7. Passivhus Norden Sustainable Cities and Buildings. Integrated design of daylight, thermal comfort and energy demand with use of IDA ICE

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1 Copenhagen, August Passivhus Norden Sustainable Cities and Buildings Brings practitioners and researchers together Integrated design of daylight, thermal comfort and energy demand with use of IDA ICE Line Karlsen 1,*, Grigori Grozman 2, Per Heiselberg 3, Ida Bryn 1 1 Oslo and Akershus University College of Applied Science, Norway, 2 Equa simulations AB, Sweden, 3 Aalborg University, Denmark * Corresponding line-roseth.karlsen@hioa.no SUMMARY This study presents work regarding implementation of the Radiance three phase daylight model into IDA Indoor Climate and Energy (IDA ICE). The model implementation is verified by comparing fullscale measurements and simulations of daylight conditions in a team office located in Oslo and an experimental room located in Aalborg. The comparisons indicate that the coupling between IDA ICE and Radiance is working satisfactory. A parameter study considering different glazing areas and façade orientations of a cell office located in Oslo was carried out to illustrate the benefit of conducting an integrated design. From the results of the parameter study it is evident that the integrated design method provides vital information of how different design parameters affect the relation between daylight, thermal comfort and energy use and it supplies the designer with an extensively more informative decision base for their design compared to conventional static daylight design. KEYWORDS Integrated design, daylight, IDA ICE INTRODUCTION With the current tightening of energy frames in Nordic countries, as well as occupants increased expectations to indoor environment, it becomes highly important to predict window performance accurately. It may be a climatic challenge to design buildings with low energy use and high indoor environmental performance, especially in relation to daylight and thermal conditions since an initiative to improve one aspect may worsen another. Today, there is often an obvious lack of sufficient integration of daylight in building design (An et al., 2010) and designers commonly use simple calculations or rules of thumb which doesn t give much information regarding the real daylight conditions in buildings (Mardaljevic et al., 2009). Earlier we have proposed a methodology of how to consistently implement daylight as part of an integrated building design with use of climate-based daylight modelling and evaluation of horizontal and vertical illuminance to ensure daylight sufficiency and minimizing glare (Karlsen et al., 2014). A finding from this previous work was that climate-based models needs to be implemented in userfriendly integrated simulation tools to make the methodology applicable for building designers. Climate-based daylight modelling is not a new invention. Already in 1995 Mardaljevic (1995) demonstrated how to carry out climate-based daylight calculations with use of the backward raytracing based simulation tool Radiance (Ward and Shakespeare, 1998). A few years later Reinhart and Walkenhorst (2001) proposed and validated the Daysim method for climate-based daylight calculations and Reinhart developed Daysim (2012) as a simulation tool. The Daysim method is based on combining a modified version of Radiance with Tregenza and Waters (1983) daylight coefficients and Perez et al. (1993) sky luminance distribution model. The stand-alone interface for Daysim is no longer maintained, but the method is continued to be developed, e.g. as plug-in to programs like DIVA for Rhino (Solemma, 2014). Within DIVA the daylight calculations can be combined with thermal building simulations from EnergyPlus on a hybrid model approach where the daylight and thermal simulations share artificial lighting and solar shading schemes (Jakubiec and Page 1/10

2 Reinhart, 2011). Open Studio (NREL et al., 2015) also provide the opportunity to combine Radiance and EnergyPlus simulations on a hybrid model approach. Recently the new Radiance three-phase method (Ward et al., 2011) was supported within Open Studio (Guglielmetti, 2014), where bidirectional scattering distribution functions (BSDF) are used to describe complex fenestration systems. A Danish contribution to the integrated thermal and daylight simulation software development has been proposed by Hviid et al. (2008). They developed a simple fully integrated thermal and daylight simulation tool, BuildingCalc/LightCalc (BC/LC), in order to evaluate the impact of daylight on building energy consumption for lighting. The tool combines the ray-tracing approach for incident initial light and the radiosity approach for internal daylight reflections. The European software WIS is used as a pre-processor to calculate