The effect of seasonal weather changes on the performance of databased models of the thermodynamic behaviour of buildings
Several studies have indicated that Model Predictive Control (MPC) of space heating systems can utilize the thermal mass of residential buildings as short-term thermal storage for various demand response purposes. Realization of this potential relies heavily on the accuracy of the model used to repr...
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2020-01-01
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doaj-31717d3cdeb24400a21931861bbccadc2021-04-02T16:33:08ZengEDP SciencesE3S Web of Conferences2267-12422020-01-011720200510.1051/e3sconf/202017202005e3sconf_nsb2020_02005The effect of seasonal weather changes on the performance of databased models of the thermodynamic behaviour of buildingsHauge Broholt Thea0Rævdal Lund Christensen Louise1Dahl Knudsen Michael2Elbæk Hedegaard Rasmus3Petersen Steffen4Aarhus University, Department of EngineeringAarhus University, Department of EngineeringAarhus University, Department of EngineeringAarhus University, Department of EngineeringAarhus University, Department of EngineeringSeveral studies have indicated that Model Predictive Control (MPC) of space heating systems can utilize the thermal mass of residential buildings as short-term thermal storage for various demand response purposes. Realization of this potential relies heavily on the accuracy of the model used to represent the thermodynamics of the building. Such models, whether they are grey box or black box, are calibrated using relevant data obtained from initial measurements, and the performance of the calibrated model is validated using data from a subsequent period. However, many studies use validation periods with weather conditions similar to those of the calibration period. Only a few studies investigate whether the calibrated model performs satisfactory when subjected to significantly different conditions. This paper presents data from a simulation-based study on the effect of seasonal weather changes on the performance of a black-box model. The study was conducted using 11 years of Danish weather data (2008-2018). The results indicate that the performance of the black-box model deteriorate as the weather data conditions become increasingly different from those used in the initial model calibration. Further, the results show that calibration in heating season leads to satisfactory model performance through the heating season, but lower performance in transitional seasons (especially spring). Results also show that calibration in February led to highest model performance through heating season, while calibration in March led to satisfactory model performance in the whole heating and fall season.https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/32/e3sconf_nsb2020_02005.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hauge Broholt Thea Rævdal Lund Christensen Louise Dahl Knudsen Michael Elbæk Hedegaard Rasmus Petersen Steffen |
spellingShingle |
Hauge Broholt Thea Rævdal Lund Christensen Louise Dahl Knudsen Michael Elbæk Hedegaard Rasmus Petersen Steffen The effect of seasonal weather changes on the performance of databased models of the thermodynamic behaviour of buildings E3S Web of Conferences |
author_facet |
Hauge Broholt Thea Rævdal Lund Christensen Louise Dahl Knudsen Michael Elbæk Hedegaard Rasmus Petersen Steffen |
author_sort |
Hauge Broholt Thea |
title |
The effect of seasonal weather changes on the performance of databased models of the thermodynamic behaviour of buildings |
title_short |
The effect of seasonal weather changes on the performance of databased models of the thermodynamic behaviour of buildings |
title_full |
The effect of seasonal weather changes on the performance of databased models of the thermodynamic behaviour of buildings |
title_fullStr |
The effect of seasonal weather changes on the performance of databased models of the thermodynamic behaviour of buildings |
title_full_unstemmed |
The effect of seasonal weather changes on the performance of databased models of the thermodynamic behaviour of buildings |
title_sort |
effect of seasonal weather changes on the performance of databased models of the thermodynamic behaviour of buildings |
publisher |
EDP Sciences |
series |
E3S Web of Conferences |
issn |
2267-1242 |
publishDate |
2020-01-01 |
description |
Several studies have indicated that Model Predictive Control (MPC) of space heating systems can utilize the thermal mass of residential buildings as short-term thermal storage for various demand response purposes. Realization of this potential relies heavily on the accuracy of the model used to represent the thermodynamics of the building. Such models, whether they are grey box or black box, are calibrated using relevant data obtained from initial measurements, and the performance of the calibrated model is validated using data from a subsequent period. However, many studies use validation periods with weather conditions similar to those of the calibration period. Only a few studies investigate whether the calibrated model performs satisfactory when subjected to significantly different conditions. This paper presents data from a simulation-based study on the effect of seasonal weather changes on the performance of a black-box model. The study was conducted using 11 years of Danish weather data (2008-2018). The results indicate that the performance of the black-box model deteriorate as the weather data conditions become increasingly different from those used in the initial model calibration. Further, the results show that calibration in heating season leads to satisfactory model performance through the heating season, but lower performance in transitional seasons (especially spring). Results also show that calibration in February led to highest model performance through heating season, while calibration in March led to satisfactory model performance in the whole heating and fall season. |
url |
https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/32/e3sconf_nsb2020_02005.pdf |
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