The document is a building energy simulation report that analyzes the energy performance of a single-storey commercial building in Waterloo, Ontario. It summarizes the baseline energy consumption and costs, and runs simulations varying the roof insulation, lighting power density, and heating efficiency. Increasing the heating efficiency to 95% reduced annual natural gas costs by $111 and GHG emissions by 15%. Reducing the lighting power density to code standards cut electricity costs by $322 and GHG emissions by up to 8.5% annually. The report recommends energy efficiency upgrades to lower energy use and utility bills.

1. Simulation Project
Report
Prepared by Asad Ullah Malik and Xiaoyi Wang
Building Science Experts 7/20/19 Building Energy Analysis

2. 1
Table of Contents
1.0 Motivation & Introduction 4
2.0 The Preparation to Apply eQUEST Model 4
3.0 Simulation Reports for baseline design 7
3.1 Annual Energy Performance 8
3.2 Benchmarking 9
4.0 Simulation Experiments of Variables Control 10
5.0 Trends & Validation 11
5.1 GHG impact 13
6.0 Recommendations 15
References 17
Appendix 18
1.1 Effective R-value calculation for the walls and the roof for Baseline Simulation 19
1.2 Comparison of Annual Energy consumption by end-use among simulations 20
2.0 Building Discretions 22

3. 2
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4. 3
July 20th
, 2019
David Mathew
ERC 3013, 200 University Avenue West
Waterloo, ON N2L 3G1
Dear Prof,
Please enclosed the Building Energy Simulation Report for a single storey commercial building
located in Waterloo, ON. The simulation evaluates and analyses the current energy consumption
of the commercial building and recommends energy saving measures by analysing ASHRAE
Standard 90.1-2016 Energy Standard for Buildings’ regulations and comparing it with the energy
consumption of the same building after certain proposed changes are made.
The details in this report are based on the comparison between the baseline analysis of the building
with various other parametric analysis. We have developed a holistic approach to identifying and
recommending energy conservation measures. Through out the report various hyperlinks referring
to the online websites or to other pages inside the report have been added for faster navigation
inside the document and for a better pictorial understanding of the physical phenomenon described.
Our team has brought the expertise from Saudi Arabia, China and Pakistan which has significantly
contributed to the efficacy of the simulation.
We are certain that our report satisfies your requirements.
Sincerely,
Asad Ullah Malik Xiaoyi Wang
Building Science Expert Lead Simulator
222-868-8935 647-685-5878
aumalik@uwaterloo.ca xiaoyi.wang@uwaterloo.ca

5. 4
1.0 Motivation & Introduction
The energy shortage crisis and the rapid change of global climate have become important issues
in the world now a days since modern trends are shifting to more sustainable solutions to save
energy and to reduce the emission of carbon dioxide. Generally speaking, when improving energy
efficiency and adopting the energy –saving design, the advantage is not only providing low
operating cost for stakeholders, but also reducing the negative impact on the global and ambient
environment. This study analyzes the surveyed building integral energy consumption, evaluates
its energy performance, and gives further recommendations for saving energy costs by using
dynamic energy simulation tool eQuest.
Building performance simulation (BPS) is the replication of aspects of building performance using
a computer-based, mathematical model created on the basis of fundamental physical principles
and sound engineering practice. The objective of building performance simulation is the
quantification of aspects of building performance which are relevant to the design, construction,
operation and control of buildings. Building performance simulation has various sub-domains;
most prominent are thermal simulation, lighting simulation, acoustical simulation and air flow
simulation. (Wikipedia Contributors, 2019). Due to the scope and flexibility of its input, eQuest
can implement dynamic calculation method for calculating building energy consumption and
influencing factors of various components, and thus be used in many applications.
The simulation was performed keeping in view that the indoor temperature has to be maintained
at 24.4 ºC while the building is occupied and at 27.8 ºC when it is unoccupied during summers. In
winters it is simulated that the temperature should be at 21.1 ºC and at 17.8 ºC while it is occupied
and unoccupied respectively.
2.0 The Preparation to Apply eQUEST Model
EQUEST calculates hour-by-hour building energy consumption over and entire year (8760 hours)
using hourly weather data for the location under consideration. The input parameters consist of
detailed description of the building, hourly scheduling of occupants, lighting, equipment and
thermostat settings. It provides accurate simulation of building features, such as shading,
fenestration, interior building mass, envelope building mass and dynamic response of different
heating and air conditioning systems and controls. (Hirsch, 2004)
The simulation process begins with developing a virtual model of the building based on
architecture plan. In this study, the details information of the surveyed building is provided.
Alternative analyses are made by changing the parameters of model that could be implemented in
the building. Data required in eQuest is summarized as shown in Table XX, which illustrates the
data should be collected prior to developing simulation of confirmed in the course of modeling.

