Method for Probabilistic Energy Calculations—Passive House Case Study

  • Stephen BurkeEmail author
  • Johnny Kronvall
  • Magnus Wiktorsson
  • Per Sahlin
  • Anders Ljungberg
Conference paper
Part of the Springer Proceedings in Energy book series (SPE)


Swedish building regulations require proof that a building fulfills a specific energy use during the design stage. This is done by doing an energy calculation. The result of this calculation is always reported to the nearest integer, for example an energy calculation of a building might predict that it should use 89 kWh/m2 year when the building regulation limits the actual energy use to maximum 90 kWh/m2 year. This can lead to conflicts if the measured energy use is greater than the calculated energy use. With the currently available energy calculation tools, if you want to see which risks are associated to the design and material properties, you need to do a parametric study. These types of studies are usually time consuming. Investigations of different buildings show that energy measurements can vary significantly in identical houses. To take into account these differences and avoid costly parametric studies, it is common to add an uncertainty factor to the calculated results. In the project, “Calculation method for probabilistic energy use in buildings” two commercial energy calculation programs developed in Sweden were modified to use Monte Carlo simulations. This method was then tested using a passive house design which was used in the Vallda Heberg passive house development. The calculation results were then compared with the actual measured energy. The results show that a variation of 15 input parameters could explain most of the difference between measured energy use and calculated energy use. The results from the probabilistic energy calculation even showed that the original energy calculation was on the high-end of the calculated energy distribution. It showed that the probability that the measured energy use would fulfil the Swedish building code was over 95%.


Energy simulations IDA-ICE VIP energy Statistical input Monte Carlo Verification 



The authors would like to thank SBUF (the Swedish construction industry’s organization for research and development), the Swedish Energy Agency under the research programme E2B2, NCC, StruSoft, Equa Simulations AB, Lund University, WSP Sverige AB, FOJAB Architects, Chalmers Real Estate AB, PEAB, Skanska and The Swedish National Board of Housing, Building and Planning for their time and funding, without which this project would not be possible.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Stephen Burke
    • 1
    Email author
  • Johnny Kronvall
    • 2
  • Magnus Wiktorsson
    • 3
  • Per Sahlin
    • 4
  • Anders Ljungberg
    • 5
  1. 1.NCC Sverige ABMalmöSweden
  2. 2.StruSoft ABMalmöSweden
  3. 3.Lund UniversityLundSweden
  4. 4.EQUA Simulations ABStockholmSweden
  5. 5.NCC Sverige ABGöteborgSweden

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