ScienceDirect. Simulation based mixed mode building design

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1 Available online at ScienceDirect Energy Procedia 00 (2016) th International Conference on Advances in Energy Research, ICAER 2015, December 2015, Mumbai, India Simulation based mixed mode building design Jay Dhariwal ab *, Rangan Banerjee a a Department of Energy Science and Engineering, IIT Bombay, Mumbai, India b Department of Architecture, Massachusetts Institute of Technology, Cambridge, MA, USA Abstract Air-conditioning represents the major component of energy consumption in commercial buildings in India. To reduce the space cooling load, a methodology is proposed to optimize the building design, using incremental integrate d design approach and experimental design methods. This methodology is applied over a three story building in New Delhi climate. For the building, using incremental integrated design, passive strategies are able to reduce the cooling load by 50% over the base case and low energy cooling techniques are able to reduce the cooling load by 50% over the passive case. Building is then optimized to use natural ventilation to the extent possible, while considering the uncertainty in input parameters, using design of experiments based methods. It is found that during winter months, building can be operated just using natural ventilation during office hours, while maintaining thermal comfort. Natural ventilation is able to reduce the energy consumption by about 15% over the incremental design case. The final achieved mixed mode design consumes 55% less energy, better daylighting, views and uses natural ventilation for 30% more hours as compared to the baseline case The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the organizing committee of ICAER Keywords: building simulation; mixed mode; natural ventilation; integrated design; design of experiments; 1. Introduction Air-conditioning for space cooling is responsible for more than half of the energy consumption in commercial buildings for Indian climates. With the growth in Indian economy, the rise in air-conditioning usage could be worrisome for an energy deficient India. Research has shown that the use of passive design strategies, low energy cooling techniques and natural ventilation can bring down the cooling load significantly. While the energy consumption reduction is important but an integrated design approach is important to improve the general well-being * Corresponding author. Tel.: ; address: jayd@mit.edu The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the organizing committee of ICAER 2015.

2 Jay Dhariwal and Rangan Banerjee/ Energy Procedia 00 (2016) and the productivity of the occupants of these spaces. The integrated design approach involves the consideration of daylighting, views to the outdoors, indoor air quality (IAQ), cost, embodied energy, space use and furniture layout. In this context, a methodology is proposed to optimize the design of a mixed mode building, which switches between air-conditioning and natural ventilation depending on the outdoor conditions. This methodology uses incremental integrated design approach to reduce the cooling load and design of experiments approach to explore the extent of use of natural ventilation. A three story commercial building in New Delhi climate is used as a case study to explain the proposed methodology. The building construction drawings for the base case, occupancy, lighting and equipment schedules and other internal gains data about the building can be found in [1]. Nomenclature discomfort hours DCV demand controlled ventilation ERV energy recovery ventilation SHGC solar heat gain coefficient TOPT indoor operative temperature (in C) VBA visual basic for applications WWR window to wall ratio 2. Methodology Figure 1 shows the methodology followed for optimizing the building design. If any of the parameters are changed at any step, then the methodology needs to be iterated. The first step is to perform climate analysis for the site to find out the climate responsive strategies, which could enhance the thermal and the visual comfort, while reducing the energy use. Using the insights gained from climate analysis and site constraints, space use and furniture layout is planned, taking care of daylighting, views, path for natural ventilation as per wind direction and reduced energy consumption. The base model is then setup and incremental building design is explored to reduce the energy consumption over the base case. Fig. 1. Methodology for optimizing the mixed mode building design. To find out the effectiveness of natural ventilation for the given case, the incremental building design is optimized to minimize the annual discomfort hours, considering natural ventilation only. The achieved optimal building design suggests the times during the year, when natural ventilation would be able to maintain thermal comfort. While

3 Jay Dhariwal and Rangan Banerjee/ Energy Procedia 00 (2016) optimizing the design, the impact of uncertainty in input parameters like wind speed, pressure coefficients, wind direction, etc. also needs to be accounted for. Hence, sensitivity analysis is performed to find out the most effective discomfort hours reducing strategies as well as the influential input parameters with uncertainty. For the combination of these important parameters, the optimal robust design is found. For the remaining hours, air-conditioning is used. 3. Case study: results and discussion 3.1. Climate analysis The climate data is analysed using Climate Consultant software version 6.0 to gain insights into the passive strategies that could be useful. The sun path diagram in Fig. 2 suggests having higher WWR on the north façade and preventing heat gain from the open west façade. The timetable plot in Fig. 3 shows that natural ventilation during daytime may work in winter months, air-conditioning would be required in summer time and night flushing of the thermal mass may work during the transition months. Fig. 4 shows that the predominant wind direction for the site is from north to west. Fig. 2. Sun path diagram for the building. Fig. 3. Timetable plot for temperature on a monthly basis.

