Whole Building Simulation Report Efficient Bank of India, Hyderabad
| Yashima Jain
11/15/18
Integrated Design Lab
Whole Building Simulation Report | Yashima Jain
Table of Contents Executive Summary ................................................................................................................................ 3 Introduction............................................................................................................................................. 4 Climate Analysis .................................................................................................................................... 5 1.
Monthly Temperature and Relative Humidity ...................................................................................................... 5
2.
Comfort hour analysis ............................................................................................................................................... 6
3.
Solar radiation distribution...................................................................................................................................... 7
4.
Wind analysis............................................................................................................................................................. 8
5.
Potential passive strategies ..................................................................................................................................... 8 5.1
Orientation ........................................................................................................................................................ 8
5.2
Shading .............................................................................................................................................................. 8
5.3
Cool roofs .......................................................................................................................................................... 9
5.4
Natural Ventilation and fan assisted ventilation........................................................................................ 9
Daylight Compliance Summary .............................................................................................................. 9 1.
ECBC Daylight compliance and results for the AS-IS Case ............................................................................... 9
2.
Proposed shading and window design measures ............................................................................................ 10
3.
2.1
Southern Faรงade............................................................................................................................................ 10
2.2
Eastern and Western faรงade...................................................................................................................... 10
Daylight results for the proposed case .............................................................................................................. 11
AS-IS baseline case ............................................................................................................................... 12 Elimination Parametric .......................................................................................................................... 14 1.
Impact on cooling load .......................................................................................................................................... 14
2.
Impact on EPI and energy cost savings .............................................................................................................. 15
Energy Conservation Measures ............................................................................................................ 16 1.
Orientation ............................................................................................................................................................... 16
2.
Building Envelope ................................................................................................................................................... 16 2.1
Wall ................................................................................................................................................................. 16
2.2
Roof .................................................................................................................................................................. 17
2.3
Window ........................................................................................................................................................... 17
2.4
Electrical Lighting ........................................................................................................................................... 18
2.5
Lighting control measures: Occupancy Sensors........................................................................................ 19
2.6
Daylighting controls ...................................................................................................................................... 19
2.7
Thermostat control based on adaptive comfort ...................................................................................... 20
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Whole Building Simulation Report | Yashima Jain
2.8
HVAC system alternatives ........................................................................................................................... 20
ECM Bundle .......................................................................................................................................... 22 Modelling for ECBC Compliance ........................................................................................................... 23 Appendix .............................................................................................................................................. 25 1.
Appendix A: Results of elimination parametric ................................................................................................ 25
2.
Appendix B: Output summary for ECMs ............................................................................................................ 25
List of figures Figure 1 Graph representing max / min monthly temperature and average relative humidity ....................... 6 Figure 2 Graph representing the IMAC bands for AC and MM Buildings with daily average DBT ................. 7 Figure 3 Solar radiation (direct + diffused) distribution over the sky dome ......................................................... 8 Figure 4 Wind rose diagrams for the three seasons................................................................................................... 8 Figure 5 Useful Daylight Illuminance (UDI) plan for base case from LightStanza................................................. 9 Figure 6 Plan representing ASE for base case of left and sDA on right.............................................................. 10 Figure 7 Shading mask for South facade................................................................................................................... 10 Figure 8 Shading mask for East facade ..................................................................................................................... 10 Figure 9 Section and plan for the shading device and the horizontal and vertical angles used ................... 10 Figure 10 Section and plan for the shading device and the horizontal and vertical angles used ................. 10 Figure 11 ASE and sDA simulation results for the proposed case ......................................................................... 11 Figure 12 UDI results as per simulation for the proposed case ............................................................................. 11 Figure 13 End-use annual energy consumption ......................................................................................................... 13 Figure 14 Monthly end use energy consumption for AS-IS case............................................................................ 13 Figure 15 Comparison of elimination parameters for annual cooling energy.................................................... 15 Figure 16 Percentage reduction in EPI and energy cost savings ........................................................................... 15 Figure 17 Percentage change in net incremental cost and energy savings for wall ......................................... 16 Figure 18 Percentage change in net incremental cost and energy savings for roof ......................................... 17 Figure 19 Comparison of SHGC cases with and without shading devices .......................................................... 18 Figure 20 Comparison of load reduction for LPD ..................................................................................................... 18 Figure 21 Comparison of light load reduction and total load reduction ............................................................. 19 Figure 22 Comparison of net incremental cost and energy savings ..................................................................... 21 Figure 23 Energy consumption comparison for AS-IS and proposed case .......................................................... 22 Figure 24 Energy use breakdown due to energy conservation measures ........................................................... 22
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Whole Building Simulation Report | Yashima Jain
Executive Summary This report documents the workflow to achieve an energy efficient building. For this purpose, Efficient Bank of India (EBI) which is a bank building was chosen as to be the case project. The project is located in Hyderabad covering an area of 1568 m2 with 75% of the area being conditioned. The process includes climate analysis to assess the potential of various passive strategies, daylighting and shading analysis to analyze the daylight performance of the building and check for compliance with ECBC 2017. Strategies like natural ventilation, cool roofs, fan-assisted ventilation, evaporative cooling, and optimizing for orientation were proposed. The climate analysis was done using ClimateConsultant and Honeybee which is a plugin in Rhino + Grasshopper which uses EnergyPlus as its simulation engine. The daylighting simulations were performed in LightStanza which uses Radiance as a simulation engine. The Useful Daylight Index (UDI) was calculated to be 47.5% which makes it an ECBC complaint building. For energy performance, an AS-IS case was prepared with input parameters relating to standard construction typologies in India. The schedules were prepared based on the functioning of an Indian bank. All energybased simulation was done in eQuest which uses DOE-2 as its simulation engine. To begin with the energy analysis and optimization, an elimination parametric was performed which looked at elimination of various building components, internal loads and systems. This was done to understand the effect of each component individually. The results showed that maximum energy savings can be achieved by optimizing the roof assemble and minimizing radiation gains through windows. The next step was to propose energy conservation measure to increase the performance of the building. This was done by performing sensitivity analysis for each building component, like walls, roof, windows and shading, internal loads like lighting, and HVAC systems. Based on the energy savings and net incremental costs appropriate energy conservation measures were selected for the proposed case. The proposed case has an energy performance index (EPI) of 62kWh/m2 with 71 unmet hours. Energy conservation measures like change in orientation, optimizing building envelope, shading of windows, reducing internal loads like lighting, thermostat setpoint controls based on adaptive comfort and efficient HVAC system were used. The u-value for building components was calculate using CARSE tool. The thermostat setpoint controls were calculated based on the Indian Model for Adaptive Comfort (IMAC). An air cooled VRF system with a COP of 4.02 was used to cool the conditioned spaces. Electrical lighting was optimized by using Super ECBC input values. The net incremental cost of the project is INR 45L with a payback period of 4.8years.
