Adaptive actions on shading devices in response to local visual stimuli

Abstract

Based on 6 years of continuous measurements, we have analysed in detail the occupancy, thermal and visual parameters influencing actions on shading devices in order to derive an accurate model for the prediction of their usage in office buildings. This article begins by presenting some of the key findings from these analyses. Informed by other developments in the literature, we go on to propose an approach for a comprehensive stochastic model for simulating blind usage. This model is based on a Markov process taking rigorously selected predictors (initial blind status, indoor and outdoor illuminance) as input variables to predict lowering and raising actions performed by occupants. A separate sub-model then predicts the chosen shaded fraction. An assessment of the predictive accuracy of simulations is then presented for several modelling variants using our measured data, from which the best performing model variant is selected.

Keywords:

• occupant behaviour
• shading devices
• window blinds
• stochastic modelling

Notes

1. The lower part accounts for the main part of outdoor visibility, see Figure 1b.

2. The position of these blinds was not measured; however, observations from a previous survey revealed that they were closed during around 11% of occupied periods.

3. The acquisition system records the changes observed by measurement devices in real time. Temperature and illuminance are recorded along with a time stamp once the variation exceeds 0.06°C or 30 lx.

4. Further details regarding the principles of logistic regression may be found in Hosmer and Lemeshow (2000). The situation of non-binary responses is treated in detail by Agresti (1990).

5. Note that the justification for such an approach has been made by Haldi and Robinson (2009) in their study of use of windows.

6. The kernel density estimator based on a sample X ₁, … , X_n from distribution f is defined as

where h > 0 is the bandwidth and g(x) is a kernel function (a symmetric probability density with mean zero and unit variance), we used here the standard normal density.

7. This refers to the period from 27 January 2005 to 14 January 2006, which offers representative climatic conditions and uninterrupted measurements.