Energy Efficiency in Buildings NZEB,ZEB and beyond
A perspective
Rangan Banerjee
Forbes Marshall Chair Professor
Department of Energy Science and Engineering
IIT Bombay
10th August 2020 - Online Faculty Development Programme Nearly Zero Energy Building
What is an energy system?
DESE-IIT Bombay Rangan Banerjee 2
ENERGY FLOW DIAGRAM
PRIMARY ENERGY
ENERGY CONVERSION FACILITY
SECONDARY ENERGY
TRANSMISSION & DISTRN. SYSTEM
COAL, OIL, SOLAR, GAS
POWER PLANT, REFINERIES
REFINED OIL, ELECTRICITY
RAILWAYS, TRUCKS, PIPELINES
WHAT CONSUMERS BUY DELIVERED ENERGY
AUTOMOBILE, LAMP, MOTOR, STOVE
MOTIVE POWER RADIANT ENERGY
DISTANCE TRAVELLED, ILLUMINATION,COOKED FOOD etc..
FINAL ENERGY
ENERGY UTILISATION EQUIPMENT & SYSTEMS
USEFUL ENERGY
END USE ACTIVITIES
(ENERGY SERVICES)
3DESE-IIT Bombay Rangan Banerjee
4
Energy End Uses
Boiler, GeyserFluid heatedHeating
Fans,AC, refrigSpace CooledCooling
motorsShaft workMotive Power
Cycle, car, train,
motorcycle, bus
Distance
travelled
Transport
Incandescent
Fluorescent, CFL
IlluminationLighting
Chullah, stoveFood CookedCooking
DeviceEnergy ServiceEnd Use
DESE-IIT Bombay Rangan Banerjee
Sustainable ?
Is our present consumption and growth pattern sustainable? Can we continue this into the future?
5DESE-IIT Bombay Rangan Banerjee
What is sustainable Development?
6
Development that meets the needs of the present without compromising the ability of future generations to meet their own needs.Brundtlant Report WCED 1987Development without cheating ourchildren
DESE-IIT Bombay Rangan Banerjee
Global Trends – Unbounded Growth?
www.globalenergyassessment.org
7DESE-IIT Bombay Rangan Banerjee
8
Are our energy systems sustainable?
DESE-IIT Bombay Rangan Banerjee
Rockstrom et al, Nature 2009
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Long term global temperature record
Rockstrom et al, Nature 2009
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Carbon Dioxide Concentrations
http://cdiac.ornl.gov/trends/co2/graphics/lawdome.gif
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Carbon Dioxide Concentrations
12DESE-IIT Bombay Rangan Banerjee
Recent Carbon dioxide concentrations
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https://scripps.ucsd.edu/programs/keelingcurve/
Recent Carbon dioxide concentrations
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https://scripps.ucsd.edu/programs/keelingcurve/
15
Source: IPCC, 2011
DESE-IIT Bombay Rangan Banerjee
www.ipcc.ch
16DESE-IIT Bombay Rangan Banerjee
Metrics for (Un)sustainability
17
• Adverse global impacts – climate change problem – “Tipping point” 2⁰ C – 1.5 ⁰ C
• Adverse local health impact
• Urban Air Quality, Indoor Air Quality
• Land Use and Availability
• Water availability and use
• Equity issues
• Financing and Capital
• Energy Security (In-security)
DESE-IIT Bombay Rangan Banerjee
Carbon Dioxide Emissions
• Kaya identity: Total CO2 Emissions
= (CO2/E)(E/GDP)(GDP/Pop)Pop
CO2/E – Carbon Intensity
E/GDP- Energy Intensity of Economy
• Mitigation – increase sinks, reduce sources-aforestation, fuel mix, energy efficiency, renewables, nuclear, carbon sequestration
• Adaptation
18DESE-IIT Bombay Rangan Banerjee
Global Final Energy use in Buildings- Potential
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www.globalenergyassessment.org Chapter 10
Buildings- End Use (US)
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www.globalenergyassessment.org Chapter 10
Share of End-Uses by Appliance in Electricity Consumption in Delhi
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www.globalenergyassessment.org Chapter 10
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What is India’s current energy use pattern?
