNOs may use it to identify the potential for demand response, managing local networks, infrastructure and aggregation.

Suggested Citation

  • Jenny Crawley & Despina Manouseli & Peter Mallaburn & Cliff Elwell, 2022. "An Empirical Energy Demand Flexibility Metric for Residential Properties," Energies, MDPI, vol. 15(14), pages 1-18, July.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:14:p:5304-:d:868429
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    References listed on IDEAS

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    2. Love, Jenny & Smith, Andrew Z.P. & Watson, Stephen & Oikonomou, Eleni & Summerfield, Alex & Gleeson, Colin & Biddulph, Phillip & Chiu, Lai Fong & Wingfield, Jez & Martin, Chris & Stone, Andy & Lowe, R, 2017. "The addition of heat pump electricity load profiles to GB electricity demand: Evidence from a heat pump field trial," Applied Energy, Elsevier, vol. 204(C), pages 332-342.
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    6. Jenny Crawley & Phillip Biddulph & Paul J. Northrop & Jez Wingfield & Tadj Oreszczyn & Cliff Elwell, 2019. "Quantifying the Measurement Error on England and Wales EPC Ratings," Energies, MDPI, vol. 12(18), pages 1-19, September.
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    Cited by:

    1. Elli Nikolaidou & Ian Walker & David Coley & Stephen Allen & Daniel Fosas & Matthew Roberts, 2022. "Towards Active Buildings: Stakeholder Perceptions of the Next Generation of Buildings," Energies, MDPI, vol. 15(15), pages 1-21, August.
    2. Paula Sankelo & Kaiser Ahmed & Alo Mikola & Jarek Kurnitski, 2022. "Renovation Results of Finnish Single-Family Renovation Subsidies: Oil Boiler Replacement with Heat Pumps," Energies, MDPI, vol. 15(20), pages 1-18, October.
    3. Lesley Thomson & David Jenkins, 2023. "The Use of Real Energy Consumption Data in Characterising Residential Energy Demand with an Inventory of UK Datasets," Energies, MDPI, vol. 16(16), pages 1-29, August.

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