CONTROL STRATEGIES AND ENERGY SAVING POTENTIALS FOR VARIABLE TRANSMITTANCE WINDOWS VERSUS STATIC WINDOWS

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1 CONTROL STRATEGIES AND ENERGY SAVING POTENTIALS FOR VARIABLE TRANSMITTANCE WINDOWS VERSUS STATIC WINDOWS J. Karlsson, B. Karlsson * and A. Roos Department of Materials Science, The Ångström laboratory, Uppsala University P.O. Box 534, S Uppsala, Sweden Tel: +46-(0) Fax: +46-(0) Joakim.Karlsson@Angstrom.uu.se * Vattenfall Utveckling AB, Älvkarleby Sweden Keywords: variable windows, smart windows, electrochromic windows, control strategies, energy efficiency, solar energy, buildings. Abstract Control strategies and energy saving potentials for windows with variable transmitting properties are briefly reviewed and discussed. A simple window selection tool is used for comparisons of heating and cooling performance of present and future variable windows with state of the art static windows. The comparisons are made for three exceptionally different climates, different directions of the window, for a residential and a commercial building, and for two different settings on a solar controlled variable window. It seems as if the variable windows save a lot of energy compared to uncoated windows but that, in many cases a suitable static window can perform as well or even better than the variable window. However, for cooling dominated climates variable windows outperform the best static ones for basically all types of buildings. Horizontal mountings seem to increase energy efficiency of the variable windows for some of the given circumstances. Limited differences in energy saving between future high performance variable windows versus state of the art static windows imply that comfort arguments may be the prioritised driving force for variable windows. 1. INTRODUCTION Windows are often a critical link in the energy system of a building. Window U-values considerably higher than the surrounding walls or high solar transmittance levels often cause problems related to heating, cooling or comfort aspects of the building. Thin film technologies have improved many features of the windows, such as radically reduced U-values, which is important in heating dominated (cold) climates, and highly reduced solar transmittance levels while maintaining high visual transmittance (T vis ), which is important in cooling dominated (warm and sunny) climates. State of the art technology is approaching its boundaries of zero thermal emittance and a factor of two between visual transmittance and solar transmittance. It is generally believed that the next generation of coatings are coatings with variable properties. A window with variable transmitting properties will enhance the possibilities to achieve improved energy and comfort performance of the window since it can control the extreme variations in solar irradiation of about 0 to 1000 W/m 2. Many locations have highly different seasonal or daily changes in irradiation, where varying windows may be a competitive alternative to static windows, different shading solutions or combinations thereof. As variable transmittance windows are now entering the glazing market, some of the R&D attention is shifting from the materials science to more integration related questions, such as where to use, how to control and what is the energy saving or comfort improving potential? So far, the most versatile path to achieve variable transmittance windows (smart windows) for architectural applications seems to be by use of electrochromic materials. An extensive handbook of inorganic electrochromic materials by Granqvist (1995) summaries the materials development up to the early nineties. Recently, Granqvist (0) also published a review of progress on electrochromic tungsten oxide films. The status of switchable glazing devices is discussed, by Lampert (1998). It is clear that electrochromic devices can optically switch with a high span between the transparent and coloured state in a lab environment and efforts are being made to upscale this technology. Durability and cost issues will be critical for market acceptance. Assuming that the durability and cost of electrochromic windows approach levels comparable to static energy efficient windows, such as low-e and solar control windows, it is still necessary to assess how these windows can outperform static windows when it comes to energy and/or comfort performance. At Lawrence Berkeley Laboratory, several studies have been made on this topic by Selkowitz et al. (1994), Sullivan et al. (1994, 1995, 1996a, 1996b) and Moeck et al. (1998). Investigations by the Berkeley group indicate that the electrochromic glazings needs to be combined with static low-e or solar control coatings and that such a combination can reduce cooling need and improve thermal comfort and glare control. However, the group state that currently available electrochromic prototype devices perform about the same as conventional static low-e or solar control windows (Sullivan et al., 1996a). With available electrochromic devices they refer to absorbing devices with a solar transmittance of 80/10 % (bleach/coloured state) leading to a total solar energy transmittance (g-value) that can vary between 52 and 15 %, if combined with a solar control glazing. Furthermore, they conclude that idealised electrochromic glazings will outperform all conventional glazings. With idealised glazings they refer to devices that change to a more reflective than absorbing state in the dark state, which would yield a total window g-value of 64 to 3 % at the best. When it comes to visual quality the Berkeley researchers

