Assessing the total energy impact of occupant behavioural response to manual and automated lighting systems

Behavioural models derived from on-going field studies can provide the basis for predicting personal action taken to adjust lighting levels or remedy direct glare in response to physical conditions. SHOCC, a sub-hourly occupancy-based control model, provides building energy simulation programs, such as ESP-r, access to advanced behavioural models, such as the Lightswitch2002 algorithms intended for manual and automated lighting systems. The effectiveness of the approach is demonstrated through annual energy simulations aiming at quantifying the total energy impact of manual control over lights and window blinds. Results show that by enabling manual control, as opposed to using predefined lighting profiles for core zones, total primary energy expenditure is reduced by as much as 62%. This underlines the importance of defining suitable reference cases for benchmarking the performance of automated lighting controls. Results also show that reduced lighting use through automated control may not always produce anticipated savings in primary energy for indoor climate control; in some cases, reduced lighting use is shown to even increase primary energy expenditure for indoor climate control, trimming down initial primary energy savings in lighting alone. This supports the use of integrated approaches rather than simple guidelines in designing lighting solutions