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Whole Building Simulation Report | Yashima Jain
Introduction The Efficient Bank of India in Hyderabad is a four-story structure measuring an area of 1568m2. It consists of spaces such as the open office, private office, banking areas, conference room, lobby, library, lecture rooms, dining and pantry. All the spaces in building are air-conditioned except the Circulation core and the restrooms. Table 1 provides details of the building.
Table 1 Building details
Building Details Type Location Building area No. of floors Floor to floor height Clear height Conditioned Area Window Design No. of occupants HVAC Zone Concept Utility Climate Climatic Zone Latitude Longitude Summer months Monsoon months Winter months Building Schedule Working days Working hours
Commercial - Bank Hyderabad 1568 m2 G+3 3040 mm 2890 mm 1193 m2 Vision windows 99 fixed and 280 floating Perimeter/Core on all floors BSES Rajdhani Power Limited
Composite 17.3850° N 78.4867° E February – June July - October November, December and January
Monday - Friday 8am – 6pm
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Climate Analysis 1. Monthly Temperature and Relative Humidity According to
Temperature (deg. C)
Winter
Summer
Monsoon
Winter
45
100
40
90
35
80 70
30
60
25
50 20
40
15
30
10
20
5
10
0
0
Relative Humidity (%)
•
Months
Average Monthly Relative Humidity
• • • • •
Maximum montlhy temperature
Minimum monthly temperature
Figure 1, maximum temperature for all the months is above 30ºC. During the month of April, May and June, the temperature goes above 40ºC hence air-conditioning would be required. The monsoon months have maximum temperature below 35ºC, but relative humidity is above 80%. Hence, dehumidification would be required. The temperature is in the comfort range of 23ºC - 26ºC as per the IMAC adaptive model for the winter months (November, December and January). Winter months can be made comfortable with natural ventilation as a passive strategy. Fan assisted ventilation can be used a passive strategy during the monsoon months due to high relative humidity with a comfortable temperature range. Heating is not required for this climate. Table 2 gives monthly temperature ranges for naturally ventilated mode, mixed-mode and airconditioned mode calculated as per the Indian Model for Adaptive Comfort (IMAC).
Table 2 Temperature range as per IMAC (NV: Naturally-ventilated; MM: Mixed Mode; AC: Air-Conditioned) Mode
Jan
Feb
Mar
April
May
June
July
Aug
Sep
Oct
Nov
Dec
MM (ºC)
20-26
20-28
21-28
22-29
23-30
23-29
26-31
22-28
22-28
21-28
21-28
20-27
AC (ºC)
23-26
24-27
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Whole Building Simulation Report | Yashima Jain
Summer
Monsoon
Winter
45
100
40
90
35
80 70
30
60
25
50 20
40
15
30
10
20
5
10
0
0
Relative Humidity (%)
Temperature (deg. C)
Winter
Months
Average Monthly Relative Humidity
Maximum montlhy temperature
Minimum monthly temperature
Figure 1 Graph representing maximum and minimum monthly temperature and average relative humidity
2. Comfort hour analysis • • • •
Figure 2 represents the adaptive comfort range for Hyderabad for naturally ventilated mode, mixed mode and air-conditioned mode with the average daily temperature. This graph represents data for occupied hours throughout the year. During the summer season (February – June), only 3% - 9% hours are comfortable of the total occupied hours. Hence, air-conditioning would be required during this period. During the monsoon period (July – October), 60% - 75% hours are comfortable for a mixed-mode operation. Due to high humidity levels, fan-assisted ventilation can be used a strategy to achieve maximum comfort. During the winter months (November, December and January), 45% - 67% hours are comfortable if the building is operated in natural ventilation mode.
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Whole Building Simulation Report | Yashima Jain
45
40
35
30
25
20
15
10
Winter
Jan
Summer
Feb
March
April
Monsoon
May
June
July
Aug
Sep
Winter
Oct
Nov
Dec
Figure 2 Graph representing the IMAC bands for AC and MM Buildings with daily average DBT
3. Solar radiation distribution • • • • •
Figure 3 illustrates the solar radiation distribution over the sky dome. The intensity of solar radiation is high from 9am – 3pm during the summer months (March – June). As it is very cloudy, solar radiation intensity is very low during the month of monsoon, a maximum of 22-25 kWh/m2, whereas in summer it goes up to 40 kWh/m2 while in winters it is 50 kWh/m2. Based on the solar radiation intensity and ambient temperature, solar shading will be required from • 9am to 4pm – March to October on southern, eastern and western facades. • 9am – 10am – November to February on the Southern facade Due to low intensity on the southern side as compared to east and west, a longer orientation of the building facing North-South would be preferred.
