posted on 2012-06-19, 14:13authored byAnna Carolina Kossmann de Menezes, Andrew Cripps, Dino Bouchlaghem, Richard BuswellRichard Buswell
With the increasing demand for more energy efficient buildings, the construction industry is faced with
the challenge to ensure that the energy performance predicted during the design stage is achieved
once a building is in use. There is, however, significant evidence to suggest that buildings are not
performing as well as expected and initiatives such as PROBE and CarbonBuzz aim to illustrate the
extent of this so called ‘performance gap’. This paper discusses the underlying causes of
discrepancies between energy modelling predictions and in-use performance of occupied buildings
(after the twelve month liability period). Many of the causal factors relate to the use of unrealistic input
parameters regarding occupancy behaviour and facilities management in building energy models. In
turn, this is associated with the lack of feedback to designers once a building has been constructed
and occupied.
The paper aims to demonstrate how knowledge acquired from Post-Occupancy Evaluation (POE) can
be used to produce more accurate energy performance models. A case study focused specifically on
lighting, small power and catering equipment in a high density office building is analysed and
presented. Results show that by combining monitoring data with predictive energy modelling, it was
possible to increase the accuracy of the model to within 3% of actual electricity consumption values.
Future work will seek to use detailed POE data to develop a set of evidence based benchmarks for
energy consumption in office buildings. It is envisioned that these benchmarks will inform designers
on the impact of occupancy and management on the actual energy consumption of buildings.
Moreover, it should enable the use of more realistic input parameters in energy models, bringing the
predicted figures closer to reality.
History
School
Architecture, Building and Civil Engineering
Citation
MENEZES, A.C. ... et al, 2012. Predicted vs. actual energy performance of non-domestic buildings: using post-occupancy evaluation data to reduce the performance gap. Applied Energy, 97, pp. 355-364.