the light transmission trough the glazing/shading system. Validation against Radiance showed good results for isotopic optical materials, however rather large deviations were seen for cases with complex shading systems, with relative errors up to 20% (Hviid et al., 2008). Yet, for early design phase, the error seen might be considered satisfactory (Reinhart and Breton, 2009). Fener (Bueno et al., 2014) is a recent addition to integrated thermal and daylight tools with the ability to analyse complex fenestration systems. It combines the Radiance three-phase daylight calculations (Ward et al., 2011) and thermal calculations on a time-step basis. In this way both thermal and daylight dependent parameters may be used in building control strategies without doing iterations between the daylight model and the thermal model. At the present time Fener only uses a shoe-box approximation energy model, yet, it may be extended with arbitrary building typologies in the future. The above illustrates that programs exists which combine daylight and thermal calculations, applicable for integrated design. Yet, to our knowledge there is a lack in uptake of such tools by building designers in Nordic countries. Reasons for this might be complexity of the programs, lack of training in the programs, that the programs are developed based on other markets etc. In order to increase the use of integrated thermal and daylight evaluations in the building design, it would be favourable if simulation tools already in use by the design community would be extended with reliable daylight calculation features. IDA Indoor Climate and Energy (IDA ICE) (Equa, 2011) is a Swedish developed simulation tool which has gained popularity among building designers in the Nordic countries during the last decade. This study presents work regarding the implementation and verification of a new daylight model in IDA ICE. It should be noted that this model implementation is potential and not released in any commercial product yet. Further this study illustrates how use of this new daylight model within an integrated framework contributes to supply the designer with an extensively more informative decision base for their design compared to conventional daylight design methods. METHODS Implementation of three-phase daylight calculations in IDA ICE The climate-based three-phase method in Radiance has been implemented in IDA ICE. A preprocessor convert the IDA ICE model to Radiance geometry and a post-processor import the Radiance simulation results. The theory behind the three-phase method is thoroughly described elsewhere, e.g. (Ward et al., 2011, McNeil, 2014), and the method is validated by McNeil and Lee (2012). Shortly, the calculation procedure is divided into three phases, see Figure 1. A Radiance ray tracing simulation generates luminous energy transfer coefficients relating (1) the luminance of sky patches to the incident light directions on the exterior side of the window, (2) the transmission through the window and (3) light from outgoing directions from the interior side of the window to desired interior points in the room. These coefficients are stored in three independent matrices; the daylight matrix, the transmission matrix and the view matrix respectively. The resultant illumination is simply obtained by matrix multiplication of the three phases in combination with a sky matrix that contains the average luminance of the sky patches for given times and sky conditions. Within IDA ICE, the user can choose between three sky division schemes with increasing accuracy; (1) Tregenza scheme with 145 divisions, (2) Reinhart scheme with 581 divisions and (3) Reinhart scheme with 2321 divisions, see Figure 1. The user can also choose among three levels of calculation accuracy with pre-defined Radiance parameters, see Table 1, or the user may set the Radiance parameters themselves. A major advantage of the three-phase method is that different types of windows and configurations of solar shadings can be studied rather easily by only exchange the transmission matrix in the calculation. At the present time, the user has to supply IDA ICE with the transmission matrices. These matrices may be generated by use of Window 7 (Huizenga et al., 2015). Window 7 uses a Klems angle basis of of hemispherical luminous coefficients defined by paired incident and outgoing angles to the fenestration system (Klems, 1994). An important approximation in the Klems Page 2/10