4 Jay Dhariwal and Rangan Banerjee/ Energy Procedia 00 (2016) Fig. 4. Wind wheel for the year and month of April Space use and furniture layout As per Fig. 5 and Fig. 6, the occupants along with the corresponding furniture and computers have been evenly distributed on the three floors in the two blocks on either side of the lift shaft and the stair block to divide the cooling load evenly. Open layout has been preferred for giving a spacious feeling to the occupants and making the best use of natural ventilation, views, daylighting, etc. for them. Fig. 5. Top view of the space use for the building.

5 Jay Dhariwal and Rangan Banerjee/ Energy Procedia 00 (2016) Fig. 6. Furniture planning for the open layout Base model Fig. 7 shows the base simulation model created using Designbuilder software, as per ASHRAE 90.1 guidelines [2]. The building is G+2 and has 8.4 m by 8.6 m blocks on each floor on either side of the lift shaft and staircase block. The open layout in each block is 8.4 m by 6 m. The case study building is surrounded by neighbouring buildings on the east and the south side, causing shading from the sun. Fig. 7. Base model of the building Incremental integrated building design Based on the insights from climate analysis, passive design and low energy cooling strategies are tried one at a time to reduce the energy consumption. The strategies are applied over a week in March and July to understand the incremental benefit. As per Fig. 8, strategies from overhangs to curtains are passive design strategies, whereas economizer to DCV are low energy cooling strategies. The figure shows that the use of all the strategies together leads to ~70% reduction in the cooling load for both the March and July weeks. The absolute cooling load reduction from the baseline case to proposed case is 3048 kwh to 925 kwh for the March week and 8828 kwh to 2487 kwh for the July week. It is to be noted that the cooling load increases from the window SHGC strategy to WWR strategy, as WWR is increased for the north facade to enhance views and daylighting. Water filled in recycled PET bottles is

6 Jay Dhariwal and Rangan Banerjee/ Energy Procedia 00 (2016) suggested to be used in place of concrete for additional thermal mass. Fig. 8. Incremental design applied over a week in March and July Naturally ventilated robust building design Integrated incremental design is found to reduce the energy consumption while enhancing or maintaining the views, daylighting and indoor air quality. But incremental design doesn t consider the impact of natural ventilation, which is explored in this section. Fig. 9 outlines the methodology followed to find the robust naturally ventilated design, which minimizes the discomfort hours, while considering the uncertainty in input data. Fig. 10 shows the model for natural ventilation created in EnergyPlus, building simulation software [4]. This model divides the building into three zones, one for each floor. This model considers the lift shaft and stairs block as openings through which airflow can happen. Also, no windows have been provided on the south façade for the left and right blocks due to the presence of rooms, which would obstruct natural ventilation. Fig. 9. Methodology for a robust naturally ventilated building design.

7 Jay Dhariwal and Rangan Banerjee/ Energy Procedia 00 (2016) Based on the insights from the incremental design, Table 1 shows the design variables considered for sensitivity analysis. The uncertainty parameters have been considered for the most relevant microclimate variables, user behaviour, building construction and material properties, as per [3]. Using fractional factorial design method [5], sensitivity analysis is performed for the ground floor zone and second floor zone to find out the significant factors affecting the respective zone operative temperature, out of the 7 design variables and 24 uncertain input parameters considered, as per Table 1 and [3]. The 596 EnergyPlus simulation runs are automated using VBA. Table 2 shows the factors which together explain more than 95% variance for the response, indoor operative temperature. Cast concrete used as the floor material has an impact for the ground floor. Window opening and curtain use behaviour have an impact for both the floors. Among the design variables, roof reflectivity and roof insulation are significant for the top floor of the building. Overhang depth and WWR are important for both the floors. The design variables, which are not significant, are kept at the values in the incremental design case. For further details of the design of experiments based methodology, [3] may be referred. Fig d model for natural ventilation modelling in EnergyPlus. Table 1. Design variables with ranges. Design variable Range WWR for east and west façade (in %) Overhang depth (in m) Roof reflectance Wall insulation thickness (in m) Roof insulation thickness (in m) Wall thermal mass thickness (in m) Roof thermal mass thickness (in m) Table 2. Most significant factors for sensitivity analysis (rank wise). Input factors for ground floor zone Design factors for ground floor zone Input factors for second floor zone Design factors for second floor zone cast concrete t overhang depth window opening factor roof reflectance cast concrete k WWR curtain use roof insulation window opening factor overhang depth curtain use WWR Among the significant design factors, overhang depth and roof reflectivity are kept at their highest allowable values due to their high significance. For discomfort hour minimization, WWR and roof insulation are varied over the significant input parameters, namely, cast concrete thickness (t), cast concrete thermal conductivity (k), window opening factor and curtain use, at two levels each. This creates a total of 64 cases. Table 3 summarizes the results for

