1、4762 Development and Testing of an Integrated Daylighting Control System Kwang-Wook Park, PhD ABSTRACT The performance of an integrated daylighting control system for electric light dimming and a motorized venetian blind with the illuminance ratio prediction method are presented in this paper. Basic
2、 control technique andparame- ters are examined with a workplane sensor control. Based on this, an integrated daylighting controlsystem is developed with the predicted daylightingparumeters by using an interiorfront wall sensor The experimental results show that this system could maintain both the w
3、orkplane illuminance level and the solar heat gains ut desirable levels by control of a light dimming and shading device. Without explicitly determining daylight transmittance of the window system, the desirable daylight level was achieved with the controlled blind tilt angle, which was obtainedfrom
4、 thepredicteddaylightangle with only one interior light sensor control. With active daylighting control, sign$cant solar gain reductions can be achieved while maintaining the design workplane illuminance level. I N TRO D U CT I O N The potential energy savings from integrated control strategies for
5、dynamic building envelopes with control of lighting and HVAC systems are more than those from individ- ual control strategies (Guillemin and Morel 2001 ; Selkowitz and Lee 1998). Research has shown that savings in lighting energy consumption are more significant when the lighting is dimmed in conjun
6、ction with photocontrolled blinds (Galasiu et al. 2004). Even with their highly promising features, only a few building control systems have adopted these control strat- egies in building energy management systems. Therefore, it is necessary to understand individual system characteristics and daylig
7、hting parameters for efficient integration. Without Andreas K. Athienitis, PhD, PEng Member ASHRAE understanding the systems, their control cannot be achieved efficiently. The performance of light-dimming systems is influenced not only by climate and site differences but also by the photo- cell conf
8、igurations and control algorithms used. A major drawback in current light-dimming control systems is that most of the research efforts to develop control dimming solu- tions focus on applying different combinations of photosensor configurations and control algorithms without a systematic approach. M
9、oreover, there is not much detailed research on workplane illuminance prediction. To improve the perfor- mance of the system, prediction of the workplane illuminance must be considered in integrated daylighting control systems. Research issues for light-dimming control systems have included determin
10、ing optimum photosensor locations, deter- mining optimum photosensor shielding configurations from electric lighting and daylighting sources, and devising more sophisticated control algorithms to disaggregate the predict- able electric lighting illuminance contribution from the complex daylight illu
11、minance contribution (Lee et al. 1999; Ranasinghe and Mistrick 2003; Ehrlich et al. 2002). Although the solutions from many research groups have been improved, they are still not robust enough and are usually dependent on solar position, sky conditions, and shading devices (venetian blind tilt angle
12、s). Accurate light-dimming control has many advantages, such as saving electric energy, potentially reducing peak demand, and providing a comfortable and pleasant work envi- ronment. Reliable control may be achieved through accurate workplane illuminance prediction. As fenestration systems become mo
13、re dynamic, such as with the use of electrochromic glazings or motorized venetian blinds, light-dimming controls must accommodate this added performance complexity. Kwang-Wook Park is a research associate and Andreas K. Athienitis is a professor in the Department of Building, Civil and Environmental
14、 Engineering, Concordia University, Montral, Qubec, Canada. 21 8 02005 ASHRAE. Increasingly, daylighting controls will be linked to whole building energy management systems as owners attempt to improve their control over energy management of the entire building (Selkowitz and Lee 1998). A new predic
15、tion method that is accurate, simple, and reliable was developed for an integrated daylighting control system-the illuminance ratio prediction (IRP) method (Park and Athienitis 2003). With the IRP method, it was found that several useful daylighting parameters, such as the workplane illuminance, ext
16、erior vertical illuminance, and solar irradiance through the window, for daylighting control in buildings can be efficiently predicted with only one interior light sensor (Park and Athienitis 2004). This paper is a part of a project that is developing an inte- grated daylighting control system for l
17、ighting, shading, heat- ing, and cooling ofbuildings. The main objective ofthe project is to develop a daylight control system prototype that manages each system efficiently and minimizes optimization efforts for integrated control algorithms. This research is focused on developing an integrated day
