Impact of Actual Weather Datasets for Calibrating White-Box Building Energy Models Base on Monitored Data

Vicente Gutiérrez González, Germán Ramos Ruiz and Carlos Fernández Bandera
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Vicente Gutiérrez González: School of Architecture, University of Navarra, 31009 Pamplona, Spain
Germán Ramos Ruiz: School of Architecture, University of Navarra, 31009 Pamplona, Spain
Carlos Fernández Bandera: School of Architecture, University of Navarra, 31009 Pamplona, Spain

Energies, 2021, vol. 14, issue 4, 1-16

Abstract: The need to reduce energy consumption in buildings is an urgent task. Increasing the use of calibrated building energy models (BEM) could accelerate this need. The calibration process of these models is a highly under-determined problem that normally yields multiple solutions. Among the uncertainties of calibration, the weather file has a primary position. The objective of this paper is to provide a methodology for selecting the optimal weather file when an on-site weather station with local sensors is available and what is the alternative option when it is not and a mathematically evaluation has to be done with sensors from nearby stations (third-party providers). We provide a quality assessment of models based on the Coefficient of Variation of the Root Mean Square Error (CV(RMSE)) and the Square Pearson Correlation Coefficient ( R 2 ). The research was developed on a control experiment conducted by Annex 58 and a previous calibration study. This is based on the results obtained with the study case based on the data provided by their N2 house.

Keywords: weather data; calibration; sensors; energy simulation; sensors saving; methodology; Building Energy Models (BEMs) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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