3 BSDF approach is that the optical properties of the layers in the fenestration system are spatially averaged over a suitably-sized area, i.e. spatially inhomogeneous systems are treated as homogeneous layers (Klems, 1994). Table 1: Pre-defined Radiance parameters for different levels of calculation accuracy. -ab= ambient bounces, -ad= ambient divisions, -lw = limit weight of each ray to be accounted for. Low Medium High DMX -ab 1 ad 500 lw 1e-3 -ab 3 ad 2000 lw 1e-4 -ab 5 ad lw 1e-5 VMX -ab 5 ad 5000 lw 1e-4 -ab 10 ad lw 1e-5 -ab 15 ad lw 1e-6 Figure 1: Principle illustration of the three-phase method (after (McNeil, 2014)) and the sky patch sub division according to (1) Tregenza-145, (2) Reinhart -581 and (3) Reinhart Test-cases for verification of model implementation A verification of the model implementation to IDA ICE has been carried out by comparing simulation results with full-scale measurements of a team office located in Oslo (latitude 59N, longitude 10E) and an experimental room located in Aalborg (latitude 57N, longitude 10E). The team office have relatively complex external obstructions and it is used to verify that the pre-processor export the geometry from IDA ICE correctly to the Radiance processor. The experimental room in Aalborg is equipped with integrated blinds and the case is used to verify that complex fenestrations are modelled correctly. Figure 2: (a-c) Illustration of the team office located in Oslo, Norway. (d-f) Illustration of the experimental room located in Aalborg, Denmark. Test case 1 External obstructions, team office Oslo The team office has the dimensions m and is situated at the corner of the 16th floor with one partly obstructed façade oriented 57 east of south and one unobstructed façade oriented 33 west of south, see Figure 2a. The south-east and south-west facades contain one and three windows respectively of 2.7 m 2 each, where three of the windows have some fins as external shading, see Figure 2b. All four windows are double-glazed, with a lowe coating and argon filling with the properties: direct solar transmission of 0.24, g-value of 0.27, visible light transmission at normal incidence of 0.50 and U-value of 1.1W/m 2 K. Page 3/10

4 The reflectivity of the internal surfaces was approximated by measurements with an illuminance meter. Table 2 summarises the visible reflectance of the internal surfaces and their colour. Indoor horizontal illuminance at the work plane was monitored with eleven illuminance sensors located on a grid across the room, 0.80 m above the floor, according to Figure 2c. The sensors were cosine corrected, connected to an Extech SDL400 illuminance meter with a basic accuracy of ± 4 %. The measurements were conducted in March Climatic data of hourly global radiation was collected from the BioForsk database (BioForsk) for the location of Ås, 30 kilometres south-east of the experimental location. The global radiation was divided into direct normal and diffuse horizontal radiation by use of the Skartveit-Olseth model (Skartveit et al., 1998). Test case 2 Complex fenestration systems, experimental room Aalborg The Cube is a test facility at Aalborg University. It has a south-oriented experimental room which is 2.76 m wide, 3.6 m deep and 2.70 m high. Figure 2d-f gives an illustration of the layout of the Cube and the experimental room. The south wall is equipped with a double layer glazing (2.76 m 1.60 m) with a U-value of 1.2 W/m²K, g-value of 0.36, direct solar transmission of 0.31 and a visible light transmission at normal incidence of The window is equipped with both an internal and external white 65 mm convex venetian blind, yet only the external blind was activated in the present study. The internal surfaces in the experimental room are kept in light colours. The reflectivity of the internal surfaces was determined using a spectrometer ( nm). Table 2 summarises the visible reflectance of the internal surfaces and their colour. Indoor horizontal illuminance at the work plane was monitored with six illuminance sensors in the centreline of the room at regular distance from the window, 0.85 m above the floor, see Figure 2f. All sensors were cosine corrected of type Hagner SD1/SD2 detectors connected to a Hagner MCA-1600 Multi-Channel Amplifier with a basic accuracy of ± 3 %. Global radiation was measured with a high accuracy CMP 22 pyranometer placed horizontally on the roof of the experimental room. The fraction of direct and diffuse radiation was modelled by use of the Skartveit-Olseth model. The measurements were conducted in July Table 2: Reflectance and colour of the internal surfaces for all evaluated cases. Surface Reflectance Colour Oslo Aalborg Test case Oslo Aalborg Test case Walls White White White Floor Brown Grey Grey Ceiling White White White Parameter study In order to illustrate the benefit of conducting an integrated design compared to conventionally static daylight analysis, a parameter study is carried out. In the parameter study a cell office of 10 m 2 (2.5 m 4 m) floor area with an unobstructed horizon located in Oslo is considered. The opaque part of the façade has a U-value of 0.09 W/m²K, while the transparent part of the façade is a 3-pane glazing with krypton filling and a U-value of 1.0 W/m²K, g-value of 0.53, direct solar transmission of 0.39 and a visible light transmission at normal incidence of Table 2 summarises the visible reflectance of the internal surfaces and their colour for the test case. Different glazing to floor ratios are considered in the parameter study, see Figure 3, as well as the four main sky directions; south, west, north and east. Figure 3: Visualisation of the façade of the models with different glazing to floor area. Page 4/10