6. 5
Figure 1 Interdepartmental Contribution Matrix (Hirsch, 2004)
• Analysis Objective
Clearly understand the design questions that wish to answer by using simulation model. In
this study, the owners are interested in having a preliminary study performed to assess the
potential energy performance impacts of certain characteristics of the design, aiming at an
economic and effective improvement on energy performance.

7. 6
• Building Site and Weather Data
The building to be studied is a hypothetical new small office building to be constructed in
Waterloo, Ontario. Weather data are downloaded from the eQUEST database.
• Building Shell, Structure, Materials and Shades
eQUEST analyzes walls, roof, and floors of the building in heat transfer and storage effects.
Overall floor area 2700 square feet with one storey. Other architectural details are shown
below:
1. Floor shall be concrete slab on grade. Interior finish will be carpet.
2. Roof type: Shall be flat.
3. Windows: Double-glazed. Frames are aluminum with thermal break. The Overall
window-to-wall ratio is 35%.
4. Interior celling: No suspended ceiling. Floor to ceiling height = 11ft.
Figure 2 Top View of the Building
• Building Operations and Scheduling
A clear understanding of the schedule of operation of the existing building is important to
the overall accuracy of simulation model. This includes information about when building
occupancy begins and ends, and internal equipment operations schedules. The building is
open from Monday to Friday, and its business hours are approximately from 7 am to 6 pm.
The HVAC system starts running 1 hour before occupancy and shuts down 1 hour after the
business time.
• Internal Loads
Heat gain from internal loads (occupants, lights and equipment) can constitute a significant
portion of the utility requirements in buildings. The surveyed building has a peak
occupancy of about 12 people, providing overhead lighting system with a maximum overall
lighting power density (LPD) of 1.0W/ft2
. For plug loads, the estimated peak load is 0.5
W/ft2
, estimated operating average during business hours is 0.25W/ft2
.

8. 7
• HVAC System
The specifications of HVAC systems are detailed below:
1. During regular business hours, the space shall be fully heated and cooled to
typical comfort conditions.
2. Equips with a single roof-top unit. Overhead ducted air distribution. Natural gas
heating with electric “DX” cooling. Preliminary estimate for supply-fan total-
static-pressure = 2.0 in w.g.
3. Minimum outdoor air intake rate on RTU’s based on 25 cfm/person.
4. Cooling efficiency = 8.5, baseline heating efficiency = 8.0
• Economic
The utility rates are provided to calculate and analyze the annual energy costs:
Electricity = $0.13/kWh; Natural Gas= $0.25/m3
(≈ $0.698/therm)
Besides the key characteristics mentioned above, all of the building descriptions set for the baseline
design are concluded in the project files. After finishing creating a building description in eQuest,
a simulation could be automatically done.
3.0 Simulation Reports for baseline design
After all of the simulations have completed, the designer can visualize the results and reports
through graphical formats, including an exterior 3D view of the simulated building (Figure 3), and
reports for annual or monthly energy consumption and costs.
Figure 3 Exterior 3D view of the building

9. 8
3.1 Annual Energy Performance
Table 1 Annual Energy Consumption by End-use (Baseline)
Electricity Natural Gas Steam Chilled Water
kWh MBtu Btu Btu
Space Cool 4,638 0 0 0
Heat Reject. 0 0 0 0
Refrigeration 0 0 0 0
Space Heat 0 100.19 0 0
HP Supp. 0 0 0 0
Hot Water 0 4.73 0 0
Vent. Fans 7,157 0 0 0
Pumps & Aux. 260 0 0 0
Ext. Usage 0 0 0 0
Misc. Equip. 6,159 0 0 0
Task Lights 0 0 0 0
Area Lights 10,880 0 0 0
Total 29,094 104.92 0 0
Figure 4 Annual Energy Consumption by End-use (Baseline)

