Daylighting utilization in the window energy balance metric: Development of a holistic method for early design decisions

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1 Daylighting utilization in the window energy balance metric: Development of a holistic method for early design decisions Authors: Jiangtao Du Bengt Hellström Marie-Claude Dubois Division of Energy and Building Design, Department of Architecture and the Built Environment, LTH, Lund University April 22, 14

2 Daylighting utilization in the window energy balance metric: Development of a holistic method for early design decisions April 22, 14 AUTHORS Primary author: Jiangtao Du (Lund University) Contributor: Bengt Hellström (Lund University) Project leader and editor: Marie-Claude Dubois (Lund University) Distribution Classification: Unrestricted This report was printed and is available at: Division of Energy and Building Design Department of Architecture and Built Environment LTH, Lund University 2

3 KEYWORDS Houses, energy use, energy balance, daylighting, daylight utilization, electric lighting, heating, cooling,, shading, s, simulation. 3

4 ACKNOWLEDGEMENTS The authors thank the Swedish Energy Agency (Statens energimyndighet, project ) and the VELUX Group, Denmark for funding this research. 4

5 Preface This report presents a study of the impact of windows on overall energy performance of single family, detached houses located in two European climates: the middle of Sweden (cold climate) and Southern France (warm climate). The parameters studied include climate and house characteristics, window properties (sizes, thermal, solar and visual transmittances) and positions as well as shading devices (interior and exterior) and. The heating, cooling and lighting energy demands are analysed in order to demonstrate how various windows and shading systems settings may affect the overall energy balance of a typical house in different climatic conditions. This project pursues the main objective of developing a methodology for obtaining a holistic energy balance metric of window performance that includes the effect of daylight utilization, with and without the use of shading devices. This number would be a key figure for architects and planners to demonstrate the energy saving potential linked to daylight utilization at an early design stage. A secondary objective of this project is to assess the daylight utilization potential for the residential sector in the Swedish climate. The project was achieved in collaboration with the VELUX Group, who provided basic house models descriptions and detailed advice regarding the settings in the simulations. 5

6 Executive summary This report presents a study of the impact of windows on overall energy performance of single family, detached houses in two European climates: the middle of Sweden (cold climate) and Southern France (warm climate). The parameters studied include climate and house characteristics, window properties (sizes, thermal, solar and visual transmittances, positions), as well as shading devices (interior and exterior) and. The heating, cooling and lighting energy use were analysed using advanced dynamic energy simulations with DesignBuilder (interface of EnergyPlus) in order to demonstrate how various windows and shading systems may affect the overall energy balance of typical houses in different climatic conditions. The Swedish house model was defined based on the Swedish building code BBR 19: BFS 11:26 (6:251) for and BBR : BFS 13:14 (9:2) for construction U-values, thermal bridges, etc. The French house model was defined based on information provided directly by the Velux Group. The study shows that the house s basic construction (U-values, airtightness, with heat recovery) and architectural aspects have a large impact on the overall energy balance. In this case for instance, the Southern house had a higher energy demand than the Northern house, and this was mainly due to the fact that the Southern house had higher U-values and air change rate for the building envelope, no heat recovery on the, and a higher envelope-to-volume ratio (thus more heat losses). The Southern house thus had an energy balance dominated by the heating demand, which would have been expected for the Northern house. Interestingly, the good construction (low U-values, airtight construction, heat recovery on ) used for the Northern house resulted in an energy balance where the lighting demand played a secondary but significant role in the overall energy balance although heating was still the dominant energy end-use. For the Northern house under cold climate, larger window sizes give rise to higher heating and cooling demand but lower lighting demand while for the Southern house, larger window sizes yield lower heating and lighting demands but higher cooling demand. In addition, the results clearly show that the impact of orientation is more or less negligible on the overall energy balance, mainly due to the fact that windows were distributed rather evenly on all facades in the studied cases. Furthermore, the results indicate that the use of an is clearly the most efficient measure to reduce cooling energy demand compared to the use of inside or. For small window sizes (%-window-to-floorratio-wgr), the selection of environmental control strategy (shading or ) 6

7 has a relatively negligible impact on overall energy demand, as long as one of these strategies is applied. For both the Northern and Southern houses, the lighting energy savings from daylight utilization are clearly demonstrated in this study, even in a smaller window area (WGR % -- - %). Interestingly, when comparing % with % WGR, the study shows that the additional heat losses due to windows are compensated by free daylight and passive solar heat gains. Generally, increasing the window area beyond %-WGR does not bring significant additional savings in terms of lighting energy use, especially in the Southern house. This could be due to the fact that %-WGR is sufficient to reach the desired average illumination levels considered in this study (15 lux). However, for the Northern house, larger WGR permit to offset the effect of shading on the lighting performance. This study showed that daylight utilization could provide electricity savings corresponding to at least one third of electric lighting demand in Swedish and French houses, going from about 12 kwh/m 2 yr to about 7-8 kwh/m 2 yr, with most savings achieved with the use of %- WGR and only marginal additional savings obtained with larger windows (%-WGR). Thus, it can be concluded that the potential for daylight utilization is real and significant in the residential sector, even considering reasonable window sizes that would limit the heating and cooling demands. Although this study yields a series of valuable results and information, it is solely based on theoretical energy simulations, using inputs and settings that could be very different from a real context. The results of this study should be considered bearing in mind the basic limitations of the simulation settings. 7