5 Ventilation air flow rates (6 m 3 /hm 2 ), internal gains from equipment (6 W/m 2 ) and operating hours (7-19) are set according to the Norwegian standards NS3701 (Standard Norge, 2012) and NS3031 (Standard Norge, 2007). Further, the room is occupied by 1 person, the installed light power in the room is 6.2 W/m 2 and the lighting is controlled to maintain 500 lux on the work plane during occupied hours. The room is equipped with heating and cooling controlled to keep the room air temperature within C. Weather data from NS 3031 is used as boundary conditions in the simulations. As illustrated in Figure 3, the cell office is equipped with external blinds. The blind is controlled in order to avoid glare and overheating. The blind is activated if one of two sensors placed at the side walls 1.5 m into the room and 1.2 m above the floor is exposed to illuminances of 1700 lux or higher or if vertical irradiance at the façade exceeds 150 W/m 2 while at the same time the interior temperature is 23.5 C For the conventional design, daylight is according to the Norwegian guidelines to the building regulations assessed as satisfying if the glazing to floor ratio is equal or higher than 10 % or if the average daylight factor (DF) in the room is minimum 2 %. The daylight factor is calculated under a CIE overcast sky. For assessment of energy demand for lighting the LENI number is calculated according to the European standard EN (CEN, 2007). Operation hours according to NS 3031 is used in the LENI calculation and since this differ from the operation hour given in EN 15193, the division of operation hours with and without daylight is calculated according to the procedure given in ISO-DIS Neither parasite load nor emergency lighting is considered in the LENI calculation or in the calculation of energy use for lighting in the integrated design approach. RESULTS Verification of model implementation Figure 4 compares measurements and simulations of daylight conditions in the team-office in Oslo on a sunny day in March 2013 for a number of representative locations. Some diversity is seen, especially before and after the sensors are hit by direct sun. These differences may be explained by the model simplifications used in the three phase model, both the sky patch approximation which extend the sun disc over a larger area than the exact sun position and the low resolution Klems BSDF basis for the incident and outgoing angles to the fenestration system. Yet, the general trend is promising and these results indicate that the geometry and external shading elements are treated correctly in the pre-processor and contribute to reliable daylight predictions. Figure 4: Comparison measurements and simulations for a number of representative positions in the team office located in Oslo for a sunny day Page 5/10

6 Figure 5 present some representative comparisons of measurements and simulations of daylight conditions in the experimental room in Aalborg for two sunny days in July, one day without solar shading (Figure 5 a-c) and one day with the venetian blind activated with a tilt angle of approximately 75 (Figure 5 d-f). On an overall basis, the simulations reproduce well the measurements for a variety of locations within the room. However, some severe deviations are seen for sensor 1 when the solar shading is deactivated and for sensor 2 in the morning and in the afternoon when the solar shading is activated. For the former case it can again be explained by the fact that low resolution Klems BSDF division is utilised which disperses energy passing through the window to a greater extent than what is the case in reality. In this certain case, the sensor is in reality just avoiding being hit by the sun, while in the simulation the sun patch is expanding a bit lager which makes the sensor location to be within the sun patch, see Figure 6. The deviation seen for sensor 2 can be explained by the fact that the external venetian blind is installed with a distance to the façade of approximately 20 cm. As a consequence, a light stripe is penetrating into the room through the openings that occur at the edge of the window, see Figure 7. This phenomenon is not captured by the three-phase method where the optical properties are spatially averaged over a suitably-sized area in the BSDF function so that spatially inhomogeneous systems are treated as homogeneous layers. Figure 5: Comparison measurements and simulations in the experimental room in Aalborg for a sunny day without solar shading (a-b) and a sunny day with activated solar shading (c-d). Figure 6: Photo inside the experiment room at , and rendering from Radiance at the same time showing that the in the simulation the energy passing through the window is dispersed to a greater extent than what is the case in reality. Page 6/10