Energy Balance for India-2017 (Sankey Diagram)
All values are in Exa Joule (EJ)
Data Source: IEA
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Development in India
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Nature Energy | VOL 4 | December 2019 | 1025–1032 | www.nature.com/natureenergy N.Rao et al
End –Uses Buildings
25
Source: GEA Chapter 10
DESE-IIT Bombay Rangan Banerjee
End Use Electricity by Appliances – New Delhi
26
Source: GEA Chapter 10
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Building Site Energy Use- Mix
27
Source: GEA Chapter 10
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Building stock growth
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Residential demand scenarios by stock type
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Approach for Energy Efficiency in Buildings
A design approach that
integrates architectural and
engineering solutions at an
early design stage is
required for getting an energy-efficient design
Building
Energy
Consumption
Architectural
Design
Building
Envelope
Climate
Building usage:
function, number of
users; period of use etc.
Artificial Lighting,
HVAC, Equipment
and Renewable
Energy
30DESE-IIT Bombay Rangan Banerjee
Building Envelope
Most of the cooling load in the buildings originates from solar heat gains and heat transmission
through the envelope (Windows, walls and roof)
The main building envelope features that influence the cooling thermal energy demand
are as follows
▪ Insulation properties of wall
▪ Insulation properties of roof
▪ Size and location of window openings
▪ Shading system for windows
▪ Window properties
▪ Colour and finish of exterior surfaces
▪ Natural ventilation
▪ Building air-tightness
31DESE-IIT Bombay Rangan Banerjee
Reduction of Heat Flow through Walls
150 mm
concrete wall
115 mm brick
230 mm brick
115 mm + 50 mm
cavity +115 mm brick
230 mm + 50
mm cavity
+115 mm brick
200 mm AAC
230 mm brick
+ 65 mm XPS
U= 3.3
W/m2.K
2.8 W/m2.K
2.0 W/m2.K
1.4 W/m2.K
1.1W/m2.K
0.7 W/m2.K 0.4 W/m2.K
32DESE-IIT Bombay Rangan Banerjee
CLIMATIC ZONES
HOT - DRY
WARM – HUMID
COMPOSITE
TEMPERATE
COLD
Requirements vary
Design features change
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https://www.nrdc.org/issues/prepare-india-extreme-heat
Cool Roofs - Ahmedabad
Shardaben Hospital White Mosaic Cool Roof
https://www.nrdc.org/
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Vehicle EfficiencyIndustrial EfficiencyBuilding EfficiencyFuel switchEnergy Intensity
Annual CO2 Emissions (Ahmedabad)M
illio
n T
on
ne
sC
O2
2.32t/capita
8.15t/capita
3.13t/capita
5.63t/capita
2.16t/capita
http://2050.nies.go.jp/report/file/lcs_asialocal/ahmedabad_2010.pdf
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BEE Case study-CESE IITK
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ECBC Case study- Source BEE
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ECBC Case Study –Source BEE
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Star Labelling (>50% AC)
Source: BEE
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Star labelling <50% AC
Source: BEE
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Survey of EPI for different climate
6-020-15 SHUKLA ET AL ECEEE SUMMER STUDY PROCEEDINGS
Radiant Cooling
Example of commercial application of radiant cooling
▪ Radiant cooling for the first time in commercial building in India
▪ SDB-1 (Hyderabad SEZ) has 2 identical halves, one with radiant
cooling and other with conventional air conditioning
▪ This building is today the biggest demonstration of
cooling technology comparison
42DESE-IIT Bombay Rangan Banerjee
Schematic of renewable energy options for buildings
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http://64.243.182.248/includes/pv%20tutorial.pdf
ModulePanel
Solar Photovoltaics
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CII-IBC Building - Hyderabad
45DESE-IIT Bombay Rangan Banerjee
Building Integrated PV
http://www.iea-pvps-task2.org/
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Compute Energy use
• How would you compute?