8 Table of Contents Preface... 5 Executive summary... 6 Table of Contents... 8 List of abbreviations... 9 List of figures... List of tables Introduction OBJECTIVES OF THIS RESEARCH Literature review Method LOCATIONS, ORIENTATION AND SURROUNDING CONDITIONS HOUSE MODELS Northern house Southern house WINDOW AND SHADING SYSTEMS Northern house Southern house SIMULATIONS Results NORTHERN HOUSE Window areas and energy performance Overall energy performance SOUTHERN HOUSE Window areas and energy performance Natural, shading devices and energy performance Overall energy performance Conclusions and discussion References

9 List of abbreviations WGR Window-to-floor ratio ach Air change(s) per hour 9

10 List of figures Figure 1: 3D model of Northern house Figure 2: Plan and section of northern house (units: mm) Figure 3: Space plan in the Northern house Figure 4: 3D model of Southern house Figure 5: Plan and section of Southern house (unit: mm) Figure 6: Space plan in the Southern house Figure 7: Window distributions of Northern house WGR % Figure 8: Window distributions of Northern house WGR % Figure 9: Window distributions of Northern house WGR %.... Figure : Window distributions of Northern house WGR % Figure 11: Window distributions of Southern house WGR % Figure 12: Window distributions of Southern house WGR % Figure 13: Window distributions of Southern house WGR % Figure 14: Window distributions of Southern house WGR % Figure 15: Heating, cooling and lighting demand in Northern house (no and no shading device) Figure 16: Heating, cooling and lighting demand in Northern house ( and without shading) Figure 17: Window areas and heating, cooling and lighting demand in northern house ( and no ) Figure 18: Heating, cooling and lighting demand in Northern house ( and ).. 37 Figure 19: Heating, cooling and lighting demand in Northern house (inside and no ) Figure : Heating, cooling and lighting demand in northern house (inside and ) Figure 21: Annual energy performance between six environmental settings (Northern house, WGR %) Figure 22: Annual energy performance between six environmental settings (Northern house, WGR %) Figure 23: Annual energy demand according to orientation (Northern house, WGR %) Figure 24: Annual energy demand according to orientation (Northern house, WGR %) Figure 25: Heating, cooling and lighting demand in Southern house (no and no shading device) Figure 26: Heating, cooling and lighting demand in Southern house ( and no shading) Figure 27: Heating, cooling and lighting demand in southern house ( and no ) Figure 28: Heating, cooling and lighting demand in Southern house ( and ).. 51 Figure 29: Heating, cooling and lighting demand in Southern house (inside and no ) Figure : Heating, cooling and lighting demand in Southern house ( and inside ) Figure 31: Annual energy performance between six environmental settings (Southern house, WGR %) Figure 32: Annual energy performance between six environmental settings (Southern house, WGR %) Figure 33: Annual energy performance according to orientation (Southern house, WGR %) Figure 34: Annual energy performance according to orientation (Southern house, WGR %).... 6

11 List of tables Table 1: Thermal, solar and visual transmittances of windows on South, East and West facades (two panes).. 22 Table 2: Thermal, solar and visual transmittances of windows on North facade (three panes) Table 3: Thermal, solar and visual transmittances of windows on South roof (two panes) Table 4: Thermal, solar and visual transmittances of windows on North roof (three panes) Table 5: Properties of shading Table 6: Thermal, solar and visual transmittances of windows at facade walls (two panes) Table 7: Thermal, solar and visual transmittances of windows on roof (two panes)

12 1 Introduction The indoor environment and energy use of a house are substantially affected by the window characteristics and configurations (Urbikain & Sala, 9) (EN/ISO, ). In general, the evaluation of windows is carried out in a specific built environment since both building type and outdoor climate conditions may have a significant effect on the energy and environmental performance (Schultz & Svendsen, 1998). Window energy performance relating to the thermal environment could be the first key issue to consider by the house inhabitants, architects or builders. The thermal transmittance of the window (even one with a good thermal performance) could be four to five times larger than that of a well-insulated wall (Schultz & Svendsen, 1998) (and up to ten times in a passive house). Overall, heat losses from windows could even be responsible for around one third of the total energy losses in a typical residential building (Karabay & Arici, 12). On the other hand, windows can contribute to passive energy gains by allowing solar radiation and light into the house, which may also increase the risk for overheating (Schultz & Svendsen, 1998). An optimal energy balance for windows is therefore a basic requirement for houses with high energy performance. Windows also provide daylight, which has been regarded as one indispensable environmental factor in residential buildings (British Standard, 8). Daylight can illuminate the indoor tasks, replace electric lighting and contribute to improve human health and wellbeing on the ground of physiological and psychological aspects (British Standard, 8) (Veitch & Galasiu, 12). Windows could be used as an efficient approach to deliver daylight into buildings (CIBSE, 12). 1.1 Objectives of this research This report presents a study of the impact of windows on overall energy performance of single family, detached houses in two European climates: the middle of Sweden (cold climate) and Southern France (warm climate). The parameters studied include climate and house characteristics, window properties (sizes, thermal, solar and visual transmittances, positions), as well as shading devices (interior and exterior) and. The heating, cooling and lighting energy use were analysed in order to demonstrate how various windows and shading systems may affect the overall energy balance of a typical house in different climatic conditions. 12