10. 9
As shown in the Table 1 and Figure 4, the simulated baseline design consumes 29.094 kWh
electricity for lighting, ventilation, HVAC mechanisms space cooling and others, while 104.92
kbtu natural gas is used for space heating and water heating.
Figure 5 Annual Utility Bills (Baseline)
The utility bills for energy charge the owner for $4514 per year, when the electricity costs accounts
for the majority of the spends. Given the area lighting have a percentage of 37% among electricity
consumption, and 95% of the natural gas is burned to heat up the space, it can be projected that
reducing the lighting power density and heat load can significantly reduce the energy costs.
3.2 Benchmarking
After converting the electricity and natural gas consumption into one unit, the surveyed building
tends to have an annual total site energy use of 74.6 kbtu/sqft (Detailed in Appendix) under the
baseline conditions. By comparing to the benchmarks provided by the US EPA’s “EnergyStar for
Buildings: Target Finder” tool, the Site energy use intensity (EUI) is ranked above the 75th
percentile.
Figure 6 Annual Site EUI benchmarks

11. 10
4.0 Simulation Experiments of Variables Control
To have a further understanding of how parameters independently affects the building performance
on annual energy cost and annual GHG emissions, series of simulations are carried on examining
the difference between baseline design and experimental groups. This study the following three
building parameters as the variables:
1. Roof R-value.
The insulation value should have the impact on space heating. The higher the value is, the
temperature difference between indoor and outdoor is smaller, hence effectively
preventing the unnecessary heat transfer through building roof.
2. Lighting Power Density.
LPD has a noticeable impact on electricity consumption.
3. Heating Efficiency
Improving heating efficiency carries reduction on gas use for certain heat load.
Table 2 displays how each parameter varies in ten simulations. It should be noted that all the other
building characteristics and conditions, despite of selected variables, are identical among the
simulations.
Table 2 Various Parameters for Each Simulation
Simulation
No.
Roof R-value Lighting Power Density Heating Efficiency
W/ft2 EER
1 (Baseline)
No exterior
insulation
1.00 0.8
2 R-12 1.00 0.8
3 R-24 1.00 0.8
4 R-36 1.00 0.8
5
No exterior
insulation
0.90 0.8
6
No exterior
insulation
0.85 0.8
7
No exterior
insulation
0.79 0.8
8
No exterior
insulation
1.00 0.85
9
No exterior
insulation
1.00 0.9
10
No exterior
insulation
1.00 0.95

12. 11
5.0 Trends & Validation
Figure 7 Monthly Energy Consumption (Baseline)
From the report of monthly energy consumption by end-use, the graphs indicate significant
variation according to seasons and weather for both electricity and natural gas usage. Between
May and October, the cooling system operates, hence causes the electricity costs to grow.
Electricity consumption peaks during the hottest July. Meanwhile, gas consumption increases in
the cooler weather due to heavier heat load. Based on these trends, the simulation result for baseline
design could be considered reasonable.
Figure 8 Total Site Energy
66 68 70 72 74 76 78
1
2
3
4
5
6
7
8
9
10
Total Site Energy (kBTU/ft2/yr)
Simulations
Annual Total Site Energy by Simulations

13. 12
It can be deduced from the simulation results that the least Total Site Energy was seen during the
last simulation when the Heating efficiency of the furnace was increased to 95%. Whereas the
maximum Total Site Energy was observed during the baseline year.
Figure 9 Cost comparison of Natural Gas vs Electricity
Graph in Figure 9 was generated through data generated by eQuest Simulations shows that the
increasing the furnace efficiency to 95%, the annual natural gas cost was reduced, leading to an
annual savings of $111.
It also shows that by reducing the Lighting Power Density to ASHRAE Standard 90.1-2016 Energy
Standard for Buildings’ regulations for Office buildings, annual savings of approximately $322 in
the Electricity costs was observed.
However, an interesting trend was observed in the Natural Gas cost which rose for Simulation 5,6
and 7 where the Lighting Power density (LPD) was reduced. This was probably due to the fact that
since the LPD was reduced less heat was generated by the Lights in the building and that gap was
filled by the furnace. Consequently, to maintain comfortable temperature in the building the
furnace had to run more and consume more natural gas, thereby increasing the cost of natural gas
by $28 annually. This cost though may be insignificant but has an interesting reasoning behind it.
733
716
705
698
747
754
761
691
655
622
3782.22
3751.67
3743.22
3738.93
3621.67
3540.94
3460.6
3782.22
3782.22
3782.22
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
1 2 3 4 5 6 7 8 9 10
Cost($)
Simulations
Annual Cost Effectiveness Comparison of Simulations
Natural Gas Cost Electrcity Cost