• Electricity use: Monthly electricity bill:
120 kWh/ month
• Cooking : LPG ~ 1 cylinder / month
• Final Energy use - Elec = 120×3600/ 1000 MJ = 432 MJ
LPG = 14.2 × 42 MJ = 596.4 MJ
Total = 1028 MJ/ month = 12.3 GJ/ year/ Household
Primary energy = 432/0.3+ 596.4/0.9 = 2100 MJ/ month
= 25.2 GJ/ year = 6.3 GJ/ capita/ year
47DESE-IIT Bombay Rangan Banerjee
Energy Bill and Carbon
• Electricity Cost = 5×120×12= Rs 7200
• LPG Rs 450×12= Rs 5400 (Rs 10800 - unsubsidised)
• Total Annual: Rs 12600 (Rs 18000)
• Emission factor = 0.89 kg CO2/ kWh
LPG = 65 kg CO2/ GJ
CO2 emissions = 1440×0.89+596.4×12×65/1000
=1281 + 465.2 = 1746 Kg CO2/ year (436 kg CO2/ capita)
48DESE-IIT Bombay Rangan Banerjee
Wind Power systems
49
http://www.AurovilleWindSystems.com
2 kW peak rating, weight 120 kg
DESE-IIT Bombay Rangan Banerjee
Solar Cooking
http://gadhia-solar.com/products/community.htm
Double Community Cooker- Rishi Valley School
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Solar Cooking - kitchen
mnes.nic.in/solar-stcooker.htm
Solar Kitchen Rishi Valley
http://gadhia-solar.com
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52
Cooking with the Sun Concentrators
live.pege.org Balcony system
(Dhule: Ajay Chandak)
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Solar Cooking
• Tirumala(Tirupati) – 4 T/day of steam – food for 15000 people
Solar parabolic Concentrators
• Solar cooking – Suitable for Institutions/ Community kitchen
Army mess, Ladakh
• Households- difficult –change in cooking habits
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Rice Husk gasifier Cookstoves
54
Anderson, 2012
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Oorja stove
55
Mukunda et al, 2010
http://www.firstenergy.in
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Biolite Stove
56
Source: GEA Chapter 10
http://www.biolitestove.com
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Sampada Biomass Gasifier Stove
57
Source: www.arti-india.org/
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Compact Biomass Gasifier
58
Source: www.arti-india.org/
1 m3 – digestor – 2 kg kitchen waste
0.5 m3 – digestor –1 kg kitchen waste
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Standard Fan vs Efficient Fan
59
Standard Fan Efficient FanPower 70 W 35 WPrice Rs 1300 Rs 2600
BLDC motorLife : 10years Sweep 1200 mm RPM – 350-400
Similar air delivery 230 m3/min
DESE-IIT Bombay Rangan Banerjee
TEAM SHUNYASOLAR DECATHLON EUROPE 2014
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House in Versailles – 26th June, 2014
Team Shunya
70 students 13 disciplines 12 faculty
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Electrical Energy Balance
Generation-Consumption Profile for Competition Day 1, June 30th 2014
0
500
1000
1500
2000
2500
3000
3500
4000
1:00AM
3:00AM
5:00AM
7:00AM
9:00AM
11:00AM
1:00PM
3:00PM
5:00PM
7:00PM
9:00PM
11:00PM
Demand (Wh) Supply (Wh)
-4
-3
-2
-1
0
1
2
3
4
Pow
er i
n k
W
Feed in Grid Load PV
Generation Consumption Profile for the competition duration
Performance:• PV Supply = 281 kWh, Demand = 146 kWh• Net Energy Positive, 135 kWh in 12 days• Energy payback analysis% for PV = 2.4 years
SDC Dezhou 2018 China
DESE-IIT Bombay Rangan Banerjee
Team Shunya
63
Plan Layout
64
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A portion of the ELU map of Ward A of MCGM
Corresponding Satellite Imagery for the area from Google Earth
Analyzed in QGIS 1.8.0To determine-Building Footprint Ratios- Usable PV AreasFor Sample Buildings
66
0
0.5
1
1.5
2
2.50:0
1-
1:0
0
1:0
1-
2:0
0
2:0
1-
3:0
0
3:0
1-
4:0
0
4:0
1-
5:0
0
5:0
1-
6:0
0
6:0
1-
7:0
0
7:0
1-
8:0
0
8:0
1-
9:0
0
9:0
1-1
0:0
0
10:0
1-1
1:0
0
11:0
1-1
2:0
0
12:0
1-1
3:0
0
13:0
1-1
4:0
0
14:0
1-1
5:0
0
15:0
1-1
6:0
0
16:0
1-1
7:0
0
17:0
1-1
8:0
0
18:0
1-1
9:0
0
19:0
1-2
0:0
0
20:0
1-2
1:0
0
21:0
1-2
2:0
0
22:0
1-2
3:0
0
23:0
1-2
4:0
0
MU
sJan, 2014 Typical Load Profile vs
PV Generation
1-AxisTracking @Highest eff.