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Whole Building Simulation Report | Yashima Jain
Monsoon
Summer
Winter
Figure 3 Solar radiation (direct + diffused) distribution over the sky dome
4. Wind analysis •
During the summer months, wind from the western side should be avoided due to average temperatures ranging between 35ºC - 41ºC. West winds can be captured and used for natural ventilation during the monsoon period. The temperature ranges between 25ºC - 33ºC. During the NE monsoons, wind speeds are comparatively lower as compared to summer and monsoon. Natural ventilation on the NE-E-SE side can be used as a passive strategy during these months.
• •
Summer
Monsoon
Winter
Figure 4 Wind rose diagrams for the three seasons
5. Potential passive strategies 5.1
Orientation • Long facades of buildings oriented towards North— South are preferred. • Depending on the windward and leeward side, fenestration could be designed to integrate natural ventilation.
5.2
Shading • Shading devices can be added on the southern, eastern and western facades. • This would help in cutting down the direct sun exposure as well as help reduce the heat gain of the building.
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• Horizontal louvers can be designed for southern façade, whereas light shelves and vertical louvers can be helpful for eastern and western façade.
5.3
Cool roofs • Cool roofs can be used as a passive design technique to maintain a temperature differential of 6ºC - 8ºC between ambient and indoor air temperature. • This strategy can be helpful throughout the year to improve indoor thermal comfort and decrease roof operating temperature.
5.4
Natural Ventilation and fan assisted ventilation • •
As seen in Figure 2, natural ventilation can be used during the winter months since 45% - 67% hours are comfortable. During the monsoon months, fan-assisted ventilation can be effective to cater the high humidity levels. It can be also used during winter months where temperatures exceed the upper limit of the mixed-mode operation.
Daylight Compliance Summary 1. ECBC Daylight compliance and results for the AS-IS Case • • • •
As per ECBC 2017, above grade floor areas shall meet or exceed the useful daylight illuminance (UDI) area requirements by 40% for 90% of the potential daylit time in a year. This value is taken for ECBC compliance with “business” as the building category. The measurements are taken at a work plane height of 0.8m above the finished floor level. The simulation has been run for 8 hours, i.e. 0900hours to 1700hours. Grid size of 600mm x 600mm has been used for simulation results. As per simulations, the UDI for the base case for the building is 40.8% which is compliant with ECBC. For the As-Is Case, reflectance values mention in the table on the right have been taken.
Figure 5 Useful Daylight Illuminance (UDI) plan for base case from LightStanza
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•
For the base case, ASE1000,250 is 14.52% and sDA300,50% is 52.30%.
Figure 6 Plan representing ASE for base case of left and sDA on right
2. Proposed shading and window design measures • •
2.1
Solar shading mask for Hyderabad (17ºN) was used to design shading devices for southern, eastern and western façade. This helped in decreasing the annual sun exposure (ASE) and optimizing Spatial Daylight Autonomy (sDA) for the perimeter rooms. For the proposed shading, the north has been changed to 90º.
Southern Façade •
For the southern façade, 2 horizontal shading devices of 690mm each have been designed for the proposed case.
Figure 8 Section and plan for the shading device and the horizontal and vertical angles used
2.2
Figure 7 Shading mask for South facade
Eastern and Western façade •
For the eastern and western façades, a combination of clerestory and vision windows has been used for the proposed case. The window height has been increased to 1800mm. 600mm on the top acts as a clerestory window and 3 horizontal shelves of 600mm each on the outside have been used to optimize ASE.
Figure 10 Section and plan for the shading device and the horizontal and vertical angles used
Figure 9 Shading mask for East facade
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3. Daylight results for the proposed case For the proposed case, strategies like changing the orientation and adding shading devices on the south, east and west façade have been used to optimize the Annual Sun Exposure (ASE) and Daylight Autonomy (sDA) of the first and the second floor.
Figure 11 ASE and sDA simulation results for the proposed case
Shading devices and changing the orientation for longer axis to face north-south of the building has helped reduced the ASE. As per simulations, the ASE achieved for the proposed case is 0%. This means there is no direct sun exposure (illuminance level > 1000lux) on the first and second floor for more than 250 hours throughout the year. As per LEED v4, ASE1000, 250 should not exceed 10%.
Figure 12 UDI results as per simulation for the proposed case
• •
The sDA for the proposed case is 68.36%. This means that 68% of analysis points receive more than 300lux for 50% time of the year. As per LEED v4, a minimum sDA300, 50% of 55% should be achieved. The Useful Daylight Illuminance of the proposed case has also increased to 47.5% by changing orientation and reflectance values of various materials. Hence, the first and second floor of the proposed model are ECBC compliant.