7 Figure 7: Photo of the experiment room at 09.30, and rendering from Radiance showing that the light stripe penetrating into the room is not detected in the simulation. Parameter study Figure 8 illustrate the DF for the cell office used in the parameter study for different glazing to floor ratios. Since the CIE overcast sky is symmetric around zenith, the DF is independent of orientation. Figure 8: Daylight factor for the cell office with different glazing to floor ratios. Table 3 gives the percentage of total occupant hours with thermal dissatisfaction and Figure 9 gives the results of daylight sufficiency, inverse indication of view in the form of the percentage of the occupied time when the solar shading is activated, energy demand for the main energy posts in addition to the LENI number for the different configurations of the cell office used in the parameter study. The daylight sufficiency is given as spatial daylight autonomy which indicates the fraction of the room that is illuminated by 300 lux of daylight alone for 50 % or more of the occupied hours (DA _300_50% ). The percentage of the work hour when the solar shading is activated indicates the time when the view to the outside is obstructed, which in addition to daylight sufficiency is an important parameter to evaluate as view might be a significant factor for occupants comfort. Table 3: Percentage of total occupant hours with thermal dissatisfaction. Glazing to floor ratio Orientation 10 % 20 % 30 % 50 % South 8 % 10 % 11 % 11 % West 9 % 10 % 11 % 12 % North 10 % 11 % 11 % 12 % East 9 % 11 % 11 % 12 % Page 7/10

8 Figure 9: Top: Results of daylight sufficiency (bars) and inverse indication of view (line graph). Bottom: Energy result of the parameter test (bars) and line graph with indicators for the light energy demand both for the integrated design and the conventionally LENI number. DISCUSSION The comparison between measurements and simulations show promising results and indicate that the coupling between IDA ICE and Radiance is working satisfactory. The deviations seen between measurements and simulations are most likely caused by model approximations as the sky patch approximation, subdivision of the fenestration system according to the Klems basis and the Klems BSDF function approximation which treats spatially inhomogeneous systems as homogeneous layers. Due to these model simplifications deviations might occur when considering specific points. However, when evaluating the daylight sufficiency in a room on an overall basis and over a sufficient time period, these small, local and time dependent deviations might have minor importance, especially for an integrated design where the main goal is to predict how the fenestration characteristics influence visual and thermal comfort and energy use, predict the need for use of solar shading to avoid glare and overheating and again evaluate how this influence the daylight sufficiency, thermal comfort, view to the outside and energy demand on an overall basis. The designer should, however, be aware of the limitations associated with the three phase model; the neglecting of geometrical features of the fenestration system may for instance limit its application in detailed discomfort glare analysis where these features might be essential for detecting contrast based glare. Yet, over exposure of light may still be indicated with use of the three phase model and it is assessed that use of the model may contribute to make a satisfying basis for a glare free environment within an integrated framework. A parameter study was carried out in order to illustrate the benefit of conducting an integrated design compared to a conventionally static daylight analysis. The results from the parameter study support earlier findings, that the pre-accepted 10 % glazing to floor area rule does not necessary secure satisfying daylight conditions in modern buildings with thick well insulated walls and light transmission Page 8/10