1-AxixTracking @Median eff.
19 deg. FixedTilt @ Highesteff.
19 deg. FixedTilt @ Medianeff.
0.115
0.125
0.135
0.145
0.155
0.165
0.175
0.185
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Capacity Factor for Mumbai
1-Axis Tracking
Fixed Tilt @ 19deg.
Annual Averagewith 1-AxisTracking
DESE-IIT Bombay Rangan Banerjee
Target area
Weather data, area details
Identification and Classification of different end uses by sector (i)
Residential (1)Hospital (2) Nursing
Homes (3)Hotels
(4)Others (5)
POTENTIAL OF SWHS IN TARGET AREA
Technical Potential (m2 of collector area) Economic
Potential (m2 of collector area) Market Potential (m2 of
collector area) Energy Savings Potential
(kWh/year) Load Shaving Potential (kWh/ hour for
a monthly average day)
* Factors affecting the adoption/sizing of solar water heating systems
Sub-class (i, j)
Classification based on factors* (j)
Single end use point
Potential
Base load for
heating
Electricity/ fuel savings
Economic
viability
Price of
electricity
Investment
for SWHS
Technical
PotentialSWHS
capacity
Constraint: roof
area availability
Capacity of
SWHS (Collector
area)
Target
Auxiliary
heating
Single end use point
Micro simulation using
TRNSYS
Hot water
usage pattern
Weather
data
SIMULATION
Auxiliary heating requirement
No. of end
use points
Technical
Potential
Economic
Potential
Economic
Constraint
Market
Potential
Constraint: market
acceptance
Potential for end use sector (i = 1) Potential
for i = 2
Potential
for i = 3
Potential
for i = 4
Potential
for i = 5
DESE-IIT Bombay Rangan Banerjee 67
Model for Potential Estimation of Target Area
Load Curve Representing Energy Requirement for Water Heating
0
100
200
300
400
500
600
700
800
900
1000
0 2 4 6 8 10 12 14 16 18 20 22 24Hour of day
En
erg
y C
on
sum
pti
on
(M
W)
Typical day of January
Typical day of May
Total Consumption =760 MWh/day
Total Consumption = 390 MWh/day
53%
Electricity Consumption for water heating of Pune
Total Consumption =14300 MWh/day
Total Consumption = 13900 MWh/day
Total Electricity Consumption of Pune
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Dhariwal and Banerjee, Building Simulation, Springer Nature (2017)
Building model methodology
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Building Orientation and inputs
DESE-IIT Bombay Rangan Banerjee
Dhariwal and Banerjee, Building Simulation, Springer Nature (2017)
70
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Building Correlations developed
Dhariwal and Banerjee, Building Simulation, Springer Nature (2017)
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Solution Procedure
Dhariwal and Banerjee, Building Simulation, Springer Nature (2017)
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Microgrid Sizing
Insolation at New Delhi: (a) weekly average annual data and
(b) hourly average daily data for a winter day
For a remote village (a) Seasonal variation of load for the year, (b) hourly variation of load
For a remote welding shop instantaneous
variation in load for an hour
Microgrid Sizing
DESE-IIT Bombay Rangan Banerjee 74
Microgrid Sizing
❑ Rate of Energy stored in storage device,
𝑑𝑄𝑠
𝑑𝑡= 𝑃 𝑡 − 𝐷(𝑡) 𝜂𝑠𝑡𝑜𝑟𝑒𝑑 P(t) – Source Power, D(t) – Load Power
Or 𝑄𝑠 𝑡 + Δ𝑡 = 𝑄𝑠 𝑡 + 𝑡𝑡+Δ𝑡
𝑃 𝑡 − 𝐷(𝑡) 𝜂𝑠𝑡𝑜𝑟𝑒𝑑
❑ For a very small time interval ‘Δt’
𝑄𝑠 𝑡 + Δ𝑡 = 𝑄𝑠 𝑡 + 𝑃 𝑡 − 𝐷(𝑡) 𝜂𝑠𝑡𝑜𝑟𝑒𝑑
❑ Constraints
1)For the entire time horizon, T Qs(t=0) = Qs (t=T)
in order to maintain the days of autonomy condition and hence sustainability of system.