2 show that the electrochromic glazings need a minimum visible transmittance of about 1% in order to achieve privacy, a near glare-free environment and constant interior daylight levels (Moeck et al., 1998). However, glare free environments achieved with very low transmittance values might increase lighting electricity use. A window with such low transmittance levels could eliminate the need for additional shading devices and allowing very large glazed areas without extreme cooling needs. One of the essential questions when applying variable windows is how to control them. When should the window be in its dark state and how can such a control system be implemented to optimise energy and comfort performance? The Berkeley group has investigated several different alternatives such as: solar, daylight, space load and outside temperature control. Solar control means that the window is regulated by incident solar radiation between a low and a high setpoint. Daylight control means that the window is regulated so that the daylight illuminance is kept at a certain level at a reference point in the room. With space control the window is regulated based on the existence of a cooling load the previous hour and by temperature control the window is regulated based on the outside temperature. In a simulation for Blythe, California the Berkeley researchers showed that daylight control of the electrochromic windows turned out to perform the best (Sullivan et al., 1994). The energy efficiency of windows depends on the g-value, T vis and the U-value of the window but also highly on the climate, direction of the window, shading and the type of building. Highly heating dominated climates require windows with low U-value and high g-value and buildings in very hot and sunny climates or buildings with high cooling needs require windows with low g-value. The benefit of varying properties of the g-value and T vis differs from case to case and also depends on which static window that is used for comparison. The purpose of this work is to further assess the energy saving potentials with variable transmittance windows under different conditions. Both existing and fictitious variable windows are compared with existing static windows. Climate, types of building, orientation of the window and, to a very limited extent, control strategy are varied and discussed in order to evaluate if a certain application for variable windows is more preferable from an energy perspective than another. The approach is to use a recently presented simple window selection tool (Karlsson et al., 1999). This model reduces the building into only one or two parameters, not including the window parameters, and takes heating and cooling but not lighting into account. The energy saving potentials of different variable and static windows are compared and discussed for different conditions as assessed by this simple window algorithm. The model may not always give accurate absolute numbers on energy saving potentials but we believe that giving the control strategies and the correct window data of the different alternatives the model can correctly point out the best performing window and an assessment of the saving potential for the given conditions of climate and type of building. 2. PREREQUISITES Maybe the most beneficial feature of a variable window is the comfort improving potentials such as automatic daylight, glare and thermal control. However, in this report we mainly discuss differences in energy performance in terms of heating and cooling need. When assessing the performance of variable windows it is necessary to establish some windows or fenestrations systems (including shading devices) for comparisons. Since energy efficient, static window coating technology is mature and wide spread a suitable comparison should be the idealised best (future) variable window with best available (or future) static window for a set of circumstances. This would give the actual energy saving potentials with the new technology versus state of the art today. Comparing the variable windows with fenestration systems that involves different types of shading is of course also very interesting. Many times shading is considered as a problem since it is expensive and/or difficult to install, select or control (automatically or manually), but may in some cases even outperform both electrochromic or/and static solar control windows. Comparison between variable windows with static windows with shading systems is however left out in this report but is a very interesting subject for future studies. The U-value does not, in principle, need to differ between an electrochromic and a static window since the coatings can be combined to have similar thermal emittance. A question that remains is how to choose the transmittance value for the static window that is used for comparison. First of all, we need to recognize that in a heating dominated climate (for instance Sweden) and in a residential building there is practically no cooling need at all. A suitable window for this situation is a window with as low U-value as possible and a high g-value almost all year around. If considering energy efficiency only, this rules out the necessity for a smart window. The use of a smart window can save energy only for conditions were cooling is required for at least part of the year. If a building has a cooling need, energy can be saved by not letting in high amounts of solar energy through the windows. However, the window needs to transmit visual light in order not to increase the lighting electricity bill. Thus for a building with a high cooling need a suitable window for comparison is a window with a low g-value but still a high visual transmittance. A static state of the art double silver coated window can have a g-value of 34 % and still a high visual transmittance of 67 %. If this g-value is low enough to satisfy the cooling requirements the lighting requirements of the variable window will be higher since, on average, it has a lower T vis. For a building with a severe cooling need, a window with an even lower g-value and a reduced visual transmittance is probably the best reference. In such a case, the variable window can reduce the lighting energy need compared to the static window since it can increase visual transmittance during hours with low radiation levels outside. The advantage with smart windows in buildings with high cooling need is that very low transmittance levels can be achieved during sunny periods and thus reduced maximum cooling power and annual cooling energy requirements. 3. SOME THOUGHTS ON CONTROL STRATEGIES How to control the smart window to optimise the energy and comfort performance? The variability adds a complexity to the systems since it needs to be controlled