13 The main goal of this research is to assess the effect of different house, climate, window and environmental settings ( and shading) on energy use, including heating, cooling and lighting energy demands, considering realistic house conditions and settings for a Northern and Southern European climate. 2 Literature review For the window use and lighting energy savings, most previous studies have been carried out in commercial and public premises (LBNL, ). However, this topic has recently received more attention in the residential building sector (Veitch & Galasiu, 12) (Mardaljevic, Andersen, Roy, & Christoffersen, 11). In Europe, a recent study (Foldbjerg, Roy, Duer, & Andersen, ) investigated the impact of windows on overall energy use (lighting, cooling, heating) in a single family house (with % window-to-floor area ratio) located in different cities. The results indicated that the window was the most energy-efficient technology to provide biological light levels (5-25 lx). Even though the basic conditions for energy analysis were significantly oversimplified, a clear relationship between windows and electrical lighting savings was expressed in this study. Another study achieved in Sweden in passive houses (Persson, Roos, & Wall, 6) pointed out that enlarging a North oriented window glazing was actually a potentially good solution to increase daylight utilization and save energy, provided that energy-efficient windows are used. Furthermore, the integration of daylighting and electric lighting systems has been suggested in several important building standards in order to achieve energy-efficiency in buildings (CIBSE, 1999) (CIBSE, 12). 3 Method 3.1 Locations, orientation and surrounding conditions The first location studied for the basic house was Stockholm (Latitude 59.65, Longitude ), the Swedish capital, which represents a Northern house located in cold climate conditions. The second location was Agen (Latitude 44.16, Longitude.6 ) in Southern France, which represents warmer climatic conditions. Three orientations were analysed for each house: South, North and West. In addition, it was assumed that each house was surrounded by neighbouring buildings or obstructions, which was simulated in the computer program by a shading wall with an obstruction angle of 5. 13

14 3.2 House models Northern house A two-story, single family detached house (Figure 1) was modelled in the computer program Design Builder with typical Swedish building characteristics and features (Myresjöhus, 13). This house had a ground floor and an attic floor (Figure 2) with a simple rectangular plan and South orientation (basic model). The house s main dimensions were: length 12m, width 8m, wall height 3.2m. The house had a 45 double sloped roof. The house was modelled including interior partitions as represented in Figure 3. The ground and attic floors each included three main zones. The windows were installed on the external wall and sloped roof. Figure 1: 3D model of Northern house. The thermal properties (U-value) of the house envelope were as follows: U(wall) =.15 W/m 2 K; U(roof) =.1 W/m 2 K; U(ground floor) =.2 W/m 2 K. The building envelope was generally based on Swedish light-weight construction. 14

15 Figure 2: Plan and section of northern house (units: mm). Figure 3: Space plan in the Northern house Southern house A one-story single family detached house (Thiers, Beinsteiner, & Peuportier, 11) (Kragh, Laustsen, & Svendsen, 8) (Figure 4) was studied as the Southern house located in 15

16 Agen. This house had a single ground floor (Figure 5) with a simple rectangular plan and a South orientation (basic model). The house s dimensions were: length 12m, width 8m, wall height 2.5m (Thiers, Beinsteiner, & Peuportier, 11). The roof was, in this case, a 15 double sloped roof. The ground floor included three rooms separated by internal partitions (Figure 6). The windows were installed on both the wall and roof. The thermal properties (U-value) of the envelope were as follows: U(wall) =.45 W/m 2 K; U(roof) =.28 W/m 2 K; U(ground floor) =.4 W/m 2 K. The building envelope was a typical French heavy construction. Figure 4: 3D model of Southern house. Figure 5: Plan and section of Southern house (unit: mm). 16

17 Figure 6: Space plan in the Southern house. 3.3 Window and shading systems Northern house The WGR (window-to-floor ratio) was defined as the ratio of window area to the internal heated floor area. Three different WGR were studied including % (no window), approximately % (small size) and approximately % (large size). Figure 7 shows the window distribution and sizes for different facade walls and roofs in the Northern house, which had two small WGR values of.8% at attic floor level and % at ground floor level. The positions of windows across the envelope were ly set in the centre of external wall or roof for each room (Figure 8). Similarly, a larger window area (WGR %) was studied (Figure 9, Figure ). 17

18 Figure 7: Window distributions of Northern house WGR %. 18

19 Figure 8: Window distributions of Northern house WGR %. 19

20 Figure 9: Window distributions of Northern house WGR %.

21 Figure : Window distributions of Northern house WGR %. According to thermal, solar and visual transmittances, various window systems were studied for different facades and roofs in the Northern house model. The windows used on South, East and West walls were double-pane windows with properties presented in Table 1. However, the North wall had more energy-efficient windows with three panes (Table 2). Table 3 and Table 4 show the size, U-value, g-value and visual transmittance of windows for the South (two panes) and North roof (three panes) respectively. The linear loss between glazing and frame was.49 W/mK. The windows used in this study were defined based on VELUX products and the DesignBuilder window library (DesignBuilder, 13). 21