8 Jay Dhariwal and Rangan Banerjee/ Energy Procedia 00 (2016) weighted and it can be seen that design with 40% WWR and 0.1 m roof insulation is the best among the options considered. Also, is higher for higher floors. Table 3. Results for designs with discomfort hours for all zones. Option WWR Roof insulation Ground floor mean First floor mean Second floor mean Ground floor 90th percentile First floor 90th percentile Second floor 90th percentile 1 40% % % % Weighted Table 4. Thermal comfort with natural ventilation. Hour of the Day Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1 99% 100% 100% 71% 20% 21% 29% 49% 80% 100% 100% 100% 2 96% 100% 100% 79% 23% 29% 34% 56% 91% 100% 100% 100% 3 95% 100% 100% 87% 29% 31% 44% 63% 98% 100% 100% 100% 4 95% 100% 100% 92% 32% 30% 53% 72% 100% 100% 100% 100% 5 92% 100% 100% 92% 34% 40% 60% 74% 100% 100% 100% 100% 6 91% 100% 100% 92% 32% 37% 58% 81% 100% 100% 99% 99% 7 87% 100% 100% 87% 29% 30% 48% 69% 100% 100% 99% 99% 8 99% 100% 100% 68% 16% 21% 38% 56% 96% 100% 100% 100% 9 100% 100% 100% 36% 10% 17% 27% 37% 62% 100% 100% 100% % 100% 96% 11% 5% 13% 18% 25% 28% 81% 100% 100% % 100% 65% 1% 0% 8% 14% 17% 8% 65% 100% 100% % 98% 39% 0% 0% 4% 10% 14% 1% 43% 88% 100% % 94% 25% 0% 0% 1% 8% 10% 0% 24% 72% 100% 14 99% 89% 17% 0% 0% 1% 4% 13% 0% 13% 62% 100% 15 99% 90% 10% 0% 1% 1% 3% 11% 0% 12% 63% 100% % 92% 10% 0% 2% 1% 3% 10% 1% 14% 79% 100% % 95% 23% 0% 3% 0% 4% 9% 2% 29% 92% 100% % 100% 34% 0% 3% 1% 6% 9% 3% 54% 97% 100% % 100% 58% 1% 3% 2% 9% 12% 8% 67% 99% 100% % 100% 81% 8% 5% 6% 10% 18% 19% 76% 100% 100% % 100% 91% 20% 10% 7% 18% 32% 34% 95% 100% 100% % 100% 96% 30% 13% 10% 22% 37% 49% 100% 100% 95% % 100% 100% 43% 15% 17% 28% 41% 62% 100% 100% 94% % 100% 100% 57% 19% 17% 30% 48% 71% 100% 100% 89% Table 4 shows the analysis of average zone operative temperatures, lying within the adaptive comfort range, for the best design from Table 3 of 40% WWR and 0.1 m roof insulation. In the table, the yellow colour shows the working