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Whole Building Simulation Report | Yashima Jain
AS-IS baseline case The inputs for the AS-IS case model were derived from the drawings provided by the architect. For the building fabric, input data was taken for standard constructions assemblies used in India. The schedules were formulated as per operation of a bank. The occupancy for each space was calculated by referring to the furniture layouts provided, and the floating population was calculated by using percentage of time on hourly basis for each space. Lighting power density (LPD) was taken from ECBC 2017 for an ECBC Compliant building. Equipment for each space were listed down and equipment power density (EPD) was calculated for 3-star rated appliance. A split AC system was used for the AS-IS Case with specifications taken from ECBC 2017. Table 3 List of data inputs for AS-IS case
Parameters
Units
Input data
Area
m2
1568
Floor to floor height
m
3.04
Building details
Window to wall area ratio
%
18
Electricity rate
INR/month
8.9
Electricity demand rate
INR/kWh
60
Building schedules
-
Prepared as per functioning of a bank for each space
Occupant density
person/m2
NBC
Lighting power density
W/m2
ECBC 2017 for ECBC compliant building
Equipment power density
W/m2
Space-wise calculation as per 3-star rated appliances
Wall u-value
W/m2.K
2.28
Roof u-value
W/m2.K
3.59
Envelope
Window shgc
-
0.79
W/m2.K
7.10
-
0.50
System type
-
Split AC system
System COP
-
3.3
Fan operation
-
Constant supply
Window u-value Glass vlt HVAC system
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Whole Building Simulation Report | Yashima Jain
The input data mentioned in Table 3 was used for the simulation model. Loads for space cooling, lighting, equipment and fans were analyzed to arrive at the results mentioned in Table 4. Table 4 AS-IS Case results Space cooling Lighting Equipment Fans EPI Unmet hours Total energy consumption Total energy cost Annual electric peak Annual cooling peak
Equipment, 14%
86 kWh/m2 22 kWh/m2 18 kWh/m2 4 kWh/m2 129 kWh/m2 Zero 2,01,758 kWh â‚š 18,16,875 101 kW 252 kW
Fans, 3%
Lighting, 17% Space cooling, 67%
Figure 13 End-use annual energy consumption
The building energy performance index (EPI) for the AS-IS case is 129 kWh/m2 with zero unmet hours. In Error! Reference source not found., maximum energy is consumed by space cooling (67%) which is a split A C system in this case. It is followed by lighting (17%), equipment (14%) and fans (3%). Figure 14 represents the distribution of end use energy consumption monthly. Maximum energy is consumed during the month of May followed by April and June. Cooling energy is also required during the winter months. This can be optimized by reducing internal loads like lighting and equipment in the building.
ENERGY CONSUMPTION (kWh)
25000
20000
15000
10000
5000
0 Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
MONTHS Space cooling
Lighting
Equipment
Fans
Figure 14 Monthly end use energy consumption for AS-IS case
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Elimination Parametric Each building component in the AS-IS baseline case was eliminated to see the impact on total energy consumption. This helped in moving forward with the sensitivity analysis and help understand which energy conservation measure (ECM) will have more impact on the reduction in the total load on the building. The various parameters used in elimination are as below. 1. 2. 3. 4. 5. 6. 7. 8. 9.
Wall Insulation: To neutralize the heat gains from wall surface and its impact on the cooling load and energy use of the building Roof Insulation: To neutralize the heat gains through the roof surface Window SHGC: To neutralize the impact of radiative heat gains through windows Window U-Value: To neutralize the impact of conductive heat gains through windows Lighting: To neutralize the impact of sensible heat gains from all electrical lighting Equipment: Zero equipment power density, to check the impact of heat gains from various equipment in the building People Heat Gains: To neutralize the sensible and latent heat gains from the occupants of the building Ventilation Air: To check the impact on cooling load due to outside air requirement Zero-Cooling-Heating: To check the impact on the energy use of building without having any space conditioning systems.
The variation in the total energy use and cooling load will help determine the best strategies for energy conservation measures. As per the elimination parametric results, heat gain from roof, radiation gain through windows, lighting and optimization of HVAC systems can help reduce the overall energy use in the building. The results from this elimination parametric are shown in Table 5. Table 5 Results of elimination parametric
Cases AS-IS case EP1 - Wall heat gain EP2 - Roof heat gain EP3 - Window radiation gain EP4 - Window conduction gain EP5 - Lighting gain EP6 - Equipment gain EP7 - People gain EP8 - Ventilation air EP9 - No cooling heating
Cooling Energy kWh
Total Energy kWh
EPI kWh/m2
1,34,318 1,29,279 1,07,736 1,01,395 1,32,141 1,27,044 1,26,053 1,05,462 9,894 0
2,01,758 1,96,418 1,73,690 1,67,556 1,99,462 1,60,111 1,65,692 1,72,585 71,777 61,771
129 125 111 107 127 102 106 110 46 39
1. Impact on cooling load • Eliminating the wall heat gain only reduces the cooling energy by 2.8%, whereas that of roof gives a reduction of 13.3%. • 18.71% decrease in the cooling energy is seen when window radiation is eliminated. • A decrease of 9.8% is seen when the impact of equipment is eliminated. • Figure 15 shows the effect on the cooling EPI for various elimination parametric. A major reduction can be seen by eliminating the radiative heat gain from windows and optimizing roof construction assembly which can be proposed as ECMs.
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ELIMINATION PARAMETERS
EP9-No Cooling Heating
0
EP8-Vent Air
6
EP7-People Gain
67
EP6-Equip Gain
80
EP5-Lights Gain
81
EP4-Win Cond Gain
84
EP3-Win Rad Gain
65
EP2-Roof Ht Gain
69
EP1-Wall Ht Gain
82
AS-IS Case
86 0
10
20
30
40
50
60
70
80
90
COOLING EPI (kWh/sqm) Figure 15 Comparison of elimination parameters for annual cooling energy
2. Impact on EPI and energy cost savings • Maximum cost saving potential is seen by eliminating electrical lighting gain (INR 3,70,658 annually). • Eliminating heat gains from roof and window radiation shows a saving of 14% and 17% respectively. This also helps in reduction of cooling load by 20% and 25% which will reduce the system size and the overall energy use of the building. • Only a reduction of 2% in the EPI is seen when heat gain from window is eliminated. • Figure 16 shows the comparison between reduction in EPI and energy cost savings. Implementing ECMs for parameters like electrical lighting, heat gin from roof and window radiation gains will reduce the cooling load, the overall system size and thus will reduce the capital cost. 100%
93%
100%
90% 80%
PERCENTAGE
70%
64%
69%
60% 50% 40% 30%
20% 14%
20% 10%
4%3%
25%
21%
17% 2%1%
5%
18%
21% 14%
6%
0% EP1-Wall EP2-Roof Ht EP3-Win EP4-Win EP5-Lights EP6-Equip EP7-People EP8-Vent Ht Gain Gain Rad Gain Cond Gain Gain Gain Gain Air
EP9-No Cooling Heating
ELIMINATION PARAMETERS Percentage reduction in cooling
Percentage reduction in energy
Figure 16 Percentage reduction in EPI and energy cost savings
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Energy Conservation Measures 1. Orientation
Table 6 Results of sensitivity analysis for orientation
Objective: To minimize the heat gain through conduction and radiation of the envelope.