22 Table 1: Thermal, solar and visual transmittances of windows on South, East and West facades (two panes). Size (mm) value (W/m 2 K) value (W/m 2 K) U(window)- U(glazing)- U(frame)- value (W/m 2 K) g- value Visual Transmittance 5x x x x Table 2: Thermal, solar and visual transmittances of windows on North facade (three panes). Size (mm) value (W/m 2 K) value (W/m 2 K) U(window)- U(glazing)- U(frame)- value (W/m 2 K) g- value Visual Transmittance 8x x Table 3: Thermal, solar and visual transmittances of windows on South roof (two panes). Size (mm) value (W/m 2 K) value (W/m 2 K) U(window)- U(glazing)- U(frame)- value (W/m 2 K) g- value Visual Transmittance 11x x Table 4: Thermal, solar and visual transmittances of windows on North roof (three panes). Size (mm) value (W/m 2 K) value (W/m 2 K) U(window)- U(glazing)- U(frame)- value (W/m 2 K) g- value Visual Transmittance 22

23 11x x A medium-opaque was used as the basic shading device for each window (wall and roof windows) when required. The basic properties of the shading are presented in Table 5. The was installed either inside or the window. Table 5: Properties of shading. Thickness Conductivity Solar transm. Solar reflectanctance Visible transm. Visual reflec- Long wave Long wave transm. (m) (w/mk) emiss Southern house The French house had three WGR including % (no window), approximately % (small size) and approximately % (large size). Figure 11 shows the window distribution and size for different facade walls and roofs for the Southern house, which had a small WGR of.5% at ground floor. The positions of windows across the envelope were evenly set in the centre of the external wall or roof of each room (Figure 12). A larger window area (WGR.8%) was also studied (Figure 13). The positions of the larger windows are shown in Figure

24 Figure 11: Window distributions of Southern house WGR %. 24

25 Figure 12: Window distributions of Southern house WGR %. 25

26 Figure 13: Window distributions of Southern house WGR %. 26

27 Figure 14: Window distributions of Southern house WGR %. In this case, all windows studied were double pane assemblies. The properties of wall windows are shown in Table 6, while Table 7 displays the properties of roof windows. The linear loss between glazing and frame was.49 W/mK. The windows used in the study were defined based on VELUX products and the DesignBuilder window library (DesignBuilder, 13). 27

28 Table 6: Thermal, solar and visual transmittances of windows at facade walls (two panes). U(frame)- Size U(window)- U(glazing)- g- Visual value (mm) value (W/m 2 K) value (W/m 2 K) value Transmittance (W/m 2 K) 6x x x x x x Table 7: Thermal, solar and visual transmittances of windows on roof (two panes). Size (mm) value (W/m 2 K) value (W/m 2 K) U(window)- U(glazing)- U(frame)- value (W/m 2 K) g- value Visual Transmittance 78x x x The same shading device (Table 5) was used in this Southern house. The was installed either inside or windows. 3.4 Simulations The energy performance of the house models was simulated using the DesignBuilder program, which is an advanced interface to the well-known dynamic simulation program EnergyPlus. This program allows predicting heating, cooling and lighting demands simultaneously. It is a state-of-the-art and dynamic simulation package, which provides a comprehensive range of energy consumption and environmental data (thermal and visual comfort,, etc) shown in annual, monthly, daily, hourly or sub-hourly intervals (DesignBuilder, 13) (EnergyPlus, 13). For Northern and Southern houses, the annual heating and cooling demands (kwh/m 2 ) were the first part to be considered. Under the French climate, it is normal to include cooling 28

29 systems into the Southern house as part of the normal building installations. Although it is not necessarily common in Sweden, the cooling demand was studied here in order to obtain a proxy for overheating. For thermal environment, the set points of 21 C and 26 C were used for heating and cooling systems respectively. The simulations were performed considering a single thermal zone for the ground and attic floors. Internal heat gains corresponding to 2 W/m 2 (excluding electric lighting) were also considered in the simulations. Airtightness and rates and schedules were set differently in each house. In the Northern house, a constant infiltration rate of.1 ach was programmed. A mechanical system was also programmed considering a minimum fresh air supply of.35 l/sm 2 (corresponding in this case to.5 ach) and a heat recovery with an efficiency of 8%. The mechanical and heat recovery were set as always on (even during the summer). However, note that the windows were considered opened by the program when indoor temperature rose above 24 C and the air change rate was very high at 3 ach (and constant) in this case. Cooling was initiated when the indoor temperature rose above 26 C. The Southern house, however, had a high infiltration rate of.5 ach. No mechanical was assumed in this case, which is more typical for French construction standard. In both Northern and Southern houses, through windows was added with the aim to reduce overheating during the cooling season. The for cooling was programmed to be initiated at 24 C (set point); it was turned off when outdoor temperature was higher than the indoor temperature in order to avoid heating the indoor air with air. The annual electric lighting demand (kwh/m 2 ) was included as one important part of the total energy calculation of each house. The zone settings for lighting calculations follow the spaces divided by partition walls. The light sensors were installed at the centre of each room in the two houses. In general, the target illuminance was 15 lx, which is regarded as the minimum lighting level for visual purposes in residential buildings. This level was considered representative as an average workplane illuminance value roughly corresponding to what people would normally use in residential spaces in the early morning or at night. A working plane (.8 m above the floor) was assumed for daylighting and lighting calculations. The electric lighting was controlled through a simple linear model corresponding to the daylight illuminance level. The lighting power density was set to 2 W/m 2 per lx (EnergyPlus, 13). The 15 lx ambient electric lighting was considered to be turned on from 6:-8: and 16:-23: hours on weekdays and from 7:-24: hours on weekends. Thus, the 29

