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Hourly electricity consumption in Norwegian households – Assessing the impacts of different heating systems

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  • Kipping, A.
  • Trømborg, E.

Abstract

This paper analyzes how different heating systems affect hourly electricity consumption in detached houses in Norway. Hourly electricity meter data, weather data, and response data from a household survey are merged into a large panel data set, and multiple regression models are applied to isolate the impacts of different heating systems for each hour of the day during the heating period. The results show that compared to direct electric heating, the additional use of air-to-air heat pumps, wood burning stoves, and oil stoves leads to relatively constant reductions in hourly electricity consumption over the course of the day while largest reductions – especially during hours of morning peak consumption – are achieved by using non-electric central heating systems. The presented method can be applied to other energy carriers, metering intervals and consumer groups and – depending on the data available – be used to model individual and aggregate regional energy demand with a high temporal resolution as well as to analyze how area-wide changes in climatic factors and important consumer characteristics will affect consumption of different energy carriers in smart energy systems.

Suggested Citation

  • Kipping, A. & Trømborg, E., 2015. "Hourly electricity consumption in Norwegian households – Assessing the impacts of different heating systems," Energy, Elsevier, vol. 93(P1), pages 655-671.
    • Handle: RePEc:eee:energy:v:93:y:2015:i:p1:p:655-671
    DOI: 10.1016/j.energy.2015.09.013
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    1. Andersen, F.M. & Gunkel, P.A. & Jacobsen, H.K. & Kitzing, L., 2021. "Residential electricity consumption and household characteristics: An econometric analysis of Danish smart-meter data," Energy Economics, Elsevier, vol. 100(C).
    2. Anna Kipping & Erik Trømborg, 2017. "Modeling Aggregate Hourly Energy Consumption in a Regional Building Stock," Energies, MDPI, vol. 11(1), pages 1-20, December.
    3. Angreine Kewo & Pinrolinvic D. K. Manembu & Per Sieverts Nielsen, 2020. "Synthesising Residential Electricity Load Profiles at the City Level Using a Weighted Proportion (Wepro) Model," Energies, MDPI, vol. 13(14), pages 1-28, July.
    4. Nick MacMackin, & Miller, Lindsay & Carriveau, Rupp, 2019. "Modeling and disaggregating hourly effects of weather on sectoral electricity demand," Energy, Elsevier, vol. 188(C).
    5. Angreine Kewo & Pinrolinvic D. K. Manembu & Per Sieverts Nielsen, 2023. "A Rigorous Standalone Literature Review of Residential Electricity Load Profiles," Energies, MDPI, vol. 16(10), pages 1-27, May.
    6. Kipping, A. & Trømborg, E., 2017. "Modeling hourly consumption of electricity and district heat in non-residential buildings," Energy, Elsevier, vol. 123(C), pages 473-486.
    7. John Clauß & Sebastian Stinner & Christian Solli & Karen Byskov Lindberg & Henrik Madsen & Laurent Georges, 2019. "Evaluation Method for the Hourly Average CO 2eq. Intensity of the Electricity Mix and Its Application to the Demand Response of Residential Heating," Energies, MDPI, vol. 12(7), pages 1-25, April.
    8. Söder, Lennart & Lund, Peter D. & Koduvere, Hardi & Bolkesjø, Torjus Folsland & Rossebø, Geir Høyvik & Rosenlund-Soysal, Emilie & Skytte, Klaus & Katz, Jonas & Blumberga, Dagnija, 2018. "A review of demand side flexibility potential in Northern Europe," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 654-664.
    9. Romero-Jordán, Desiderio & del Río, Pablo, 2022. "Analysing the drivers of the efficiency of households in electricity consumption," Energy Policy, Elsevier, vol. 164(C).
    10. Gouveia, João Pedro & Seixas, Júlia & Mestre, Ana, 2017. "Daily electricity consumption profiles from smart meters - Proxies of behavior for space heating and cooling," Energy, Elsevier, vol. 141(C), pages 108-122.
    11. Palacios-Garcia, E.J. & Moreno-Munoz, A. & Santiago, I. & Flores-Arias, J.M. & Bellido-Outeirino, F.J. & Moreno-Garcia, I.M., 2018. "A stochastic modelling and simulation approach to heating and cooling electricity consumption in the residential sector," Energy, Elsevier, vol. 144(C), pages 1080-1091.
    12. Erik Dahlquist & Fredrik Wallin & Koteshwar Chirumalla & Reza Toorajipour & Glenn Johansson, 2023. "Balancing Power in Sweden Using Different Renewable Resources, Varying Prices, and Storages Like Batteries in a Resilient Energy System," Energies, MDPI, vol. 16(12), pages 1-28, June.
    13. Lund, Henrik & Østergaard, Poul Alberg & Connolly, David & Mathiesen, Brian Vad, 2017. "Smart energy and smart energy systems," Energy, Elsevier, vol. 137(C), pages 556-565.
    14. Gibbons, Laurence & Javed, Saqib, 2022. "A review of HVAC solution-sets and energy performace of nearly zero-energy multi-story apartment buildings in Nordic climates by statistical analysis of environmental performance certificates and lite," Energy, Elsevier, vol. 238(PA).

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