9 that deviate from 80 % (Karlsen et al., 2013, Smits et al., 2013). Further, if using the conventional average DF and the LENI number as criteria for daylight sufficiency and energy use for lighting, these metrics indicate that the higher glazing ratio the better. However, when assessing the results from the integrated design approach in Figure 9 and Table 3, it is evident that this is not the whole truth. With use of the integrated design approach the influence of e.g. orientation and use of solar shading is accounted for in the daylight analysis. It is apparent that the daylight sufficiency increases with increasing glazing fraction up to a certain level, but after exceeding this level the daylight sufficiency actually decrease and energy for artificial lighting may increase due to extensive need for use of solar shading to avoid glare and overheating. As a consequence of activated solar shading, the view to the outside may also be obstructed for a relatively high portion of the occupied time, especially for south east and west façade orientations. When doing integrated evaluations it is additionally clear that the energy demand may increase with increasing glazing ratio as an effect of high heat loss through the glazing, see Figure 9. Table 3 further reveal that the percentage of occupied time outside the comfort zone also may increase with increasing glazing ratios due to warm and cold radiation from the window. The differences seen in thermal discomfort for the different configurations in the present study are however small; this is principally a result of utilizing ideal heating and cooling in the simulation and the consequences of different façade configurations and orientations are therefore more distinct in the predicted energy demand visualised in Figure 9. For the specific cell office investigated in this study, Table 3 and Figure 9 indicates that the 20 % and 30 % glazing to floor area might be satisfying solutions depending on the façade orientations and it is apparent that the final design decision is a compromise between comfort aspects and predicted energy demand, which again support the importance of doing holistic considerations. When assessing Figure 9 it is obvious that the façade orientation strongly effect the daylight sufficiency and need for use of solar shading which again influence the energy demand for lighting. This information is not available with use of the daylight factor and LENI number (which daylight dependency is based on the DF) due to the limitations of the DF, limitations that is thoroughly discussed elsewhere, e.g. (Mardaljevic et al., 2009). CONCLUSIONS This study has illustrated that the three-phase Radiance model has been successfully implemented into IDA ICE and that the model on an overall basis is able to reproduce real world conditions. If released in an official commercial version, this new daylight features would make IDA ICE a powerful tool for making integrated analysis of daylight, thermal comfort and energy use. Different configurations of a cell office has been studied both with use of the new integrated features of IDA ICE and by use of conventional daylight design methods. It is evident that the integrated design method provides vital information of how different design parameters like orientation and use of solar shading affect the relation between daylight, thermal comfort and energy use, information which is unavailable with conventional daylight design methods. Annual daylight calculations are, however, more time demanding than a static daylight calculation, which is one of the drawbacks of the proposed methodology. At the present time, the computational time consume is affordable at room level evaluations, while it might be too expensive if it is required to evaluate all rooms in a large building. Development in computer power and optimization of the calculation process might reduce this problem in the future. Still, currently it is recommended that the integrated design method is adapted in design of low-energy buildings and passive houses at room level evaluations of critical and representative room in order to make more reliable predictions of daylight, thermal comfort and energy use and thereby be able to obtain the sustainable low-energy and comfortable buildings we want for the future. ACKNOWLEDGEMENT We would like to thank Silje N. Andressen and Silje Bjørkeng, master students at Oslo and Akershus University College of Applied Science, and Mingzhe Liu, Hicham Johra, Jérôme Le Dréau and Rasmus Lund Jensen at Aalborg University for their cooperation and assistance throughout the planning and execution of measurements in Oslo and Aalborg respectively. Thanks are also due to the building owners and the plant managers for their cooperation and help. REFERENCES An, J., S. Mason and A. Ten (2010). Integrating advanced daylight analysis into building energy analysis. Proceeding in Fourth National Conference of IBPSA-USA, New York City. Bueno, B., E. Guidolin, J. Wienold and T. E. Kuhn (2014). A Radiance-based building energy model to evaluate the performance of complex fenestration systems Proceeding in 2014 ASHRAE/IBPSA-USA Building Simulation Conference, Atlanta, Georgia, USA. Page 9/10

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