30 internal heat gains from electric lighting combined with other internal heat gains were between 2 and 5 W/m 2, depending on whether the electric lighting was switched on or off. The reflectance of internal walls, floor and ceiling was set to.5,.3 and.7 respectively, which corresponds to the materials in the building construction settings. For the two houses, the shading device was operated by a model called Night heating and day cooling in DesignBuilder. In this model, the shading device is down at night when heating is on and during daytime when there is a cooling load (based on the previous hour in the iterative calculation) (DesignBuilder, 13) (EnergyPlus, 13). Note that the program does not allow to evaluate the effect of both shading device (interior and exterior) active simultaneously. In addition, the photometric properties of the external ground surface (affecting solar and daylight calculation) were as follows: ground reflectance of.2 without snow and.8 with snow. DesignBuilder evaluates the occurrence of snow based on climate data and adjusts ground reflectance accordingly. 4. Results 4.1. Northern house This section presents the results obtained regarding the impact of window area and environmental settings (shading device and ) on energy performance in the Northern house Window areas and energy performance This section presents results related to window areas and energy use under six different environmental settings: 1. without and shading device; 2. with and without shading device; 3. with and without ; 4. with and ; 5. with inside and without ; 6. with and inside. Setting 1 (without and shading device)

31 The results for the first setting are presented in Figure 15. In general, annual heating and cooling demands increase with increasing WGR while the reverse effect is obtained for electric lighting: increasing WGR results in a reduction in annual lighting demand. The cooling demand increases from an average of 1. kwh/m 2 yr for the case without windows to 7.1 kwh/m 2 yr for %-WGR and 38.3 kwh/m 2 yr for %-WGR (average for the three orientations). The increase in cooling with larger windows is thus substantial but the cooling demand of the no-window model is very small. Figure 15c also shows that the no window model yields the highest electric lighting energy use, while %-WGR and %-WGR yield lighting energy savings of 34% and 42% respectively compared to the no window case. Therefore, the effect of increasing the WGR beyond % is marginal for electric lighting, which is probably due to the fact that there is sufficient daylight in the space to reach an average 15 lux on the sensor with %-WGR. Note also that most electric lighting is used early in the morning and at night when there is no or little daylight outdoors. A significant effect of orientation on heating and cooling energy demand is obtained for large WGR only (%). As expected, facing South results in heating energy savings compared to other orientations while the cooling demand is minimised with the North orientation. The orientation has no significant effect on electric lighting energy use under the Swedish climate conditions in this study. This may be explained by the predominance of overcast sky conditions and position of the measurement point in the simulations (middle of room), where most daylight is reflected and diffuse. Setting 2 (with and without shading device) The results for the simulations with and no shading device are presented in Figure 16. The variations of heating, cooling and lighting energy use are similar to the ones presented for the previous environmental setting (setting 1). However, the use of has a clear beneficial effect on the cooling demand, especially for the large WGR (%-WGR). Note, as stated earlier, that the windows were considered opened by the program when indoor temperature rose above 24 C and the air change rate was very high at 3 ach (and constant) in this case. Cooling was initiated when the indoor temperature rose above 26 C. In the case without and shading, the cooling demand was 1. kwh/m 2 yr for the no-window case, 7.1 kwh/m 2 yr for %-WGR and 38.3 kwh/m 2 yr for %-WGR (average for the three orientations). Adding resulted in a cooling demand which was on average 2. kwh/m 2 yr for %-WGR and 22.5 kwh/m 2 yr for %-WGR (average for the three orientations). Natural thus reduces the cooling demand by more than % for the %-WGR, which is a substantial reduction. 31