3 automatically (and manually) for optimising energy and comfort efficiency. In the first four rows in table 1 we supply some of our personal comments on the proposed strategies by the Berkeley group (as discussed in the introduction). If one of the strategies should be selected, we support, without proving it, strategies 2 and 4 in the table, which we base on the fact that the smart window can vary its solar and visual throughput and should therefore be controlled by these parameters. However, mixing of different strategies could be preferable in order to optimise performance. Strategy Type Personal comments 1 Temperature Not very comfortable since temperatures can be very high when it is cloudy, the window should not be dark when it is dark outside and vice versa. 2 Solar Good from both an energy and comfort point of view. The window darkens when there is a certain amount of radiation impinging on the window. 3 Space load Suffer from the same problem as strategy 1, the window goes dark if it is very hot outside but dark 4 Daylighting Same as 2 but optimised for lighting and comfort. 6 Mixing strategies Strategy 3 with 4 or other combinations? Table 1: Control strategies and some personal comments. In this report we mainly test strategy 2 under different conditions. The window selection tool that is used does not consider lighting energy (Karlsson et al., 1999). However, we believe that strategy 2 combines energy efficiency, lighting and improved comfort reasonably well since the window will darken when the pane is illuminated above a certain level. We use a linear regulator as in figure 1, where g max and g min are the g-values of the smart window in transparent and dark state respectively. I gmin and I gmax are the setpoints of the regulator, i.e. when the window darkens or lightens, respectively. Control strategy 2 only trigger on the sunlight on the window surface, which means that the switching depends on the location, shading situation and direction of the window. However, optimal settings of I gmin and I gmax also depend on type of building and glazing data (g max and g min ). By regulating with I gmin and I gmax the smart window can be adjusted for different needs. Figures 2 and 3 illustrate the number of hours that the window is in the dark and regulated state (see figure 1 for definitions) for two different settings of I gmin and I gmax. Setting A have settings I gmin = 50 W/m 2 and I gmax = 300 W/m 2 and setting B have the settings and 400 W/m 2 (table 2). Setting A might be preferable in warm and sunny climates or buildings with high cooling needs and setting B might be better to use in somewhat colder climates or in buildings with less cooling need. In figure two it is seen that for setting A, a southfacing window will be in its dark state for about 1000, 1900 and 1300 hours per year for Stockholm, Denver and Miami, respectively and for a north facing window it will almost never be in its dark state. It may be questionable if it is acceptable by the occupants that the window is in its dark state for more than a third of the daytime during the whole year, as for a south facing window in Denver. For setting B the south-facing window will be in its dark state for about 700, 1300 and 800 hours per year respectively, which might seem a bit more comfortable for the occupants. Too many hours in the dark state with strategy 2 might put control strategy 4 in a more interesting perspective. Control settings I gmin I gmax A B 400 Table 2: Different control settings tested for strategy 2. g (%) g max Transparent state Regulated state Dark state g min I gmin I gmax I g (W/m 2 ) Figure 1: Linear regulator for controlling solar throughput with strategy 2. I g is total radiation impinging on the window surface and g is the total solar energy transmittance. g max and g min is transmittance at the transparent and dark state respectively and I gmin and I gmax are the regulating setpoints.

4 N E S W 0 dark reg dark reg dark reg Stockholm Denver Miami Figure 2: Number of hours in the dark and the regulated (reg) state for Setting A ( W/m 2 ), at the three different locations and for different window directions N E S W 0 dark reg dark reg dark reg Stockholm Denver Miami Figure 3: Number of hours in the dark and the regulated state for Setting B ( 400 W/m 2 ), at the three different locations and at different window directions. 4. ASSESSMENTS Three different locations where chosen for the simulations: Stockholm (Sweden), Denver (USA) and Miami (USA), all having highly different annual average temperatures and solar radiations as described in table 3. A test set of windows was created containing one uncoated, one low-e, four solar control and four smart windows as described in table 4. Smart 1 and 2 are data from currently available smart windows and SmartFict 1 and 2 are variable windows that may be available in the future. Location Annual average temperature ( C) Annual average solar radiation (kwh/m 2 yr, horizontal surface) Stockholm (TRY) Low (6.9) Low (920) Denver (TMY2) Low (9.9) High (1700) Miami (TMY2) High (24) High (1800) Table 3: The three locations chosen for the simulations and their annual average temperature and solar radiation.

