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Integration of Measurements and Time Diaries as Complementary Measures to Improve Resolution of BES

Author

Listed:
  • Jakob Carlander

    (Division of Building, Energy and Environment Technology, Department of Technology and Environment, University of Gävle, 80176 Gävle, Sweden)

  • Kristina Trygg

    (Technology and Social Change, Linköping University, 58183 Linköping, Sweden)

  • Bahram Moshfegh

    (Division of Building, Energy and Environment Technology, Department of Technology and Environment, University of Gävle, 80176 Gävle, Sweden
    Division of Energy Systems, Department of Management and Engineering, Linköping University, 58183 Linköping, Sweden)

Abstract

Building energy simulation (BES) models rely on a variety of different input data, and the more accurate the input data are, the more accurate the model will be in predicting energy use. The objective of this paper is to show a method for obtaining higher accuracy in building energy simulations of existing buildings by combining time diaries with data from logged measurements, and also to show that more variety is needed in template values of user input data in different kinds of buildings. The case studied in this article is a retirement home in Linköping, Sweden. Results from time diaries and interviews were combined with logged measurements of electricity, temperature, and CO 2 levels to create detailed occupant behavior schedules for use in BES models. Two BES models were compared, one with highly detailed schedules of occupancy, electricity use, and airing, and one using standardized input data of occupant behavior. The largest differences between the models could be seen in energy losses due to airing and in household electricity use, where the one with standardized user input data had a higher amount of electricity use and less losses due to airing of 39% and 99%, respectively. Time diaries and interviews, together with logged measurements, can be great tools to detect behavior that affects energy use in buildings. They can also be used to create detailed schedules and behavioral models, and to help develop standardized user input data for more types of buildings. This will help improve the accuracy of BES models so the energy efficiency gap can be reduced.

Suggested Citation

  • Jakob Carlander & Kristina Trygg & Bahram Moshfegh, 2019. "Integration of Measurements and Time Diaries as Complementary Measures to Improve Resolution of BES," Energies, MDPI, vol. 12(11), pages 1-29, May.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:11:p:2072-:d:235754
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    References listed on IDEAS

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    3. Marianne Abramsson & Eva Andersson, 2012. "Residential Mobility Patterns of Elderly—Leaving the House for an Apartment," Housing Studies, Taylor & Francis Journals, vol. 27(5), pages 582-604.
    4. Ellegård, Kajsa & Palm, Jenny, 2011. "Visualizing energy consumption activities as a tool for making everyday life more sustainable," Applied Energy, Elsevier, vol. 88(5), pages 1920-1926, May.
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    Cited by:

    1. Lukas Lundström & Jan Akander, 2019. "Bayesian Calibration with Augmented Stochastic State-Space Models of District-Heated Multifamily Buildings," Energies, MDPI, vol. 13(1), pages 1-28, December.
    2. Jakob Carlander & Bahram Moshfegh & Jan Akander & Fredrik Karlsson, 2020. "Effects on Energy Demand in an Office Building Considering Location, Orientation, Façade Design and Internal Heat Gains—A Parametric Study," Energies, MDPI, vol. 13(23), pages 1-22, November.

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