Factors affecting ‘end-of-day’ window position in a non-air-conditioned office building

Abstract

This paper presents a longitudinal study observing people's use of windows in mixed mode cellular offices, and sets out to identify factors other than air temperature, that have a significant influence on window operation. The work focuses on the final position of the window at the end of the working day.The results have been compared to other published work and the building is found to have similar characteristics when it and its occupants are treated as a whole. When sub-sets of the data are examined, the factors of season, floor level, gender, and personal preference emerge as having a statistically significant effect on the end-of-day window position in the building examined and these findings are properly discussed with relevant references.

Impact of occupant behaviour on the energy-saving potential of retrofit measures for a public building in the UK

“…Currently, a number of methods are available to help monitor principle occupant behaviour, e.g. window behaviour and heating behaviour, in buildings, for example, self-recording by the building occupants (Haldi and Robinson, 2008;Raja et al), electronic measurement devices (Spataru andGillott 2011, Yun andSteemers, 2010), surveyor observation (Wei et al 2013;Zhang and Barrett, 2012) and self-estimation by the building occupants (Guerra Santin, 2013;Huang et al 2014). A deep understanding of the advantages and disadvantages of each method is still highly needed so the most suitable method for refurbishment applications can be identified.…”

“…The data were provided by the FM according to the initial design of the building. In winter, the building is heated by a district heating system covering the Central Park of the university campus, generally starting from the beginning of October and ending at the end of March (Wei, Buswell, and Loveday 2013 Table 1 and relevant geometry information provided by the FM, a base case simulation model was developed as shown in Figure 2. To build this model, three types of blocks defined in DesignBuilder were used, namely building block, adiabatic block and ground block (DesignBuilder): the building block was used to define components of building construction; the adiabatic block was used to define any adjacent buildings; the ground block was used to define the adjacency of any touching building block surfaces as being 'adjacent to ground'.…”

Stochastic behavioural models of occupants' main bedroom window operation for UK residential buildings

“…The review concluded that: (1) window operation has a strong impact on the energy use and indoor environmental conditions of buildings; (2) there remains a lack of consensus as to which drivers actually influence occupants' window operation; ( Furthermore, as Fabi et al [20] reviewed window interaction studies in both domestic and nondomestic buildings, it was evident that most previous analyses have focused on office buildings (e.g. [17,18,[35][36][37][38][39][40][41]) and there is a lack of studies related to residential buildings. Stochastic models of occupants' window interactions developed based on measurements in office buildings can provide useful inputs for modelling large buildings or clusters of buildings (city scale) with many occupants.…”

Driving factors for occupant-controlled space heating in residential buildings

“…In those cases, accurate modelling of occupants' operation of the building was less important, as long as occupant behaviour was represented by the same operational schedule in all design scenarios. In the last two decades, more accurate modelling of occupant behaviour in BPS, and especially their operation of windows, blinds and artificial lights, has gained a great deal of research attention, due to the significant influence of occupants' behaviour on the performance of buildings[64][65][66][67]. In the following part of this paper, the current status of modelling occupant space-heating behaviour in BPS is reviewed, mainly from two aspects: (1) the selection of the heating setpoint values; and (2) the dependence of the heating setpoint value on influencing factors.…”