The role of spectral response of photosensors in daylight responsive systems
Introduction
Despite the great potential for energy savings in areas with high levels of daylight and case studies documenting energy savings from dimming [1], [2], [3], [4], [5], [6], lighting control with photosensors have not been widely installed by building contractors. This is because of the added cost of the equipment and installation labour. In addition there is a perception that automatic dimming controls are unreliable, although, various studies have described their proper functioning [7], [8], [9], [10], [11], [12], [13], [14], [15], [16].
Accurate computation of daylight, accurate simulation of the performance of the photosensor and reliable simulation of the artificial lighting system output in relation to the control voltage are needed for the prediction of the performance and its effects on energy use [9], [10], [17], [18], [19], [20]. The basic operation of a photosensor is the production of a signal that is related to the amount and the distribution of lighting in a space in which it is placed. The performance of the photosensor can be complex because it depends from a lot of variables, such as:
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the distribution of daylight and artificial lighting in the space in which it is placed;
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the spectral composition of lighting;
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the adjustment settings of the commissioning control;
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the ambient light level;
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the field of view.
The behaviour of the photosensor in response to variable lighting, blind and/or glazing conditions is significant in the design of a daylight responsive system. Fig. 1 shows a photosensor system diagram [21]. Its optical response is consisted of two main sub functions:
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Spatial response: The spatial response describes the sensitivity of the photosensor to incident radiation from different directions, in other words, what the photosensor “sees.” Spatial response is analogous to a luminaire intensity distribution but describes sensitivity instead of light output.
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Spectral response: The spectral response describes the sensitivity of the photosensor to optical radiation of different wavelengths.
Ehrlich et al. [22] have presented a method of simulating the photosensor behaviour based on the multiplication of two fisheye rendered images, one generated with the actual angular sensitivity of the photosensor while the other with an 180° field of view of the space as “seen” by the photosensor. Analyzing the final image, photosensor illuminance can be calculated accurately. For the estimation of energy consumption, functions of control voltage, light output ratio and consumed power of the lighting system are also needed. These can be estimated using experiments or using the manufacturer's data [23], [24], [25]. Other studies [9], [15], [16], [17], [24], [26] have also simulated the photosensor behaviour taking into account only the spatial response of the photosensor.
However, the photocells used in photosensors are sensitive to a wider range of wavelengths than what the human eye sees. In other words, photocells respond to portions of the ultraviolet (UV) and infrared (IR) spectrum as well as the visible spectrum. Filters that incorporated into the photocell element, limit the sensitivity to ultraviolet (UV) and infrared (IR) radiation. Bierman and Conway [21] examining the behaviour of the photosensor found that a high performance control algorithm could possibly, but not likely, compensate for both a non-ideal spatial response and a poor spectral correction. On the other hand, they concluded that the better the spatial response tracks change in working plane illuminance and the better the spectral correction of the photosensor, the finer will be the overall operation of the photosensor system. Their conclusions differ from the commonly held belief of lighting practitioners that photosensor system performance depends primarily on a product's spatial response.
Simulation programs (DAYSIM [27], SPOT [28]) which have been developed for the estimation of the electrical lighting savings, can take into account the spatial response for the photosensor but they use the CIE photopic luminous efficiency function or one colour channel. Daylight's spectral power distribution is ignored although there are some efforts for the creation of a comprehensive model which, using simple parameters, the complete characterization of the light coming from the sky vault (including its spectral distribution) can be estimated [29], [30].
Without taking into account the differences in components and factors that affect a daylight responsive dimming system someone can be led away from the initial expectations, miscalculating the energy savings and thus the subsequent payback period. Recent studies have showed that commercial photosensors with different spatial and spectral response can affect differently the accuracy of the performance of such a system [13], [17], [21]. The proper placement and control algorithms of the photosensor are very significant factors that must be considered during the initial design stage [7], [8], [9], [13], [21]. The optimum choice of ballast from a large variety of electronic dimmable ballasts with different characteristics is also required, because the differences in energy savings can be significant [23], [24], [25]. Furthermore, improper daylight conditions during calibration procedure [26] together with the presence of shading and/or daylighting systems can turn the system in poor performance [31], [32].
However, the effect of spectral response in a daylight dimming system has received little attention. The present paper compares the performance of a number of photosensors with various spectral responses, installed in a typical office test-room with different types of glazing, in terms of estimated illuminance.
Section snippets
Photosensors
Five commercial photosensors, from three different manufactures, were tested. These photosensors were considered as separate devices that can work with any electronic dimmable ballast models having a 0–10 V DC signal.
The photosensors have been codified using two digits. The first digit is the number of the photosensor (1–5) and the second digit corresponds to the manufacturer of the photosensor (i–iii for three manufacturers). For example, the 3ii code corresponds to the third photosensor
Simulations
Simulations were performed using Radiance software [36] which has been used in previous photosensor studies [9], [15], [16], [22]. The room (Fig. 8, Fig. 9) that was used for the simulation is a typical space in an office building and has been used in the past for IEA task 27 and SWIFT projects [37], [38]. The windows were located on the south facade of the building. The photosensor was placed in the geometrical center of the room mounted on the ceiling, oriented with its maximum response
Conclusions
Given nowadays extensive availability of glazing types with various optical properties and daylighting control systems, spectral simulation of illuminance is extremely important.
Lighting control systems are a complex technology that changes rapidly. A variety of controllers, software, sensors and devices are currently available, but there is lack of information concerning the actual performance of these systems and control strategies. In order to fully exploit their capabilities and implement
Acknowledgements
The project is co-funded by the European Social Fund (75%) and National Resources (25%)—Operational Program for Educational and Vocational Training II (EPEAEK II) and particularly the Program PYTHAGORAS II.
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