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Modeling hourly consumption of electricity and district heat in non-residential buildings

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  • Kipping, A.
  • Trømborg, E.

Abstract

Models for hourly consumption of heat and electricity in different consumer groups on a regional level can yield important data for energy system planning and management. In this study hourly meter data, combined with cross-sectional data derived from the Norwegian energy label database, is used to model hourly consumption of both district heat and electrical energy in office buildings and schools which either use direct electric heating (DEH) or non-electric hydronic heating (OHH). The results of the study show that modeled hourly total energy consumption in buildings with DEH and in buildings with OHH (supplied by district heat) exhibits differences, e.g. due to differences in heat distribution and control systems. In a normal year, in office buildings with OHH the main part of total modeled energy consumption is used for electric appliances, while in schools with OHH the main part is used for heating. In buildings with OHH the share of modeled annual heating energy is higher than in buildings with DEH. Although based on small samples our regression results indicate that the presented method can be used for modeling hourly energy consumption in non-residential buildings, but also that larger samples and additional cross-sectional information could yield improved models and more reliable results.

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  • 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.
    • Handle: RePEc:eee:energy:v:123:y:2017:i:c:p:473-486
    DOI: 10.1016/j.energy.2017.01.108
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    References listed on IDEAS

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    Cited by:

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    6. Ioakimidis, Christos S. & Thomas, Dimitrios & Rycerski, Pawel & Genikomsakis, Konstantinos N., 2018. "Peak shaving and valley filling of power consumption profile in non-residential buildings using an electric vehicle parking lot," Energy, Elsevier, vol. 148(C), pages 148-158.
    7. Lizana, Jesus & Serrano-Jimenez, Antonio & Ortiz, Carlos & Becerra, Jose A. & Chacartegui, Ricardo, 2018. "Energy assessment method towards low-carbon energy schools," Energy, Elsevier, vol. 159(C), pages 310-326.
    8. Adeoye, Omotola & Spataru, Catalina, 2019. "Modelling and forecasting hourly electricity demand in West African countries," Applied Energy, Elsevier, vol. 242(C), pages 311-333.
    9. Paul Anton Verwiebe & Stephan Seim & Simon Burges & Lennart Schulz & Joachim Müller-Kirchenbauer, 2021. "Modeling Energy Demand—A Systematic Literature Review," Energies, MDPI, vol. 14(23), pages 1-58, November.
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