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Weather Files for the Calibration of Building Energy Models

González, VG, Ruiz, GR, Du, H, Sánchez-Ostiz, A and Bandera, CF (2022) Weather Files for the Calibration of Building Energy Models. Applied Sciences, 12 (15). p. 7361.

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In the fight against climate change, energy modeling is a key tool used to analyze the performance of proposed energy conservation measures for buildings. Studies on the integration of photovoltaic energy in buildings must use calibrated building energy models, as only with them is the demand curve real, and the savings obtained at the self-consumption level, energy storage in the building, or feed into the grid are accurate. The adjustment process of a calibrated model depends on aspects inherent to the building properties (envelope parameters, internal loads, use schedules) as well as external to them (weather, ground properties, etc.). Naturally, the uncertainty of each is essential to obtaining good results. As for the meteorological data, it is preferable to use data from a weather station located in the building or its surroundings, although this is not always possible due to the cost of the initial investment and its maintenance. As a result, weather stations with public access to their data, such as those located at airports or specific locations in cities, are largely used to perform calibrations of building energy models, making it challenging to converge the simulated model with measured data. This research sheds light on how this obstacle can be overcome by using weather data provided by a third-party company, bridging the gap between reality and energy models. For this purpose, calibrations of the two buildings proposed in Annex 58 were performed with different weather configurations, using the mean absolute error (MAE) uncertainty index and Spearman’s rank correlation coefficient (rho) as comparative measures. An optimal and cost-effective solution was found as an alternative to an on-site weather station, based on the use of a single outdoor temperature sensor in combination with third-party weather data, achieving a robust and reliable building energy model.

Item Type: Article
Subjects: N Fine Arts > NA Architecture
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Civil Engineering & Built Environment
Publisher: MDPI AG
SWORD Depositor: A Symplectic
Date Deposited: 31 Aug 2022 08:03
Last Modified: 31 Aug 2022 08:03
DOI or ID number: 10.3390/app12157361
URI: https://researchonline.ljmu.ac.uk/id/eprint/17461
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