32 Setting 3 (with and without ) The results for the cases with and without are presented in Figure 17. In this case, the heating demand varies in a similar way as shown previously. Note however that the heating demand increases slightly (by.6 kwh/m 2 yr for the %- WGR and by 2.9 kwh/m 2 yr for the %-WGR compared to results of setting 1 no shading and no ). This could be an effect of a sub-optimisation of the control system for the shading device. In this case, it is possible that the program sets the down when it would be preferable to have it up. This can happen when shading is still in use for the hours where the solar gains would exceed the increased insulation gains (early and late hours of the day). This parameter is sensitive and can be refined or adjusted to determine the best use of the shading device in a given climate. The shading results in the same cooling demand for the small window size (%-WGR) as the no-window case. The large window case (%-WGR) sees a substantial decrease of cooling demand with the use of compared to the previous setting ( and no ). The cooling demand with is around 1/ of the case with and around 1/ of the setting without and. However, the slightly increases the lighting energy consumption of the house with windows, but this effect is negligible compared to the effect on cooling loads. Setting 4 (with and ) With and (Figure 18), the general varying trends of heating and lighting are similar to the previous setting (Figure 17). However, cooling demand in the house with windows is lower than for the house without windows. The results show that the combination of shading and is an efficient strategy to control overheating in summer time, even for houses with large glazing. Setting 5 (with inside and without ) With inside and without (Figure 19), heating and lighting demands vary in a similar trend as in the previous setting (Figure 18). However, the cooling demand is much higher than the setting with, which is due to the fact that the inside is not as efficient in cutting down solar radiation as the. 32

33 Setting 6 (with inside and ) With inside and (Figure ), the variations of heating and lighting demands are similar as shown previously but the cooling demand is reduced by the addition of. 33

34 Lighting demand (kwh/m2) Cooling demand (kwh/m2) Heating demand (kwh/m2) Lund University, Energy and Building design Annual Heating demand in Northern House % % % Annual Cooling demand in Northern House % % % Annual Lighting demand in Northern House % % % Figure 15: Heating, cooling and lighting demand in Northern house (no and no shading device). 34

35 Lighting demand (kwh/m2) Cooling demand (kwh/m2) Heating demand (kwh/m2) Lund University, Energy and Building design Annual Heating demand in Northern House ( ) % % % Annual Cooling demand in Northern House ( ) % % % Annual Lighting demand in Northern House ( ) % % % Figure 16: Heating, cooling and lighting demand in Northern house ( and without shading). 35

36 Lighting demand (kwh/m2) Cooling demand (kwh/m2) Heating demand (kwh/m2) Lund University, Energy and Building design Annual Heating demand in Northern House ( shade) % % % Annual Cooling demand in Northern House ( shade) % % % 35 Annual Lighting demand in Northern House ( shade) % % % Figure 17: Window areas and heating, cooling and lighting demand in northern house ( and no ). 36

37 Lighting demand (kwh/m2) Cooling demand (kwh/m2) Heating demand (kwh/m2) Lund University, Energy and Building design Annual Heating demand in Northern House ( & shade) % % % Annual Cooling demand in Northern House ( & shade) % % % Annual Lighting demand in Northern House ( & shade) % % % Figure 18: Heating, cooling and lighting demand in Northern house ( and ). 37

38 Lighting demand (kwh/m2) Cooling demand (kwh/m2) Heating demand (kwh/m2) Lund University, Energy and Building design Annual Heating demand in Northern House (inside shade) % % % Annual Cooling demand in Northern House (inside shade) % % % Annual Lighting demand in Northern House (inside shade) % % % Figure 19: Heating, cooling and lighting demand in Northern house (inside and no ). 38

39 Lighting demand (kwh/m2) Cooling demand (kwh/m2) Heating demand (kwh/m2) Lund University, Energy and Building design Annual Heating demand in Northern House ( & inside shade) % % % Annual Cooling demand in Northern House ( & inside shade) % % % Annual Lighting demand in Northern House ( & inside shade) % % % Figure : Heating, cooling and lighting demand in northern house (inside and ). 39

40 4.1.2 Natural, shading devices and energy performance This section presents a comparison of energy performance between the six environmental settings described previously (Figure 21, Figure 22). For small windows (%-WGR), the South is the best orientation in terms of heating energy demand but generally, there are only small variations between the results of the different orientations, which could be an effect of the fact that the windows are distributed rather evenly on all facades. Thus the South and North orientated houses are in fact almost equivalent in terms of sun exposure. Furthermore, only small differences of heating demand were found for the six environmental settings. The yields the smallest cooling demand. A slightly higher cooling demand is obtained with the two settings ( with and with inside and ). The highest cooling demand occurs with the setting of inside and the setting without and. In addition, note that the lighting energy does not vary significantly with different settings. It is generally increased by about 3 kwh/m 2 yr by the addition of the shading. For large windows (%-WGR), the South orientation yields the lowest heating demand, as expected, compared to the North and West orientations. Figure 22(a) also shows that heating energy is slightly higher with the use of than with other environmental settings. In reality, this should not be the case since the shading device should be removed whenever passive solar gains exceed heat losses through windows. It could be due to the fact that the shading s are down at moments when it would be more beneficial to have them removed and thus, small adjustments in the simulation settings may be required to avoid this effect. Note also that the four environmental settings (without ) yield a similar heating energy demand. On the contrary, the two cases with bring the minimum cooling demand while the setting of no shading device and no give rise to the maximum cooling demand. Interestingly, the setting of and the setting of inside have a similar cooling demand. For electric lighting, as expected, the use of and inside yields a slight increase in energy use but this effect is not significant in absolute terms compared to the effect of the s on the cooling demand.