18、lighting control system with which daylight distributions in the room and several parame- ters affecting the system are identified. Then control strategies considering human preference can be simply and flexibly implemented with low risk of losing system reliability. The performance of an integrated
19、 daylighting control system for electric light dimming and a shading device (motorized venetian blind) with the IRP method (Park and Athienitis 2004) is presented in this paper. The basic control technique and parameters, such as control time intervals for electric light dimming and changing blind t
20、ilt angle, are exam- ined with a workplane sensor control. Based on this, an inte- grated daylighting control system, which controls the workplane illuminance level while preventing undesirable solar heat gains, is developed with the predicted daylighting parameters by using an interior front wall s
21、ensor. The proce- dure for general applications with the IRP method is explained. ILLUMINANCE RATIO PREDICTION (IRP) METHOD The illuminance (E) of N surfaces in an enclosure can be calculated by using radiation exchange theory as follows (Murdoch 1985): EIN = Tl,.CMol, (1) where Mo is the initial lu
22、minous exitance (source) and the illu- minance transfer factor matrix, TlNxN = FlN,NTlN,N (2) where F = view factor and T = luminous exitance transfer factor. Tdepends on the geometric orientation to the light source surfaces and reflectances of the surfaces. A space with different geometry or havin
23、g different surface reflectance will have a completely different illuminance distribution under the same initial luminous exitance. With careful observation of Equation 1, the prediction of the workplane illuminance can be simplified without loss of accuracy. Consider an enclosure where there is onl
24、y one source (initial luminous exitance, Mo) on surface 1 so that Mo, # O and Mo, = O for k = 2, 3, ., N. Then the illuminance of surface i is Ei = MO, . Ti, . (3) The illuminance ratio of two surfaces m and n due to a light source at surface 1 is then (4) where Th, and T, are both constant values f
25、or the given space geometry and surface properties. Therefore, it can be concluded that the illuminance ratio of two surfaces is only a function of the geometric relationship of the two surfaces and their properties; the illuminance ratio of two arbitrary surfaces in an enclosure is always kept cons
26、tant even with varying quantity of the diffuse light source (Mo,). It is not required to calculate the illuminance transfer factor; that is, it is not neces- sary to calculate view factors and measure the reflectances of all subdivided surfaces. However, the exact illuminance of any subdivided surfa
27、ce can be predicted easily, especially in a light-dimming control system where an indirect prediction method is employed to complement electric light for the target design illuminance level. In the daylighting control environment, at least two light sources must be considered, one for the daylight t
28、hrough the window systems and one for the electric light, which will complement design workplane illuminance level by dimming. The daylight and electric light contributions to the photocell and the workplane are different (because of the different loca- tions of the light sources) so that a separate
29、 prediction must be employed for the two light sources. Electric light from a lighting fixture (luminaire) is designed to distribute luminous flux in a predictable manner. The workplane illuminance then can be predicted indirectly with a photocell located somewhere in the space rather than on the wo
30、rkplane. The dimming of the luminaire will not affect the illuminance ratio of two surfaces (workplane surface and surface with photocell) according to Equation 4. The daylight admitted through window systems can be direct or diffuse. With direct daylight admission into the room, the initial light s
31、ource would be beam daylight projection on the room surfaces so that its location and surface area will be changing continuously according to the position of the sun; numerous ratios would be required to predict workplane illu- minance with the illuminance ratio prediction method. If the light sourc
32、e location and surface area were fixed, then only one ratio would be needed to predict daylight in the space. A window system with shading devices controlled to prevent direct daylight transmission can be treated as a lumi- ASHRAE Transactions: Research 21 9 naire such as a dimmable spotlight, which
33、 aims at one fixed point and distributes variable amounts of light consistently. It is possible to achieve consistent daylight distribution in the space by means of shading device control. The illuminance ratio, for the venetian blinds for example, could be a function of angle of incidence on the bl