5 Identity (Gas fill) Type g (%) U (W/m 2 K) Category Panes T vis (%) 2k Clear Low-e Solar control Solar control Solar control Solar control Smart 44/ /15 Smart 36/ /15 Smart 44/ /0 Smart 56/ /0 Table 4:Test set of static and variable windows. All the static windows are commercially available, however data for the last solar control alternative was simulated, to get a static alternative with low g and reasonably high T vis (double silver layer on grey glass). Smart 1 and 2 are data from recently released smart windows (E-Control by Pilkington Flabeg GmbH) and SmartFict 1 and 2 are data for idealised smart windows that might be available in the future. The Category account for proper angle dependence according to Karlsson and Roos (1999). Figures 4-6 illustrate the results (heating + cooling) for the three different locations for a residential building with a balance temperature of 15 C. In the Stockholm and Denver climates the smart windows performed best using setting B, but still the low-e alternative performed better. Thus in the heating dominated climates of Stockholm and Denver the low-e alternative outperforms the variable windows when it comes to heating and cooling, which means that the comfort improvement (glare control etc.) with the smart window is achieved at a price of reduced energy performance. For the Miami climate however, setting B performs better than A and even the existing smart window (Smart 2) outperform the best solar control window. The fictitious smart window alternatives clearly outperform all the other alternatives, except for North-facing windows. Note that the heating and cooling plant efficiency are both set to unity in all simulations and all results are given in saved kwh per square meter glazed area and year compared to an uncoated double glazed unit. Strategy 2, Setting B Figure 4:Total (heating plus cooling) saved energy versus the direction of the windows for the different window alternatives compared to an uncoated double glazed window in a residential building with T b = 15 C in Stockholm. Solar control strategy (strategy 2) are used with setpoints to 400 W/m 2 (setting B).

6 Strategy 2, Setting B Figure 5: Total (heating plus cooling) saved energy versus the direction of the windows for the different window alternatives compared to an uncoated double glazed window in a residential building with T b = 15 C in Denver. Strategy: 2, setting: B Strategy 2, Setting A Figure 6: Total (heating plus cooling) saved energy versus the direction of the windows for the different window alternatives compared to an uncoated double glazed window in a residential building with T b = 15 C in Miami. Strategy: 2, setting: A. Figures 7 and 8 illustrate the same comparison as above but for commercial buildings with a high cooling need and a balance temperature of 0 C for Stockholm and Denver. For these buildings the smart windows outperform the static windows. The simulations indicated that the more cooling need the more beneficial were the smart windows. The Miami climate is considerably different to the other two and so are the types of buildings that are used in each climate. It is probably not very common to find buildings with very low balance temperatures in Miami since insulation levels are lower. However, also in this climate the benefits of variable windows increase with cooling need as seen in figure 9 where simulation is performed for a balance temperature of 10 C in Miami. For horizontally (roof) mounted windows with the same conditions as below, the smart windows provided higher cooling savings, compared to the static ones. In Stockholm, for instance the savings increased to about 50 kwh/m2yr (at 1100 hours in the dark state) as opposed to about 20 kwh/m2yr for the south-facing window when compared with the best static solar control window. For the Denver and Miami climate, however, these settings and the horizontal mounting lead to the fact that the windows were for a very long time in the dark state (2300 and 2500 hours, respectively), which would increase the lighting energy.

7 Strategy 2, Setting A Figure 7: Total saved energy for the different window alternatives compared to an uncoated double glazed window in a commercial building with T b = 0 C in Stockholm. Strategy: 2, setting: A. 500 Strategy 2, Setting A Figure 8: Total saved energy for the different window alternatives compared to an uncoated double glazed window in a commercial building with T b = 0 C in Denver. Strategy: 2, setting: A.

