Predicting Operational Energy Consumption Profiles - Findings from Detailed Surveys and Modelling in a UK Educational Building Compared to Measured Consumption

Abstract

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.

A Review of the Regulatory Energy Performance Gap and Its Underlying Causes in Non-domestic Buildings

“…In particular, Ruyssevelt (2014) reported university buildings to use 156% more energy than initially predicted, an average based on 13 individual studies. This percentage is, however, not supported by Knight et al (2008) and Diamond et al (2006) who report a difference of only 8 and 22% for university buildings, respectively. Similarly, Ruyssevelt (2014) reported schools to use 37% more energy than initially predicted, based on an average of 58 individual studies, whereas Pegg et al (2007) and Kimpian et al (2014) report much higher average percentages of 117% (3 schools) and 71% (5 schools), respectively.…”

Effect of housing density on energy efficiency of buildings located in hot climates

“…Ecotect is a widely used program in environmental performance simulation studies, where its three-dimensional CAD interface makes it more practical in building simulation. Ecotect is known to give a reasonable estimate of energy loads in buildings [13], and has been solely used in several recent energy modelling studies [14][15][16][17][18]. In addition, its thermal modelling of buildings has been compared to other tools [19] and field measurements [20] where good agreement has been observed.…”

Minimising the Deviation between Predicted and Actual Building Performance via Use of Neural Networks and BIM

“…Deviations between predicted and actual building performance leads to inefficiencies in terms of cost and energy consumption: van Dronkelaar et al, (2016) reported a 15%-80% discrepancy in total energy between design and building performance [19], while Knight et al, (2008) indicated a 22% difference between actual and predicted performance in university buildings [20]. A case study by The Carbon Trust, (2012) indicated that an extra £10/m2 in annual operating energy costs resulted due to the performance gap between predicted and actual performance of the building [21].…”