Cases
Description: The building was rotated at an interval of 45º to analyze the impact of total load on the building. Results: gives the results from the sensitivity analysis of the orientation. A maximum reduction of EPI can be seen when the building is oriented at 270º. This also aligns with the daylight analysis done in Section 3 where optimum results were obtained when the building orientation was 270º.
AS-IS Case 45 90 135 180 225 270 315
Total Load kWh
EPI
Reduction %
2,01,758 2,02,202 1,99,635 1,99,038 1,99,779 2,00,644 1,98,481 2,00,592
129 129 127 127 127 128 127 128
-0.22% 1.05% 1.35% 0.98% 0.55% 1.62% 0.58%
2. Building Envelope 2.1
Wall
Objective: To minimize heat transfer through external wall. Description: U-values at interval of 0.12 were simulated to analyze the effect of total load on the building. A typical cost of ₹1500/m3 was considered for wall construction with an insulation cost of ₹7500/m3. (Parikh, 2018) Results: Figure 17 depicts the trend in the energy savings and net incremental cost for various u-values simulated. With 2% energy savings and 16% increase in net incremental cost, 0.48 W/m2.K was selected as the optimum u-value for the proposed case. ₹ 600
₹ 558 3.0%
2.1%
₹ 300 1.0%
1.4%
1.8%
2.0% 1.5%
₹ 318
1.0%
₹ 235 ₹ 210
₹ 106
0.5%
₹ 126
0.00
0.12
0.24
0.36
0.48
0.0%
0.60
0.72
0.84
0.96
1.08
1.20
₹ 71 ₹ 64 ₹ 68 ₹ 65 ₹ 69 ₹ 65 ₹ 73 ₹ 80
1.32
1.68
1.80
1.92
2.04
2.16
₹-
0.9%
1.44
₹ 100
₹ 95 ₹ 106 0.6% ₹ 108 ₹ 101 0.5% 0.3% 0.2% 0.1% ₹ 89 ₹ 83 0.0%
0.8%
1.56
₹ 200
1.1%
1.3%
1.6%
1.7%
2.6% 2.5%
2.2%
PERCENTAGE
₹ 400
2.28
NET INCREMENTAL COST (INR) * 1000
2.5% 2.4%
₹ 500
U-VALUE (W/sqm.K)
Net incremental total cost (INR)
Energy savings (%)
Figure 17 Percentage change in net incremental cost and energy savings for wall
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2.2
Roof
Objective: To minimize heat transfer through external roof. Description: U-values at interval of 0.18 were simulated to analyze the effect of total load on the building. A typical cost of ₹1500/m3 was considered for roof construction with an insulation cost of ₹7500/m3. (Parikh, 2018) Results: Error! Reference source not found. depicts the trend in the energy savings and net incremental cost f or various u-values simulated. With 21.3% energy savings and 51% decrease in net incremental cost, 0.35 W/m2.K was selected as the optimum u-value for the proposed case. ₹ 1,258
₹ 1,200
13.1% 14% 12.3% 13.9% 11.5%
₹ 1,000
₹ 400
₹ 544
₹ 444
₹ 512
₹ 200
₹ 281 ₹ 481
₹ 387 ₹ 334
₹0
2.2% 1.6% 1.2% -₹ 200 0.5% 0.0%
12%
10.3% 9.5% 8.7% 8.0% 7.3% 6.6% 5.9% ₹ 169 5.2%
₹ 800 ₹ 600
16%
₹ 283
8% 6%
₹ 104
₹ 265
2.7% 3.3%
4.0% 4.6% ₹ 50
₹ -17
10%
₹ 814
₹ -53
₹ -152 ₹ -125
₹ -178
PERCENATGE
NET INCREMENTAL COST (INR) * 1000
₹ 1,400
4%
₹ -74 ₹ -152
2% 0%
0.01
0.17
0.35
0.53
0.71
0.89
1.07
1.25
1.43
1.61
1.79
1.97
2.15
2.33
2.51
2.69
2.87
3.05
3.23
3.41
3.59
-₹ 400 U-VALUE (W/sqm.K)
Net incremental cost (INR)
Energy savings (%)
Figure 18 Percentage change in net incremental cost and energy savings for roof
2.3
Window
Objective: To minimize conductive and radiative heat gain through appropriate glass selection. Description: To arrive at the optimum assembly for windows, sensitivity analysis was done separately for u-value and SHGC of glass. An interval of 0.5 was chosen for u-value and 0.1 for SHGC. Since the AS-IS case had no shading device, a comparison was also done by adding shading device designed as per daylight analysis for zones in different directions of the building. Visible light Transmittance (VLT) of 0.50 has already been chosen as per daylight analysis. Results: •
U-Value Energy saving of only 1.1% is seen when the u-value is reduced from 7.7 W/m2.K to 0.10 W/m2.K. The energy saving is very low because cooling load is calculated based on the room temperature, but the u-value of the glass would affect the mean radiant temperature of the space. Since, eQuest does not show the operative temperature of spaces, an ECBC recommended u-value of 3 W/m2.K has been chosen for the proposed case.
