Andrew Cripps

TL;DR: In this paper, a case study focused specifically on lighting, small power and catering equipment in a high density office building is analyzed and presented, showing 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.

TL;DR: In this article, a case study focused on lighting, small power and catering equipment in a high density office building is presented, where the authors demonstrate how knowledge acquired from post-Occupancy Evaluation (POE) can be used to produce more accurate energy performance models.

TL;DR: In this paper, two models for estimating small power consumption in office buildings, alongside typical power demand profiles, were proposed, one relying solely on the random sampling of monitored data, and the second relying on a bottom-up approach to establish likely power demand and operational energy use.

TL;DR: The CIBSE Guide F as mentioned in this paper is a widely recognised guidance document on energy efficiency in buildings, which includes energy consumption benchmarks for small power equipment in offices. In its recently publis...

TL;DR: In this article, the authors report on a study aiming to assess the intent of occupants to switch off lighting and appliances when not in use in office buildings based on the Theory of Planned Behaviour, and investigate three predictors to behaviour individually: behavioural attitude, subjective norms, and perceived behavioural control.