9 Jay Dhariwal and Rangan Banerjee/ Energy Procedia 00 (2016) hours, blue colour shows the hours comfortable and red colour shows the hours uncomfortable. For hours comfortable in blue colour, a cut-off of 85% has been assumed. Table 5 shows the time, when the window is open (blue coloured cells) and the indoor operative temperature is in thermal comfort range. These tables show that during December to January, natural ventilation can be used during the working hours to reduce the heating load and the fresh air load. During November, natural ventilation could be helpful for most of the day except the afternoon. During March and October, natural ventilation could be helpful during the mornings only. For the summer time, air-conditioning would be needed. Table 5. Window opening for thermal comfort with natural ventilation. Hour of the Day Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1 6% 21% 91% 71% 20% 21% 29% 49% 80% 77% 14% 0% 2 8% 15% 87% 79% 23% 29% 34% 56% 91% 78% 12% 0% 3 5% 12% 81% 87% 29% 31% 44% 62% 98% 69% 10% 0% 4 3% 11% 78% 92% 32% 30% 53% 72% 100% 62% 7% 0% 5 4% 8% 71% 92% 34% 40% 60% 74% 100% 62% 6% 0% 6 3% 6% 71% 92% 32% 37% 58% 80% 100% 61% 2% 0% 7 0% 8% 76% 87% 29% 30% 48% 68% 100% 59% 3% 0% 8 26% 52% 98% 68% 16% 21% 38% 56% 96% 87% 31% 0% 9 68% 98% 100% 36% 10% 17% 27% 37% 62% 100% 81% 3% 10 88% 100% 96% 11% 5% 13% 18% 25% 28% 81% 100% 49% 11 99% 100% 65% 1% 0% 8% 14% 17% 8% 65% 100% 75% 12 99% 98% 39% 0% 0% 4% 10% 14% 1% 43% 88% 90% 13 99% 94% 25% 0% 0% 1% 8% 10% 0% 24% 72% 95% 14 99% 89% 17% 0% 0% 1% 4% 13% 0% 13% 62% 99% 15 99% 90% 10% 0% 1% 1% 3% 11% 0% 12% 63% 100% % 92% 10% 0% 2% 1% 3% 10% 1% 14% 79% 100% % 95% 23% 0% 3% 0% 4% 9% 2% 29% 92% 95% % 100% 34% 0% 3% 1% 6% 9% 3% 54% 97% 100% 19 99% 100% 58% 1% 3% 2% 9% 12% 8% 67% 99% 75% 20 72% 96% 81% 8% 5% 6% 10% 18% 19% 76% 82% 5% 21 41% 63% 91% 20% 10% 7% 18% 32% 34% 90% 46% 1% 22 15% 31% 96% 30% 13% 10% 22% 37% 49% 83% 19% 0% 23 12% 30% 98% 43% 15% 17% 28% 41% 62% 84% 16% 0% 24 9% 27% 96% 57% 19% 17% 30% 48% 71% 81% 12% 0% 3.6. Mixed mode design Mixed mode building design switches between natural ventilation and mechanical cooling seasonally from winter to summer. Also, during months of March, October and November, it switches on a daily basis as well. Figure 11 shows the CFD analysis using Designbuilder software for open layout of second floor left block for north-westerly wind for 23 rd March at 10 am. It shows that some part of the wind goes directly to the east as the cross ventilation path is open and some part of it turns towards the north and is able to reach all the occupants in the space. From the

10 Jay Dhariwal and Rangan Banerjee/ Energy Procedia 00 (2016) daylighting perspective, the proposed building case passes the LEED credit 8.1 and has 84% of the area well lit, above the requirement of 75%. Fig. 12 shows the daylighting levels of the building, as per analysis using Designbuilder software. The most occupied areas of the open layout are well lit. Fig. 11. CFD analysis vertical view for open layout of second floor left block. Fig. 12. Daylighting views for the building. Fig. 13 shows the steps taken to reduce the energy consumption having an EPI (energy performance index) of 180 kwh/m 2 -year for the base case to 80 kwh/m 2 -year for the mixed mode case. Passive strategies are able to reduce the cooling load by 50% over the base case and low energy cooling techniques are able to reduce the cooling load by 50% over the passive case. Natural ventilation is able to reduce the energy consumption by about 15% over the incremental design case. Fig. 14 compares the final achieved mixed mode design with the base case. This design consumes 55% less energy, has better views to the exterior, better daylighting levels, uses natural ventilation for 30% more hours and consumes lesser embodied energy as compared to the baseline case.

11 Jay Dhariwal and Rangan Banerjee/ Energy Procedia 00 (2016) Fig. 13. Comparison between the different cases for energy performance. Fig. 14. Spider chart comparing the base case with mixed mode case for integrated design. 4. Conclusions A generic framework is proposed to optimize a building design in mixed mode by taking advantage of natural ventilation to the extent possible. This framework is explained using a three story building in New Delhi climate. Climate analysis offers insights into the use of favourable outdoor conditions for comfort to bring the energy costs down. A baseline simulation model is created, which is optimized for reduction in cooling load using an incremental integrated design approach. This design is further improved to use natural ventilation for maintaining comfort. It is found that during winter, building can be operated just using natural ventilation during office hours but during summer, air-conditioning use is necessary for maintaining thermal comfort. The final achieved mixed mode design consumes 55% less energy, has better views to the exterior, better daylighting and uses natural ventilation for 30% more hours as compared to the baseline case. As one of the next steps, design of experiments based methods could be used for optimizing the design for minimizing the cooling load as well. References [1] IBPSA. BS2015 Student competition. 14th International Conference of IBPSA, Hyderabad. Accessed August 16, 2015.

12 Jay Dhariwal and Rangan Banerjee/ Energy Procedia 00 (2016) [2] ASHRAE Standard Energy standard for buildings except low-rise residential buildings. Atlanta: ASHRAE; [3] Dhariwal J, Banerjee R. Naturally ventilated building design under uncertainty using design of experiments. BS2015, 14th International Conference of International Building Performance Simulation Association (IBPSA), Hyderabad; December 7-9, [4] EnergyPlus. EnergyPlus Engineering Reference: The Reference to EnergyPlus Calculations. Accessed August 16, [5] Montgomery DC. Design and Analysis of Experiments. Wiley India Edition, Reprint, New Delhi; 2007.