8 Strategy 2, Setting A Figure 9: Total saved energy for the different window alternatives compared to an uncoated double glazed window in a commercial building with T b = 10 C in Miami. Strategy: 2, setting A. 6. DISCUSSION 5. CONCLUSIONS From a pure energy perspective and with the given control strategies, the following conclusions are drawn: The energy saving potential of variable windows depends on which static windows that are used for comparison, climate, direction, shading, type of building, control strategy and comfort demands. In all cases the static windows outperformed the electrochromic ones for northerly directions (on the Nordic hemisphere) For residential buildings in heating dominated climates it seems as if static windows are more energy efficient than variable windows. For commercial buildings with cooling need in heating dominated climates the future smart windows seem to outperform static solar control windows. Presently available smart windows perform about as well as the best static ones, but could improve comfort performance. In hot and sunny climates the presently available and the future smart windows outperform the static windows for both commercial and residential types of buildings (except for northerly directed windows). The higher the cooling need is, the more beneficial the smart windows perform. Solar control strategy seems like a feasible approach to achieve well performing variable windows both for energy efficiency and comfort. From an energy point of view, low setpoints perform better in buildings with high cooling requirements and high setpoints perform better in buildings with lower cooling requirements. In this paper we have scratched the surface of a very complex problem: to assess the energy saving potentials of windows with variable properties. The diversity in conditions implies that several studies similar to what is done here and by our Berkeley colleagues (Selkowitz et al., 1994, Sullivan et al., 1994, 1995, 1996a, 1996b, and Moeck et al., 1998) need to be carried out in order to see the advantages with this new technology. It seems that the smart windows will compete with high performance static solar control windows with low g-value and high T vis. Considering the small differences in energy performance between high performance smart windows and high performance static windows and the very interesting comfort potentials of variable windows it might be interesting to further assess advantages of the latter. Such advantages could be glare free and thermally comfortable environment, and possible large areas of glazing without the need for additional shading devices. Using comfort arguments, control strategy 4 seems like an interesting alternative, which is also shown by the Berkeley group (Sullivan et al., 1996b). Mixing different control strategies might be optimal, but the control system needs to be reasonably simple and cost effective. However limited energy saving potentials in this particular study, the smart window may well have a natural place in a future smart building where lighting, ventilation and solar throughput is automatically controlled for pleasant indoor environment, and a low energy bill. The model applied in this paper should be seen as a pre feasibility tool for other more advanced and in depth studies. The applied model is in the process of being validated with a detailed dynamic building simulation program (see for instance: Lomas et al., 1997).

9 7. ACKNOWLEDGEMENTS Prof. Claes-Göran Granqvist is acknowledged for supplying constructive comments and help. This work is supported by the Swedish Foundation for Strategic Research through the graduate school Energy Systems. 8. REFERENCES Granqvist C.G. (1995). Handbook of inorganic electrochromic materials. Elsevier, Amsterdam. Granqvist C.G. (0). Electrochromic tungsten oxide films: Review of progress Solar Energy Materials & Solar Cells, 60, Karlsson J. and Roos A. (1999). Modelling the angular behaviour of the total solar energy transmittance of windows. In press. Solar Energy. Karlsson J., Karlsson B. and Roos A. A simple model for assessing the energy performance of windows. Submitted, Energy and Buildings Lampert C.M. (1998). Smart switchable glazing for solar energy and daylight control, Solar Energy Materials and Solar Cells, 52, Lomas K. J., Eppel H., Martin C. J. and Bloomfield D. P. (1997). Empirical validation of building energy simulation programs. Energy and Buildings, 26, Moeck M., Lee E.S., Rubin M., Sullivan R. and Selkowitz S. (1998), Visual quality assessment of electrochromic and conventional glazings. Solar Energy Materials and Solar cells, 54, Selkowitz S., Rubin M., Lee E.S. and Sullivan R., (1994), A review of electrochromic window performance factors. SPIE, 2255, Sullivan R., Lee E.S., Papamichael K., Rubin M.and Selkowitz S. (1994). Effect of switching control strategies on the energy performance of electrochromic windows. SPIE, 2255, Sullivan R., Rubin M. and Selkowitz S. (1995). Reducing residential cooling requirements through the use of electrochromic windows. Thermal Performance of the Exterior Envelopes of Buildings VI Conference, Clearwater Beach, USA. LBNL-report NR: LBNL Sullivan R., Lee E.S., Rubin M. and Selkowitz S. (1996a). The energy performance of electrochromic windows in heatingdominated geographic locations. LBNL-report NR: LBNL Sullivan R., Rubin M. and Selkowitz S. (1996b). Energy performance analysis of prototype electrochromic windows. ASHRAE, Boston, USA, LBNL-report NR: LBNL