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A. Mahdavi, C. Berger:
"On the Reliability of Buildings' Energy Use Predictions Can we Close the Occupant-related Performance Gap?";
Talk: Planning Post Carbon Cities. Proceedings of the 35th PLEA Conference on Passive and Low Energy Architecture., A Coruna, Spain; 2020-09-01 - 2020-09-03; in: "Planning Post Carbon Cities. Proceedings of the 35th PLEA Conference on Passive and Low Energy Architecture.", J. Rodriguez-Alvarez, J.C. Soares-Gocalves, PLEA (ed.); A Coruña: University of A Coruña, (2020), Paper ID 1147 (p. 1662- 1667), 6 pages.

Computational building models can support building design, for instance via provision of
performance predictions. Specifically, energy use predictions are considered both as useful feedback for iterative
design improvements and as useful orientation for future building users and operators. However, in many
instances, predictions of building energy use are not confirmed by actual monitored energy use data. This
circumstance is generally referred to as performance gap. As such, multiple factors can play a role in the
divergence of predictions and observations, including differences between the computational building model and
the actually constructed building, weather conditions, and user presence and behaviour. The latter aspect has
recently suggested to be a major factor behind the performance gap. In this paper, we reconsider the problem of
performance gap as related to building energy use predictions. Toward this end, we: i) formulate a general
definition of the occupant-centric performance gap research premise, ii) provide a systematic depiction of the
many ways people's presence and control-oriented actions can influence buildings' energy demand, iii) reassess
the validity of identification of the human factor as the main contributor to performance gap, and iv) explore the
postulated prospect of sophisticated occupancy modelling techniques and behavioural modification schemes.

(no german abstract)
Computational building models can support building design, for instance via provision of
performance predictions. Specifically, energy use predictions are considered both as useful feedback for iterative
design improvements and as useful orientation for future building users and operators. However, in many
instances, predictions of building energy use are not confirmed by actual monitored energy use data. This
circumstance is generally referred to as performance gap. As such, multiple factors can play a role in the
divergence of predictions and observations, including differences between the computational building model and
the actually constructed building, weather conditions, and user presence and behaviour. The latter aspect has
recently suggested to be a major factor behind the performance gap. In this paper, we reconsider the problem of
performance gap as related to building energy use predictions. Toward this end, we: i) formulate a general
definition of the occupant-centric performance gap research premise, ii) provide a systematic depiction of the
many ways people's presence and control-oriented actions can influence buildings' energy demand, iii) reassess
the validity of identification of the human factor as the main contributor to performance gap, and iv) explore the
postulated prospect of sophisticated occupancy modelling techniques and behavioural modification schemes.

Energy, Performance Gap, Prediction, Simulation, Buildings

http://dx.doi.org/10.17979/spudc.9788497497947