Predicting operational energy consumption profiles : findings from detailed surveys and modelling in a UK educational building compared to measured consumption

Knight, I. (Welsh School of Architecture, Cardiff University, Cardiff, UK) ; Stravoravdis, S. (Welsh School of Architecture, Cardiff University, Cardiff, UK) ; Lasvaux, Sébastien (Institut National des Sciences Appliquées, INSA, Toulouse, France)

This paper presents the preliminary findings from the first stage of a physical survey and modelling case study conducted to obtain modelled and actual energy consumption profiles for a UK multi-storey mixed use educational building (the Bute building at the University of Wales, Cardiff). The purpose of the study is to provide an insight into how accurately current models and software can predict the actual energy consumption in such a building, with a view to informing the development of operational and asset ratings for buildings in the EU as part of the Energy Performance in Buildings Directive (EPBD) Article 7 requirements. The models used in this study were the software tool ECOTECT and the SBEM (Simplified Building Energy Methodology) version of the UK’s national calculation methodology. The study also briefly discusses the potential problems inherent in the use of modelling techniques for assessing the energy performance of buildings. The data obtained through this study enabled predicted energy consumption profiles for both heating/cooling and electrical energy use to be obtained, as well as a UK SBEM asset-type compliance rating. The predicted profiles and compliance rating were then compared to the monitored actual energy consumption profiles obtained over the same period. It was seen that the various modelling approaches gave a reasonable prediction of the gas consumption and a reasonable estimate of the electrical consumption using the SBEM. However, overall it was felt that further case studies would need to be tested to have any confidence in these findings. The relative agreement between the SBEM results in this case study and the measured consumption supports the view that for prediction of electrical consumption then statistically derived numbers, such as benchmarks, are likely to enable reasonably confident predictions of energy use by generic activity type.

Note: LASVAUX, Sébastien est un chercheur à la HES-SO, HEIG-VD, depuis 2015.

Article Type:
Ingénierie et Architecture
IGT - Institut de Génie Thermique
9 p.
Published in:
International Journal of Ventilation
Numeration (vol. no.):
2008, vol. 7, no. 1, pp. 49-57
Appears in Collection:

 Record created 2021-02-26, last modified 2021-03-19

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