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Whole Building Simulation Report | Yashima Jain
•
SHGC Window with no shading give energy savings of 2% - 15% for various SHGC values. Minimum heat gain is from the northern side and maximum from western side. For the north and east façade, a SHGC of 0.49 has been proposed and for south and west façade, 0.29 is proposed. North façade does not have shading, while south, east and west façade have shading devices as proposed in Proposed shading and window design measures.
SOLAR HEAT GAIN (kW) * million
8 7 6 5 4 3 2 1 0.09
0.19
0.29
0.39 0.49 SHGC CASES
0.59
0.69
0.79
NORTH_W/O SHADING
SOUTH_W/O SHADING
WEST_W/O SHADING
EAST_W/O SHADING
NORTH_WITH SHADING
SOUTH_WITH SHADING
WEST_WITH SHADING
EAST_WITH SHADING
Figure 19 Comparison of SHGC cases with and without shading devices
For SHGC – 0.49 without shading device, the HVAC system size has reduced by 7% with first cost savings of INR 2.6 lakhs. For SHGC – 0.49 with shading device, the HVAC system size has reduced by 11% with first cost savings of INR 4.1 lakhs. For SHGC – 0.29 with shading device, the HVAC system size has reduced by 12.25% with first cost savings of INR 4.82 lakhs.
2.4
Electrical Lighting
Objective: To reduce electric lighting energy with appropriate lighting design including fixture selection. Description: The lighting power density (LPD) of each pace is reduced to reduce the lighting loads of the space. The LPD of the spaces was taken for an Super ECBC building mentioned in space function method in ECBC-2017.
Reduction in total load (%)
11%
5%
Reduction in cooling (%)
1%
0%
3%
2%
Super ECBC case
4%
6%
8%
10%
12%
ECBC + case
Results: As per Figure 20, lighting energy Figure 20 Comparison of load reduction for LPD consumption reduces by 23% and 51% and cooling load reduces by 1% and 3% for ECBC+ and Super ECBC levels. This leads to only a reduction of 0.95% and 1.96% in system sizing. Hence, Super ECBC level has been chosen for the proposed case.
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Whole Building Simulation Report | Yashima Jain
2.5
Lighting control measures: Occupancy Sensors
Objective: To reduce the electric lighting energy by turning off the lights when they are not needed. Description: Occupancy based sensor controls are provided for the spaces to turn off lights when the spaces are unoccupied. They are provided in 21 spaces of the building. Since Super ECBC level has been proposed as lighting measure, reduction in LPD by occupancy sensors was calculated based on that data. These sensors have been proposed in the restrooms on the ground floor, and restrooms, circulation spaces and canteen on the upper floors. The fixed and floating population was estimated on each floor. Time spent per person was assumed to be 2.5 mins. Based on this total occupied hours were calculated for the restrooms. This was further rationalized by the occupancy schedule of the space. For restrooms, a reduction of 40% was calculated for the ground, first and second floor and 80% for third floor. The same procedure was similarly followed for the circulation spaces on the upper floors. Results: The spaces where occupancy sensors have been proposed accounts for 26% of total building area. Figure 21 shows that lighting load reduces by 58% and energy load by 41%. The incremental cost is INR 1.35 lakhs.
2.6
Daylighting controls
Objective: To reduce the electric lighting in spaces which have access to daylight. Description: Daylighting controls with dimming have been proposed in the perimeter zones of the building. This means that when the illuminance levels in daylight zones are sufficient the artificial lights for the zones can be dimmed. A continuous dimming daylighting control has been set up at 2.4m from the window and are ceiling mounted. Dimming controls have been used in this case where the fixtures dim to a maximum of 80%. Results: Daylighting controls with dimming are provided in all the perimeter zones covering 51% of total building area. Figure 21 shows that lighting load reduces by 55% and energy load by 46%. The incremental cost is INR 5.46 lakhs.
46.1%
Super ECBC LPD with Occupancy and Daylight sensors
55.2%
41.7%
Super ECBC LPD with Occupancy sensors
58.1%
10.5%
Super ECBC Case
50.8%
4.7%
ECBC+ case
22.9%
0%
10%
20%
30%
40%
50%
60%
70%
PERCENTAGE Reduction in total load (%)
Reduction in lighting (%)
Figure 21 Comparison of light load reduction and total load reduction
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Whole Building Simulation Report | Yashima Jain
2.7
Thermostat control based on adaptive comfort
Objective: To reduce the cooling loads by varying the setpoint temperatures based on the outdoor temperature as suggested by the Indian Model for Adaptive Comfort (IMAC). Description: The upper and lower limit for mixed mode building operation was calculated based on the 30-day moving average and neutral temperature limit for the entire year on hourly basis. This was used to calculate the setpoint temperatures for each month. Results: There is a 6% decrease in the cooling energy consumption, and 4% decrease in the annual energy consumption of the building. The total system size reduces by 10%.
