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Overheating in English dwellings: comparing modelled and monitored large-scale datasets

Tutkimustuotosvertaisarvioitu

Standard

Overheating in English dwellings : comparing modelled and monitored large-scale datasets. / Symonds, Phil; Taylor, Jonathon; Mavrogianni, Anna; Davies, Michael; Shrubsole, Clive; Hamilton, Ian; Chalabi, Zaid.

julkaisussa: Building Research and Information, Vuosikerta 45, Nro 1-2, 17.02.2017, s. 195-208.

Tutkimustuotosvertaisarvioitu

Harvard

Symonds, P, Taylor, J, Mavrogianni, A, Davies, M, Shrubsole, C, Hamilton, I & Chalabi, Z 2017, 'Overheating in English dwellings: comparing modelled and monitored large-scale datasets', Building Research and Information, Vuosikerta. 45, Nro 1-2, Sivut 195-208. https://doi.org/10.1080/09613218.2016.1224675

APA

Symonds, P., Taylor, J., Mavrogianni, A., Davies, M., Shrubsole, C., Hamilton, I., & Chalabi, Z. (2017). Overheating in English dwellings: comparing modelled and monitored large-scale datasets. Building Research and Information, 45(1-2), 195-208. https://doi.org/10.1080/09613218.2016.1224675

Vancouver

Symonds P, Taylor J, Mavrogianni A, Davies M, Shrubsole C, Hamilton I et al. Overheating in English dwellings: comparing modelled and monitored large-scale datasets. Building Research and Information. 2017 helmi 17;45(1-2):195-208. https://doi.org/10.1080/09613218.2016.1224675

Author

Symonds, Phil ; Taylor, Jonathon ; Mavrogianni, Anna ; Davies, Michael ; Shrubsole, Clive ; Hamilton, Ian ; Chalabi, Zaid. / Overheating in English dwellings : comparing modelled and monitored large-scale datasets. Julkaisussa: Building Research and Information. 2017 ; Vuosikerta 45, Nro 1-2. Sivut 195-208.

Bibtex - Lataa

@article{425b6ff620294438a63355d55b9da93c,
title = "Overheating in English dwellings: comparing modelled and monitored large-scale datasets",
abstract = "Monitoring and modelling studies of the indoor environment indicate that there are often discrepancies between simulation results and measurements. The availability of large monitoring datasets of domestic buildings allows for more rigorous validation of the performance of building simulation models derived from limited building information, backed by statistical significance tests and goodness-of-fit metrics. These datasets also offer the opportunity to test modelling assumptions. This paper investigates the performance of domestic housing models using EnergyPlus software to predict maximum daily indoor temperatures over the summer of 2011. Monitored maximum daily indoor temperatures from the English Housing Survey’s (EHS) Energy Follow-Up Survey (EFUS) for 823 nationally representative dwellings are compared against predictions made by EnergyPlus simulations. Due to lack of information on the characteristics of individual dwellings, the models struggle to predict maximum temperatures in individual dwellings and performance was worse on days when the outdoor maximum temperatures were high. This research indicates that unknown factors such as building characteristics, occupant behaviour and local environment makes the validation of models for individual dwellings a challenging task. The models did, however, provide an improved estimate of temperature exposure when aggregated over dwellings within a particular region.",
keywords = "building information modelling (BIM), building performance, EnergyPlus, housing stock, occupant behaviour, overheating, simulation, validation",
author = "Phil Symonds and Jonathon Taylor and Anna Mavrogianni and Michael Davies and Clive Shrubsole and Ian Hamilton and Zaid Chalabi",
year = "2017",
month = "2",
day = "17",
doi = "10.1080/09613218.2016.1224675",
language = "English",
volume = "45",
pages = "195--208",
journal = "Building Research and Information",
issn = "0961-3218",
publisher = "Taylor & Francis Ltd",
number = "1-2",

}

RIS (suitable for import to EndNote) - Lataa

TY - JOUR

T1 - Overheating in English dwellings

T2 - comparing modelled and monitored large-scale datasets

AU - Symonds, Phil

AU - Taylor, Jonathon

AU - Mavrogianni, Anna

AU - Davies, Michael

AU - Shrubsole, Clive

AU - Hamilton, Ian

AU - Chalabi, Zaid

PY - 2017/2/17

Y1 - 2017/2/17

N2 - Monitoring and modelling studies of the indoor environment indicate that there are often discrepancies between simulation results and measurements. The availability of large monitoring datasets of domestic buildings allows for more rigorous validation of the performance of building simulation models derived from limited building information, backed by statistical significance tests and goodness-of-fit metrics. These datasets also offer the opportunity to test modelling assumptions. This paper investigates the performance of domestic housing models using EnergyPlus software to predict maximum daily indoor temperatures over the summer of 2011. Monitored maximum daily indoor temperatures from the English Housing Survey’s (EHS) Energy Follow-Up Survey (EFUS) for 823 nationally representative dwellings are compared against predictions made by EnergyPlus simulations. Due to lack of information on the characteristics of individual dwellings, the models struggle to predict maximum temperatures in individual dwellings and performance was worse on days when the outdoor maximum temperatures were high. This research indicates that unknown factors such as building characteristics, occupant behaviour and local environment makes the validation of models for individual dwellings a challenging task. The models did, however, provide an improved estimate of temperature exposure when aggregated over dwellings within a particular region.

AB - Monitoring and modelling studies of the indoor environment indicate that there are often discrepancies between simulation results and measurements. The availability of large monitoring datasets of domestic buildings allows for more rigorous validation of the performance of building simulation models derived from limited building information, backed by statistical significance tests and goodness-of-fit metrics. These datasets also offer the opportunity to test modelling assumptions. This paper investigates the performance of domestic housing models using EnergyPlus software to predict maximum daily indoor temperatures over the summer of 2011. Monitored maximum daily indoor temperatures from the English Housing Survey’s (EHS) Energy Follow-Up Survey (EFUS) for 823 nationally representative dwellings are compared against predictions made by EnergyPlus simulations. Due to lack of information on the characteristics of individual dwellings, the models struggle to predict maximum temperatures in individual dwellings and performance was worse on days when the outdoor maximum temperatures were high. This research indicates that unknown factors such as building characteristics, occupant behaviour and local environment makes the validation of models for individual dwellings a challenging task. The models did, however, provide an improved estimate of temperature exposure when aggregated over dwellings within a particular region.

KW - building information modelling (BIM)

KW - building performance

KW - EnergyPlus

KW - housing stock

KW - occupant behaviour

KW - overheating

KW - simulation

KW - validation

UR - http://www.scopus.com/inward/record.url?scp=84988432242&partnerID=8YFLogxK

U2 - 10.1080/09613218.2016.1224675

DO - 10.1080/09613218.2016.1224675

M3 - Article

VL - 45

SP - 195

EP - 208

JO - Building Research and Information

JF - Building Research and Information

SN - 0961-3218

IS - 1-2

ER -