Method for Scalable and Automatised Thermal Building Performance Documentation and Screening
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Department of Applied Mathematics and Computer Science, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark
2
ENFOR A/S, Lyngsø Allé 3, 2970 Hørsholm, Denmark
*
Author to whom correspondence should be addressed.
Energies 2020, 13(15), 3866; https://doi.org/10.3390/en13153866
Received: 29 May 2020
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Revised: 13 July 2020
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Accepted: 20 July 2020
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Published: 28 July 2020
(This article belongs to the Special Issue Building Energy Performance Measurement and Analysis)
In Europe, more and more data on building energy use will be collected in the future as a result of the energy performance of buildings directive (EPBD), issued by the European Union. Moreover, both at European level and globally it became evident that the real energy performance of new buildings and the existing building stock needs to be documented better. Such documentation can, for example, be done with data-driven methods based on mathematical and statistical approaches. Even though the methods to extract energy performance characteristics of buildings are numerous, they are of varying reliability and often associated with a significant amount of human labour, making them hard to apply on a large scale. A classical approach to identify certain thermal performance parameters is the energy signature method. In this study, an automatised, nonlinear and smooth approach to the well-known energy signature is proposed, to quantify key thermal building performance parameters. The research specifically aims at describing the linear and nonlinear heat usage dependency on outdoor temperature, wind and solar irradiation. To make the model scalable, we realised it so that it only needs the daily average heat use of buildings, the outdoor temperature, the wind speed and the global solar irradiation. The results of applying the proposed method on heat consumption data from 16 different and randomly selected Danish occupied houses are analysed.
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Keywords:
thermal building performance; data-driven energy performance documentation and screening; energy signature; occupants effect on heat consumption
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MDPI and ACS Style
Rasmussen, C.; Bacher, P.; Calì, D.; Nielsen, H.A.; Madsen, H. Method for Scalable and Automatised Thermal Building Performance Documentation and Screening. Energies 2020, 13, 3866. https://doi.org/10.3390/en13153866
AMA Style
Rasmussen C, Bacher P, Calì D, Nielsen HA, Madsen H. Method for Scalable and Automatised Thermal Building Performance Documentation and Screening. Energies. 2020; 13(15):3866. https://doi.org/10.3390/en13153866
Chicago/Turabian StyleRasmussen, Christoffer, Peder Bacher, Davide Calì, Henrik A. Nielsen, and Henrik Madsen. 2020. "Method for Scalable and Automatised Thermal Building Performance Documentation and Screening" Energies 13, no. 15: 3866. https://doi.org/10.3390/en13153866
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