2.8
Months January February March April May June July August September October November December
AS-IS Case (ºC)
Proposed Case (ºC)
25 25 25 25 25 25 25 25 25 25 25 25
24 25 25 26 27 27 26 25 25 25 25 24
HVAC system alternatives
Objective: To reduce energy consumption by selecting higher efficiency cooling systems. Description: Various systems like split AC units, air cooled and water cooled VRF system and air-cooled chiller system of different COPs were simulated to arrive at a system which gives higher energy savings, with a low payback period. Table 7 Description of HVAC systems
System type
System COP
AS-IS Case, Split AC unit – BEE 3-star
3.3
Split AC unit – BEE 5-star
4.5
Air cooled VRF system Water cooled VRF system
3.4 4.0 4.4 5.0 4.2
Air cooled chiller system 4.8 Water cooled chiller system Evaporative cooler
4.5 5.7 -
System description For the AS-IS case, BEE 3-star recommended split AC units with a COP of 3.5 were used. The AS-IS case system was replaced by BEE 5-star recommended split AC units with a COP of 4.5. The AS-IS case system was replaced by an air-cooled VRF system with COPs of 3.4 and 4.2 in all the conditioned spaces. The AS-IS case system was replaced by a water cooled VRF system with COP of 4.4 and 5. On the water side, a heat rejection system was used. The AS-IS system was replaced by an air-cooled chiller system with COP of 4.2 and 4.8. An AHU is placed on every floor which is connected to a VAV system on that floor. A screw chiller with variable speed drive has been used. The AS-IS system was replaced by a water-cooled chiller system with COP of 4.5 and 5.7. A screw chiller with variable speed drive has been used which is further connected to a cooling tower for heat rejection The AS-IS case system was replaced by an indirect / direct evaporative cooling system with an air flow capacity of 30,000 cfm.
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Whole Building Simulation Report | Yashima Jain
Results: Figure 22 shows percentage energy savings for HVAC system types and incremental cost per ton. For split AC system, by changing the COP from 3.3 to 4.5, there is an reduction in cooling energy consumption by 27% and energy savings by 14%. The net incremental cost is INR 18.20L and INR 27.95L with a payback period of 1.0 years and 1.89 years respectively. For air cooled VRF systems, the system COP is increased from 3.3 (AS-IS case) to 3.4 and 4 the cooling energy consumption reduces by 25% and 36% and overall energy consumption by 10% and 18%. The net incremental cost is INR 33.70L and INR 37.26L with a payback period of 2.09 years and 2.52 years. For water cooled VRF systems, the system COP is increased from 3.3 (AS-IS case) to 4.4 and 5 the cooling energy consumption reduces by 47% and 53% and overall energy consumption by 13% and 18%. The net incremental cost is INR 42.52L and INR 45.45L with a payback period of 2.73 years and 3.09 years. For air cooled chiller systems, the system COP is increased from 3.3 (AS-IS case) to 4.2 and 4.8 the cooling energy consumption reduces by 15% and 26% and overall energy consumption by 8% and 15%. The net incremental cost is INR 75.73L and INR 70.73L with a payback period of 4.56 years and 4.62 years. For water cooled chiller system, the system COP is increased from 3.3 (AS-IS case) to 4.5 and 5.7 the cooling energy consumption reduces by 32% and 44% and overall energy consumption by 8% and 15%. The net incremental cost is INR 95L and INR 128L with a payback period of 6.12 years and 9.11 years. The highest energy savings of 33% were achieved by using an evaporative cooler. But due to high unmet hours of 3961, this was ruled out as a measure for system alternative. Split AC units
Air cooled VRF
Water cooled VRF
Air cooled chiller
Water cooled chiller
120
22%
100 80
15%
14%
60
24% 20%
18%
18%
28%
16%
13%
13%
12%
10% 8%
40
PERCENTAGE
INCREMENTAL COST (INR/sqm) * 1,00,000
140
8%
20
4%
-
0% 3.30
4.50
3.42
4.02
4.39
5.70
4.20
4.80
4.50
5.70
SYSTEM TYPES Net incremental cost (INR)
Energy savings (%)
Figure 22 Comparison of net incremental cost and energy savings
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Whole Building Simulation Report | Yashima Jain
Based on the sensitivity analysis, an ECM bundle was prepared which gave an EPI of 62 kWh/m2 with annual energy savings of 52% from the AS-IS case. This is an annual energy savings of INR 9.36L. A net incremental cost of INR 45L and a payback period of 4.8 years is achieved for the proposed case. Figure 23 Energy consumption comparison for AS-IS and proposed caseFigure 23, shows a comparison of the energy consumption between the AS-IS case and proposed case. The cooling load reduces by 68%, and the lighting load by 78%. The total fan energy increases by 70%. There is no change in equipment load.