34、ade of the blinds because the way daylight is distributed into the space will change with the solar altitude, surface solar azimuth, and blind tilt angles. EXPERIMENTS ON DAYLIGHT CHARACTERIZATION In this section, previously obtained correlations between the interior light sensor and several sensors
35、 (for the workplane illuminance, the exterior vertical illuminance, and the solar irradiation through the window) will be addressed. The inte- rior light sensor was placed on the front wall (the same surface with the window), which was determined to be the optimal surface for the electric light and
36、daylight predictions. The detailed experimental procedures and results can be obtained from Park and Athienitis (2003,2004). Test Facility An insulated outdoor test room on the roof of a university building in Montreal (latitude 45“N, longitude 74“W) was operated for daylighting control studies unde
37、r real weather conditions. The interior dimensions of the test room are 2.82 m x 2.22 m x 2.24 m. The test room has cream-white painted walls, acoustic ceiling, and carpeted floor. The measured reflectances of the test room surfaces are floor 17%, ceiling 66%, wall 68%, window 8% with blinds closed
38、and 6- 10% with blinds open, and desk 52%. A schematic of the test room is given in Figure 1. Two lighting fixtures, each with two T8 32 W lamps and dimmable fluorescent ballasts, were installed. These are mounted on the ceiling parallel to the window along the centerline of the test room. The insta
39、lled window system is a double-glazed window with reflective venetian blinds inte- grated between two glazings with one low-emissivity coating. The dimensions of the window are 1.08 m x 1.08 m. The louvers are made of extruded aluminum and hollow-cham- bered profile with overlap. The blades are conv
40、ex with inter- locking type ends; their dimensions are 35 mm wide by 6 mm thick. The main control strategy for blind tilt angle was to allow maximum outside view while blocking direct daylight beam penetration for the daylight prediction; the rotation range of the tilt angle was from O degrees (full
41、y open, hori- zontal) to 70 degrees (not closed completely but no horizontal beam can penetrate) since the blades of the blind are overlap- ping. A number of thermocouples, Pyranometers, and light sensors were placed in different locations for measuring inside and outside temperatures, the solar irr
42、adiance through the window, and the illuminance. All were connected to the data acquisition system, which was installed in the test room and programmed for control of inside temperature, light dimming, and blind tilt angle, as well as data recording. The existing heating (baseboard heater) system wa
43、s controlled to maintain the temperature constant (23C) with ON/OFF control. The reason for keeping room temperature constant is that temper- ature might affect the accuracy of the sensor reading. Electric Light Correlation To obtain electric light correlation between the workplane illuminance and t
44、he front wall sensor illuminance, the window I, 2,220 mm b n Vision Figure 1 220 Schematic I I Heater of the test room. ASHRAE Transactions: Research 8.32XDL- 4% .+ - - 1 O 10 20 30 40 50 60 70 BO 90 100 I Lighting Output Level (Vo) Figure 2 Correlations between the light dimming level L) and the wo
45、rkplane illuminance (EEWP) and the front wall sensor illuminance (EEFW). was completely covered with black cardboard. A light meter was mounted on the front wall surface (L2 in Figure 1) with one meter for the workplane illuminance measurement on the table, which is in the center ofthe test room at
46、0.8 m height (L, in Figure 1). The electric light was dimmed randomly between zero and full every 1 O seconds to simulate variable conditions. Data from the light meters were sampled and logged every 10 seconds for one hour. The purpose of the light-dimming control is to comple- ment the target desi
47、gn illuminance level with electric light, hence, to maximize daylight use and save energy. It is neces- sary to know the target (workplane) illuminance level at a given light dimming level. Two linear correlations for the workplane illuminance (EEwp) and the front wall sensor illu- minance (EEFw) we
48、re obtained as the following equations (Figure 2): E, = 8.32 . DL - 48.6 (5) where DL stands for electric light dimming level expressed in percent and it ranged from 15% to 100%. Daylight Correlation The same light meters for both the workplane illuminance and the front wall sensor illuminance, in a
49、ddition to one exte- rior light meter (L3 in Figure 1) for the exterior vertical illu- minance and two Pyranometers on the interior window surface (PT and P, in Figure 1) for the solar irradiance through the window, were used for the daylight prediction. It was found (Park and Athienitis 2003) that the correlation for daylight prediction was dependent on the blind tilt angle, the solar alti- tude angle, and the surface solar azimuth angle, so that the daylight angle (o) parameter was introduced and defined as follows: tan a cosy d = tan - (-) a: solar altitude angle y: surf