14. 13
Figure 10 Annual Natural Gas Consumption vs Electricity Consumption plotted on Log
scale for better visual clarity.
5.1 GHG impact
Given the GHG emissions factors，the GHG impact due to energy used by the design building
can be calculated. During the baseline one-year period, the usage of 1049.2 therm natural gas emits
approximately 5560.76 kg of eCO2 to the atmosphere, while 26,184 kg of eCO2 was let out due to
the consumption of 29,094 kWh electricity.
From an environmental aspect, GHG emissions generated by Natural gas were significantly
reduced by increasing the efficiency of the furnace. Simulation # 10 in Figure 11 seconds the
aforementioned trend and shows a 15% reduction in GHG emissions when the furnace efficiency
was increased to 95%. It is to be noted that high efficiency furnaces are now commercially
available in the market either for commercial or domestic use.
Figure 12 shows that by reducing the Lighting Power Density to 0.78965 W/ft2
for simulation 7,
the GHG emissions due to Electricity Consumption saw an 8.5% decrease annually. Similarly, by
reducing the Lighting Power Density from 1W/ft2
to 0.808 W/ft2
, 6.4% decrease in GHG emissions
from Electricity Consumption was recorded.
1
10
100
1,000
10,000
100,000
1 2 3 4 5 6 7 8 9 10
LogrithmicScale
Simulations
Comparison of Annual Energy Consumptions for the
performed Simulations
Electricity Consumption (kWh) Natural Gas Consumtion (MBTu)

15. 14
Figure 11 Comparison of GHG emissions by Simulation based on data from eQuest
Figure 12 Annual GHG emissions from Electricity Consumption observed during all the
simulations plotted for comparison
5562
5436
5353 5299
5670 5727 5780
5250
4972
4723
4000
4200
4400
4600
4800
5000
5200
5400
5600
5800
6000
1 2 3 4 5 6 7 8 9 10
GHGEmissions(kgeCO2/therm)
Simulation
Annual GHG Emissions from Natural Gas by Simulation
26185
25973
25915
25885
25073
24514
23958
26185
26185
26185
22500
23000
23500
24000
24500
25000
25500
26000
26500
1 2 3 4 5 6 7 8 9 10
GHGEmissions(kgeCO2/kWh)
Simulation
Annual GHG Emissions from Electricity by Simulations

16. 15
Increasing the exterior roof insulation did decrease the GHG emissions of Electricity and Natural
Gas. However, economically, it is predicted not to bring any significant savings to the building
owner. Calculations show that the owner will save $67/yr in simulation # 3 by using R-36
insulation on the exterior of the roof which doesn’t justify the extra cost of the insulation and the
ROR isn’t buyer feasible. Further work in this direction can be to test additional insulation in walls
(either exterior or interior) and reducing the sizes of windows along the sun facings walls.
6.0 Recommendations
1) Steel framing vs Wood Framing:
The current building was simulated with metal framing as the main load bearing element
of the commercial building. However, it is an established fact that these steel framing
elements act as thermal bridges in the walls and the roof and diminish the effectiveness of
the thermal barrier (Overbey, 2017).
According to ASHRAE, a layer of R-19 batt insulation is reduced by a staggering 63
percent to an effective R-7.1 when 2x6 metal studs are spaced at 16 inches-on-center.
Wood framing also induces thermal bridging, but it is not as bad a metal stud. Although
less conductive than steel, wood will still diminish the effective R-value of batt insulation
somewhere between 14 - 18 percent. (Overbey, 2017)
Figure 13 When used as infill in a 2x6 metal framed wall (assuming studs at 16 inches-on-
center), the effectiveness of rated R-19 batt insulation may be reduced by a staggering 63
percent. (Illustration by Daniel Overbey)
Figure 14 By comparison, when 2x6 wood studs are utilized, rated R-19 batt insulation may
only be reduced by about 16 percent. (Illustration by Daniel Overbey)