ENERGY USE INTENSITY (kWh/sqm)
ECM Bundle 140 120 100
52% reduction
80 60 40 20 AS-IS Case Cooling
Fans
Proposed Case Equipment
Lighting
Figure 23 Energy consumption comparison for AS-IS and proposed case
Figure 24 gives an energy use breakdown for various energy conservation measures. The EUI has been reduced from 129 kWh/m2 to 62 kWh/m2 by implementing active and passive strategies in the design. Passive strategies like orientation, shading, optimizing the building envelope have been incorporated. Reducing lighting power density reduces the internal heat gains, thus decreasing the fan and cooling energy consumption. The daylighting and occupancy sensor lighting control help in reducing the lighting and total energy consumption by 46%. The HVAC system is modified to an air cooled VRF system (COP 4.2). Air cooled VRF (COP 4.02) Adaptive Thermostat control Daylighting Sensors Occupancy Sensors LPD - super ecbc Shading SHGC Roof Wall Orientation AS-IS Case Cooling (kWh/sq.m)
20
40
Fans (kWh/sq.m)
60
80
Equipment (kWh/sq.m)
100
120
140
Lighting (kWh/sq.m)
Figure 24 Energy use breakdown due to energy conservation measures
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Whole Building Simulation Report | Yashima Jain
Modelling for ECBC Compliance Table 8 provides a comprehensive list of the various input parameters required to achieve an ECBC compliance. It should be noted that building only with connected load higher than 100 kW can be complaint with ECBC. Also, unmet hours for the ECBC complaint design shall not exceed 300. Table 8 Input parameters for achieving ECBC compliance
Input Parameters
AS-IS Case
Building Details Area Electricity rate Electricity Demand Rate
Building Schedules
Occupant density
Minimum OA ventilation Lighting Lighting power density (W/sqm)
Lighting Control devices
Exterior Lighting Equipment Loads Envelope Roof Assembly (W/m2.K) Roof Assembly (SRI Value) Above grade wall assembly (W/m2.K) WWR (%) North facade WWR (%) West Façade WWR (%) South Façade WWR (%) East Façade WWR (%) Window assembly (W/m2.K)
Proposed Design
ECBC Baseline
1586 m2 ₹ 8.90/kWh/month ₹ 8.90/kWh/month Occupancy, lighting equipment and HVAC schedule modelled as per functioning of bank Fixed and floating population calculated as per furniture layout provided and floating population Space wise inputs as per NBC 2016 LPD for ECBC compliant building
-
Space wise equipment calculation for BEE-3 star recommended appliances
Same as AS-IS case
To be modelled as per section 9.6 of NBC 2017
Same as AS-IS case
LPD for Super ECBC compliant building Occupancy sensors for restrooms and circulation spaces on upper floors. Daylight sensors for perimeter zones. -
LPD for ECBC compliant building Central programmable timing controls are
mandatory. -
Same as AS-IS Case
3.59 0.65
0.35 0.85
0.33 > 0.60
2.28
0.48
0.40
Same as AS-IS Case
Same as AS-IS Case
3
3
22 25 24 16 28 7.7
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Whole Building Simulation Report | Yashima Jain
SHGC of North window SHGC of Non-north window Thermal zoning HVAC System System type Fan control Cooling type
Heating Type
North and east – 0.49 South and south – 0.29 Based on perimeter zoning and core zone, and segregation of condition and unconditioned spaces 0.79
0.5 0.27 As per Table 9.1 of ECBC 2017
Split AC (COP 3.30) Air cooled VRF (COP: 4.02) VRF system Variable Constant Direct expansion with air cooled condenser Where no heating system has been specified or where an electric heating system has been specified in the Proposed Design
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Whole Building Simulation Report | Yashima Jain
Appendix 1. Appendix A: Results of elimination parametric AS-IS Case Elimination Parametrics EP1-Wall Ht Gain EP2-Roof Ht Gain EP3-Win Rad Gain EP4-Win Cond Gain EP5-Lights Gain EP6-Equip Gain EP7-People Gain EP8-Vent Air EP9-No Cooling Heating
kWh/sq.m 3.61
Equipment (Interior) kWh/sq.m 17.56
Lighting (Interior) kWh/sq.m 21.82
kWh/sq.m 129
Annual Cooling Peak kW 252
kWh NA
Energy cost Savings Rs NA
Cooling Capacity Tons 71.79
82.40
3.42
17.56
21.82
125
240
₹5,340
₹47,526
68.29
247.27
68.67
2.67
17.56
21.82
111
179
₹28,068
₹2,49,805
50.82
332.30
64.63
2.80
17.56
21.82
107
212
₹34,202
₹3,04,398
60.33
279.90
84.23
3.54
17.56
21.82
127
249
₹2,296
₹20,434
70.80
238.51
80.98
3.49
17.56
0.03
102
245
₹41,647
₹3,70,658
69.66
242.40
80.35
3.44
0.01
21.82
106
243
₹36,066
₹3,20,987
68.98
244.81
67.22
3.41
17.56
21.82
110
199
₹29,173
₹2,59,640
56.46
299.07
6.31
0.07
17.56
21.82
46
57
₹1,29,981
₹11,56,831
16.23
1040.77
0.00
0.00
17.56
21.82
39
48
₹1,39,987
₹12,45,884
13.51
1250.32
Cooling EPI
Fans
kWh/sq.m 85.62
EPI
Energy Savings
Peak Cooling sq.ft/ton 235.24
2. Appendix B: Output summary for ECMs Cooling
Fans
Equipme nt
Lighting
EPI
(kWh/sq. m)
(kWh/sq. m)
(kWh/sq. m)
(kWh/sq. m)
(kWh/sq. m)
(INR)
AS-IS Case
86
22
18
4
129
Orientation
84
22
18
3
Wall
81
22
18
Roof
66
22
SHGC
55
Shading
ECMS
LPD - super ecbc Occupancy Sensors Daylighting Sensors Adaptive Thermostat control Air cooled VRF (COP 4.02)
Total Consumptio n Charge
Total Energy Cost (INR/s q.m)
Cooling Peak
Energy Savings
Energy savings
Cooling Capacity
Peak Cooling
Unmet Hours
(kW)
(kWh)
INR
(Tons)
(Sf/ton)
Hours
17,95,646
1,145
252
-
-
72
235
0
127
17,66,481
1,127
198
3,277
29,165
56
300
0
3
124
17,32,332
1,105
200
7,114
63,315
57
297
0
18
2
108
15,04,563
960
118
32,706
2,91,083
34
503
0
22
18
2
96
13,36,219
852
93
51,621
4,59,427
26
638
0
50
22
18
2
91
12,70,306
810
86
59,027
5,25,340
24
690
0
47
11
18
2
77
10,73,242
684
81
81,169
7,22,404
23
733
0
47
9
18
2
75
10,46,462
667
81
84,178
7,49,184
23
733
0
45
5
18
1
69
9,67,127
79
93,092
8,28,519
22
751
0
43
5
18
1
67
9,38,452
599
78
96,314
8,57,195
22
759
0
27
5
18
12
62
8,59,286
548
78
1,05,209
9,36,360
22
759
71
617
25