41 Lighting demand (kwh/m2) Cooling demand (kwh/m2) Heating demand (kwh/m2) Lund University, Energy and Building design Annual Heating demand in Northern House (WGR: %) no shade and no & inside inside & Annual Cooling demand in Northern House (WGR: %) no shade and no & inside inside & Annual Lighting demand in Northern House (WGR: %) no shade and no & inside inside & Figure 21: Annual energy performance between six environmental settings (Northern house, WGR %). 41

42 Lighting demand (kwh/m2) Cooling demand (kwh/m2) Heating demand (kwh/m2) Lund University, Energy and Building design Annual Heating demand in Northern House (WGR: %) no shade and no & inside inside & Annual Cooling demand in Northern House (WGR: %) no shade and no & inside inside & Annual Lighting demand in Northern House (WGR: %) no shade and no & inside inside & Figure 22: Annual energy performance between six environmental settings (Northern house, WGR %). 42

43 4.1.3 Overall energy performance This section presents the comparison of overall energy performance (sum of heating, cooling and lighting energy use) for the six environmental settings described previously in addition to the case without window. For small window size (WGR%) (Figure 23), the maximum overall energy demand is obtained with the setting without shading device and and the setting inside, on all three orientations. The energy demand in these two cases is higher compared to the case with no window. Other environmental settings ( with and without shading device, with and without, with and, with and inside ), yield similar overall energy demand, which is also similar to the case with no windows. Note also that Figure 23 generally shows the dominance of the heating demand in the overall energy balance, especially for small WGR (%). The lighting demand is the second most important energy end-use affecting the overall energy balance. In the case of large windows (%-WGR) (Figure 24), the energy balance is dominated by cooling in two cases; heating is relatively less important (except for the and no window cases). Heating remains an important end-use - and the main energy consumer for four of the environmental settings (no window, s with and without and inside with ). For two of the environmental settings ( or inside ), the heating demand is approximately equivalent to the cooling demand. Figure 24 shows that the case without windows generally yields the minimum overall energy demand while the case of large windows without shading device and yields the highest energy use, as expected. With the occurrence of large windows, the two settings of could be the best choice in terms of overall energy savings. The three settings ( or inside ), nevertheless, have a higher overall energy use compared with the setting of. These results generally show the importance of selecting an appropriate shading strategy, especially when the house has large windows. 43

44 Primary energy consumpation (kwh/m2) Primary energy consumpation (kwh/m2) Primary energy consumpation (kwh/m2) Lund University, Energy and Building design Northern House (WGR: %; Orientation: south) no windows no shade and no & inside inside & Lighting demand Cooling demand heating demand Northern House (WGR: %; Orientation: north) no windows no shade and no & inside inside & Lighting demand Cooling demand heating demand Northern House (WGR: %; Orientation: west) no windows no shade and no & inside inside & Lighting demand Cooling demand heating demand Figure 23: Annual energy demand according to orientation (Northern house, WGR %). 44

45 Primary energy consumpation (kwh/m2) Primary energy consumpation (kwh/m2) Primary energy consumpation (kwh/m2) Lund University, Energy and Building design Northern House (WGR: %; Orientation: south) no windows no shade and no & inside inside & Lighting demand Cooling demand heating demand Northern House (WGR: %; Orientation: north) no windows no shade and no & inside inside & Lighting demand Cooling demand heating demand Northern House (WGR: %; Orientation: west) no windows no shade and no & inside inside & Lighting demand Cooling demand heating demand Figure 24: Annual energy demand according to orientation (Northern house, WGR %). 45

46 4.2. Southern house This section presents the results related to the impact of window area and environmental factors (shading and ) on energy performance in the Southern house Window areas and energy performance This section presents the results related to window area and energy use under the six environmental settings described previously. Setting 1 (without and shading device) For the case without shading device and (Figure 25), the larger the WGR, the smaller the heating demand. The cooling demand increases with an increasing WGR, as could be expected, and the lighting energy demand decreases with increasing WGR. However, note that the reduction in lighting energy savings is not significant beyond %- WGR. On average, 3.3% and 11% less heating is required with %-WGR and %-WGR respectively compared to the case with no window. For cooling, the %-WGR, %-WGR and %-WGR yield a cooling demand of.5, 2. and 13.9 kwh/m 2 yr respectively (average for the three orientations). Therefore, the effect of increasing the WGR beyond % is significant on the cooling demand. However, the results obtained with other environmental settings show that it is possible to control the cooling demand using an appropriate shading solution (exterior) and a strategy. The no window case results in the highest energy use for electric lighting while the %-WGR and %-WGR yield reductions of % and 46% respectively in lighting energy use. The benefits in terms of lighting energy reduction of increasing the WGR beyond % are thus marginal, which is probably due to the fact that at %-WGR, the daylight level already reaches 15 lux at the sensor. Increasing the WGR will only increase the light level beyond 15 lux. The impact of orientation is only significant for the cooling and heating demands and the large WGR (%). In general, the results indicate that the lighting demand is not significantly affected by the orientation under the French climate conditions in this study. This could be an effect of the simulation methodology (one sensor in the middle of the room) and the house design with rather uniform window distribution (thus equivalent solar exposure for the different house orientations). Setting 2 (with and without shading device) With and no shading device (Figure 26), the general varying trends in heating, cooling and lighting demands are similar to those of the previous settings. However, 46