2) Storage charge level Qs(t)≥0 for all time values
3) Generation should not exceed maximum power that can be produced from renewable source during that period.
𝑀𝑖𝑛𝑖𝑚𝑢𝑚 𝑆𝑡𝑜𝑟𝑎𝑔𝑒 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 =max(𝑄𝑠)
𝐷𝑜𝐷
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Modelling of Energy Systems
Quadratic fitting for the boundary
points of the design space of
stand-alone welding shop (a)
Hydrogen storage, (b) VRLA
battery and (c) Supercapacitor
0.000
0.001
0.002
0.003
0.004
PV size
7.5
(t
=1ye
ar)
1
(t=0
)3
(t
=15
min
ute
s)
5
(t=1
day
)
tim
e (i
n lo
g sc
ale
) 0
10
20
30
Feasible regionInfeasible
region
Energ
y
cumulative generation
cumulative load
mismatch
Sho
rt-t
erm
Dat
a in
se
con
d
Mid
-ter
m
Dat
a in
ho
ur
Lon
g-te
rm
Dat
a in
wee
k
P1 P2
S1
M1
L1
S2
M2
Energ
y
Time
Design Space for hybrid energy storage (kWh)Pinch for ‘P1’ PV size
Pinch Point
Pinch Point
Pinch Point
Infeasibleregion
0.6
0.7
0.8
0.9
Infeasible
region
Feasible region
Energ
y
Feasible region
DESE-IIT Bombay Rangan Banerjee 76
COE (₹/kWh) for the different configurations of remote rural
village case study (a) using present cost (b) using US DOE
target cost for hydrogen storage
Case
Study
Optimum ConfigurationCOE
(₹/kWh)PV
(kWp)
Fuel Cell
(kW)
Electrolyse
r (kW)
Hydrogen tank
(m3)
VRLA battery
(kWh)
Supercapacit
or (Wh)
Case 1 –
Rural
Village
65 12 65 12.3 165 - 35
Case 2 –
Telecom
tower
40 6 40 5.2 58 - 33
Case 3 –
Welding
Shop
2 0.32 2 0.27 0.78 3.5 24
Case 4 –
Backup
for lift
1 - - - 2.7 69 30
77
Building Energy Simulation and Model Prediction for real-time control
Summary
• New Buildings stock – green, passive, net zero buildings – potential to transform cities
• Increased Renewable share
• Performance Metrics –buildings, areas, city
• Level playing field for Efficiency and DSM, Demand response
• Intelligence – forecasting supply and demand variability – scheduling, deferring loads, bringing storage on line
• Building modelling,optimization, Smart Buildings
• Transform housing and energy sector
• Need for innovation, research , technology development
78
End-Note
http://www.ubmfuturecities.com/document.asp?doc_id=523792
79
References
• Pillai and Banerjee, Methodology for estimation of potential for solar water heating in a target area, Solar Energy, 81,
pp. 162-172, 2006.
• UNEP,2011: Cities Investing in energy and resource efficiency, Towards a Green Economy, United Nations
Environment Programme, 2011.
• UN Habitat 2013: State of World’s Cities 2012-13 Prosperity of cities, United Nations Human Settlements
Programme (UN-Habitat), Kenya, 2013. < www.unhabitat.org> last accessed October 28, 2013.
• S.Guttikunda and P.Jawahar, 2011, Shakti Foundation
http://shaktifoundation.in/wp-content/uploads/2017/06/Urban-Air-Pollution-Analysis-in- India.pdf
• ICLEI, Agra Solar City Master Plan, 2011: Development of Agra Solar City, Final Master Plan, supported by MNRE,
New Delhi, ICLEI, South Asia.
• Reddy and Balachandra, IGIDR, WP-2010-023, Working Paper,2010.
• Reddy, IGIDR, WP-2013-02, Working Paper,2013.
• Singh, R., and Banerjee, R., Estimation of rooftop solar photovoltaic potential of a city, Solar Energy, Vol. 115, 589-
602, May 2015.
• https://www.nrdc.org/issues/prepare-india-extreme-heat
Thank [email protected]
Acknowledgement: Balkrishna Surve,Brijesh Pandey, Rhythm Singh, Jay Dhariwal,Ammu Jacob, Team Shunya
80