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Building-PROFet: A scalable data-driven modelling approach for estimating heat and electricity load profiles of buildings

Author

Listed:
  • Smertinas, Justinas
  • Walnum, Harald Taxt
  • Ludvigsen, Bjørn
  • Sørensen, Åse Lekang
  • Sartori, Igor
  • Madsen, Henrik

Abstract

The rapid roll-out of smart meters in Scandinavia has enabled granular energy monitoring across building stocks, yet the tools to translate this data into actionable insights remain limited. To address this gap, this work presents Building-PROFet, a modular and scalable framework for estimating hourly heat and electricity demand profiles in buildings. The model builds upon Energy Signature (ES) techniques, introducing physically interpretable building parameters and extending them with periodicity adjustments and additional weather variables, such as wind speed and solar irradiance. A clear separation between estimation and prediction stages enhances model transparency and supports robust forecasts across temporal scales.

Suggested Citation

  • Smertinas, Justinas & Walnum, Harald Taxt & Ludvigsen, Bjørn & Sørensen, Åse Lekang & Sartori, Igor & Madsen, Henrik, 2026. "Building-PROFet: A scalable data-driven modelling approach for estimating heat and electricity load profiles of buildings," Energy, Elsevier, vol. 353(C).
    • Handle: RePEc:eee:energy:v:353:y:2026:i:c:s0360544226009175
    DOI: 10.1016/j.energy.2026.140814
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