47 the clearly contributes to reduce the absolute cooling demand, which is especially significant for the large WGR (%). This obviously shows that houses with larger windows should be well ventilated to avoid overheating. Setting 3 (with and without ) With and no (Figure 27), similar variations in heating, cooling and lighting demands are obtained. However, the absolute cooling demand is greatly reduced with the compared to the previous settings ( and no shading device). The use of does not significantly affect the energy demand of heating and lighting systems. For lighting, it could be explained by the fact that most lighting use occurs at night when there is no or little daylighting outdoors. Setting 4 (with and ) With and (Figure 28), the cooling demand s absolute value is further reduced, especially in the case of large WGR (%), which shows that it is possible to control overheating and high cooling loads using an efficient shading and strategy. Setting 5 (with inside and without ) With inside and no (Figure 29), heating and lighting demands vary in a similar trend as the setting of. However, the cooling demand is higher than the setting with, especially for the large WGR (%). This is obviously due to the fact that the inside is not as effective in cutting down solar gains as the. Setting 6 (with inside and ) With inside and (Figure ), the variations of heating and lighting demands are similar as in the previous settings except that the cooling demand is reduced by adding. 47

48 Lighting demand (kwh/m2) Cooling demand (kwh/m2) Heating demand (kwh/m2) Lund University, Energy and Building design Annual Heating demand in Southern House % % % Annual Cooling demand in Southern House % % % Annual Lighting demand in Southern House % % % Figure 25: Heating, cooling and lighting demand in Southern house (no and no shading device). 48

49 Lighting demand (kwh/m2) Cooling demand (kwh/m2) Heating demand (kwh/m2) Lund University, Energy and Building design Annual Heating demand in Southern House ( ) % % % Annual Cooling demand in Southern House ( ) % % % Annual Lighting demand in Southern House ( ) % % % Figure 26: Heating, cooling and lighting demand in Southern house ( and no shading). 49

50 Lighting demand (kwh/m2) Cooling demand (kwh/m2) Heating demand (kwh/m2) Lund University, Energy and Building design Annual Heating demand in Southern House ( shade) % % % Annual Cooling demand in Southern House ( shade) % % % Annual Lighting demand in Southern House ( shade) % % % Figure 27: Heating, cooling and lighting demand in southern house ( and no ). 5

51 Lighting demand (kwh/m2) Cooling demand (kwh/m2) Heating demand (kwh/m2) Lund University, Energy and Building design Annual Heating demand in Southern House ( & shade) % % % Annual Cooling demand in Southern House ( & shade) % % % Annual Lighting demand in Southern House ( & shade) % % % Figure 28: Heating, cooling and lighting demand in Southern house ( and ). 51

52 Lighting demand (kwh/m2) Cooling demand (kwh/m2) Heating demand (kwh/m2) Lund University, Energy and Building design Annual Heating demand in Southern House (inside shade) % % % Annual Cooling demand in Southern House (inside shade) % % % Annual Lighting demand in Southern House (inside shade) % % % Figure 29: Heating, cooling and lighting demand in Southern house (inside and no ). 52

53 Lighting demand (kwh/m2) Cooling demand (kwh/m2) Heating demand (kwh/m2) Lund University, Energy and Building design Annual Heating demand in Southern House ( & inside shade) % % % Annual Cooling demand in Southern House ( & inside shade) % % % Annual Lighting demand in Southern House ( & inside shade) % % % Figure : Heating, cooling and lighting demand in Southern house ( and inside ). 53

54 Natural, shading devices and energy performance This section compiles results to allow a comparison of total energy balance between the six environmental settings described previously. For small WGR (%) (Figure 31), the South orientation is the best one in terms of heating demand and West also has a slightly lower heating demand than the North orientation but the absolute difference between these two orientations is small. No significant differences of heating demand are obtained between the six environmental settings for the small WGR. The two settings using result in the minimum cooling demand. A slightly higher cooling demand is obtained with the two settings with and with inside and. The second highest cooling demand occurs with the setting with inside and the highest demand is for the setting without and. Lighting energy use does not vary with the different environmental settings. For large WGR (%) (Figure 32), the South orientation has a lower heating demand compared to the North and West orientations. The brings the lowest heating demand due to the additional insulation layer in the window at night. The cuts down long wave radiative heat losses towards the cold sky and this effect is important especially since the French house has a nearly horizontal roof with roof windows facing the sky. Note, however, that the absolute difference between the six environmental settings is relatively small. Regarding cooling, the setting with also yields the lowest cooling demand while the setting no shading device and no gives rise to the highest cooling demand. Interestingly, the setting of and the setting of inside and result in a similar cooling demand, which is higher than the setting with and lower than the setting without shading device and. These results generally indicate that the is very effective in cutting down cooling, even without (in a house with high infiltration rate). The results also indicate that the different settings have no significant effect on the lighting load. The lighting demand is roughly the same for all six environmental settings. 54

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