Adding advanced behavioural models in whole building energy simulation: A study on the total energy impact of manual and automated lighting control

Abstract

/npsi/ctrl?lang=en http://nparc.cisti-icist.nrc-cnrc.gc.ca/npsi/ctrl?lang=fr Access and use of this website and the material on it are subject to the Terms and Conditions set forth at http://nparc.cisti-icist.nrc-cnrc.gc.ca/npsi/jsp/nparc_cp.jsp?lang=en NRC Publications Archive Archives des publications du CNRCThis publication could be one of several versions: author's original, accepted manuscript or the publisher's version. / La version de cette publication peut être l'une des suivantes : la version prépublication de l'auteur, la version acceptée du manuscrit ou la version de l'éditeur. For the publisher's version, please access the DOI link below./ Pour consulter la version de l'éditeur, utilisez le lien DOI ci-dessous.http://dx.doi.org/10.1016/j.enbuild. 2006.03.002 Energy and Buildings, 38, 7, pp. 814-823, 2006-07-01 Adding advanced behavioural models in whole building energy simulation: a study on the total energy impact of manual and automated lighting control Bourgeois, D.; Reinhart, C. F.; Macdonald, I. A. AbstractBehavioural models derived from on-going field studies can provide the basis for predicting personal action taken to adjust lighting levels, remedy direct glare, and save energy in response to physical conditions. Enabling these behavioural models in advanced lighting simulation programs, such as DAYSIM and the Lightswitch Wizard, allows for a more realistic estimate of lighting use under dynamic conditions. The current downside of these approaches is that the whole building energy impact of manual changes in blind settings and lighting use, including its effect on heating and cooling requirements, is not considered. A sub-hourly occupancy-based control model (SHOCC), which enables advanced behavioural models within whole building energy simulation, is presented. The considered behavioural models are the Lightswitch2002 algorithms for manual and automated light and blind control, while the investigated whole building energy simulation program is ESP-r.The enhanced functionality is demonstrated through annual energy simulations aiming at quantifying the total energy impact of manual control over lights and window blinds.Results show that building occupants that actively seek daylighting rather than systematically relying on artificial lighting can reduce overall primary energy expenditure by more than 40%, when compared to occupants who rely on constant artificial lighting.This underlines the importance of defining suitable reference cases for benchmarking the performance of automated lighting controls. Results also show that, depending on the proportion of buildings occupants that actively seek out daylighting, 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 reveals the superiority of integrated design approaches ove...

Modelling electricity consumption in office buildings: An agent based approach

“…Thus there is an argument for an automated electricity management strategy which maintains efficient electricity consumption to satisfactorily meet electricity users' electricity needs and meanwhile minimizes the cost of electricity without any user intervention in office buildings. Bourgeois et al [18] show that under automated lighting management the electricity consumption is much less than that in automated lighting management. In the School of Computer Science, there seems to be a debate between the automated strategy and staff-controlled strategy.…”

Occupants’ behavioural impact on energy consumption: ‘human-in-the-loop’ comfort process control

“…In this context, user behaviour may be defined as the presence of people in a workplace location in a building and the action users take (or do not take) to influence their indoor environment (Hoes et al, 2009). Recently models have been developed to describe human behaviour and are included in building performance analyses (Bourgeois, Reinhart, & MacDonald, 2006;Degelman, 1999;Hoes et al, 2009;Mahdavi, Kabir, Lambeva, & Proglhof, 2006;Nicol, 2001;Page et al, 2007;Reinhart, 2004;Rijal et al, 2007;Tabak & de Vries, 2010). However, only a few studies successfully demonstrated energy reduction from occupancy behavioural patterns that had been determined because there was no formal connection to the building energy management systems of these buildings (Dong & Andrews, 2009).…”

Use of model predictive control and weather forecasts for energy efficient building climate control

“…low energy cost actuators were exploited as much as possible. The effect of automated blinds and lighting control on heating and cooling requirements were studied in [5]; the authors investigated the reduction of the annual primary energy usage in building climate control for the case of Rome. In the study of [4], the influence of occupant behavior on energy consumption was investigated in a single room occupied by one person.…”