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Impact Assessment for Building Energy Models Using Observed vs. Third-Party Weather Data Sets

Author

Listed:
  • Eva Lucas Segarra

    (School of Architecture, University of Navarra, 31009 Pamplona, Spain
    These authors contributed equally to this work.)

  • Germán Ramos Ruiz

    (School of Architecture, University of Navarra, 31009 Pamplona, Spain
    These authors contributed equally to this work.)

  • Vicente Gutiérrez González

    (School of Architecture, University of Navarra, 31009 Pamplona, Spain)

  • Antonis Peppas

    (School of Mining and Metallurgical Engineering, National Technical University of Athens (NTUA), 15780 Athens, Greece)

  • Carlos Fernández Bandera

    (School of Architecture, University of Navarra, 31009 Pamplona, Spain)

Abstract

The use of building energy models (BEMs) is becoming increasingly widespread for assessing the suitability of energy strategies in building environments. The accuracy of the results depends not only on the fit of the energy model used, but also on the required external files, and the weather file is one of the most important. One of the sources for obtaining meteorological data for a certain period of time is through an on-site weather station; however, this is not always available due to the high costs and maintenance. This paper shows a methodology to analyze the impact on the simulation results when using an on-site weather station and the weather data calculated by a third-party provider with the purpose of studying if the data provided by the third-party can be used instead of the measured weather data. The methodology consists of three comparison analyses: weather data, energy demand, and indoor temperature. It is applied to four actual test sites located in three different locations. The energy study is analyzed at six different temporal resolutions in order to quantify how the variation in the energy demand increases as the time resolution decreases. The results showed differences up to 38% between annual and hourly time resolutions. Thanks to a sensitivity analysis, the influence of each weather parameter on the energy demand is studied, and which sensors are worth installing in an on-site weather station are determined. In these test sites, the wind speed and outdoor temperature were the most influential weather parameters.

Suggested Citation

  • Eva Lucas Segarra & Germán Ramos Ruiz & Vicente Gutiérrez González & Antonis Peppas & Carlos Fernández Bandera, 2020. "Impact Assessment for Building Energy Models Using Observed vs. Third-Party Weather Data Sets," Sustainability, MDPI, vol. 12(17), pages 1-27, August.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:17:p:6788-:d:402110
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    References listed on IDEAS

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    Cited by:

    1. Amin, Amin & Mourshed, Monjur, 2024. "Weather and climate data for energy applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    2. Vicente Gutiérrez González & Germán Ramos Ruiz & Carlos Fernández Bandera, 2021. "Impact of Actual Weather Datasets for Calibrating White-Box Building Energy Models Base on Monitored Data," Energies, MDPI, vol. 14(4), pages 1-16, February.

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