17. 16
2) Continuity in Insulation:
An important conclusion to draw here is that continuous insulation is critically important -
especially where metal framing is utilized. Continuous insulation can be achieved by
providing insulation on the exterior rather than on the interior side. Having insulation on
the exterior side enables it to have fewer thermal breaks like framing members.
3) Reduce Lightning Efficiency
As discussed above in section 5.0, although by reducing the Lighting Power density the
electricity cost, consumption and GHG emissions go down but at the natural gas cost,
consumption and GHG emissions go up. However, the benefit of this trade off exceeds the
cons as the building owners gets to save more money than he/she loses i.e. annual savings
of $322 vs annual increase of $28.
4) Increase Heating Efficiency of the Furnace.
Increasing the heating efficiency of the Furnace has no effect on the electricity cost,
consumption or GHG emissions. However, it reduces the cost of Natural Gas by $111 in
addition to reduction in Natural Gas’s consumption and GHG emissions.

18. 17
References
1. Wikipedia Contributors. (2019, July 2). Building performance simulation. Retrieved July
20, 2019, from Wikipedia website:
https://en.wikipedia.org/wiki/Building_performance_simulation
2. CertainTeed Corporation. (n.d.). Sustainable Insulation ® FTC Fact Sheet (p. 1).
Retrieved from https://www.certainteed.com/resources/30-29-179.pdf
3. Overbey, D. (2017). Comparing Continuous Insulation R-Values in Steel vs. Wood
Framing | SBC Magazine. Retrieved July 20, 2019, from Sbcmag.info website:
https://www.sbcmag.info/news/2017/jun/comparing-continuous-insulation-r-values-steel-
vs-wood-framing
4. Hirsch, J. J. (2004). Energy Simulation Training for Design & Construction
Professionals. Retrieved from:
http://doe2.com/download/equest/eQuestTrainingWorkbook.pdf.
5. Mather, D. (2019). Simulation Project – Simulation Project Instructions [PDF]. Waterloo.

19. 18
Appendix

20. 19
1.1 Effective R-value calculation for the walls and the roof for Baseline
Simulation

21. 20
1.2 Comparison of Annual Energy consumption by end-use among
simulations
Figure 16 Annual Electricity Consumption with GHG emissions calculation
Figure 15 Annual Natural Gas Consumption with calculation of GHG emissions
Electricity Electricity Electricity Electricity Electricity Electricity Electricity Electricity Electricity Electricity
kWh kWh kWh kWh kWh kWh kWh kWh kWh kWh
Space Cool 4,638 4,576 4,565 4,559 4,566 4,528 4,492 4,638 4,638 4,638
Heat Reject. 0 0 0 0 0 0 0 0 0 0
Refrigeration 0 0 0 0 0 0 0 0 0 0
Space Heat 0 0 0 0 0 0 0 0 0 0
HP Supp. 0 0 0 0 0 0 0 0 0 0
Hot Water 0 0 0 0 0 0 0 0 0 0
Vent. Fans 7,157 6,984 6,930 6,903 7,081 7,043 7,005 7,157 7,157 7,157
Pumps & Aux. 260 260 260 260 260 260 260 260 260 260
Ext. Usage 0 0 0 0 0 0 0 0 0 0
Misc. Equip. 6,159 6,159 6,159 6,159 6,159 6,159 6,159 6,159 6,159 6,159
Task Lights 0 0 0 0 0 0 0 0 0 0
Area Lights 10,880 10,880 10,880 10,880 9,792 9,248 8,704 10,880 10,880 10,880
Total 29,094 28,859 28,794 28,761 27,859 27,238 26,620 29,094 29,094 29,094
Cost ($) 3782.22 3751.67 3743.22 3738.93 3621.67 3540.94 3460.6 3782.22 3782.22 3782.22
GHG Emissions
(kg eCO2/kWh)
26185 26185 2618526185 25973 25915 25885 25073 24514 23958
Simulation#9
Simulation#10
Annual Electrical Energy Consumption by End Use - Comparison
Baseline
(Simulation#1)
Simulation#2
Simulation#3
Simulation#4
Simulation#5
Simulation#6
Simulation#7
Simulation#8
Natural Gas Natural Gas Natural Gas Natural Gas Natural Gas Natural Gas Natural Gas Natural Gas Natural Gas Natural Gas
MBtu MBtu MBtu MBtu MBtu MBtu MBtu MBtu MBtu MBtu
Space Cool 0 0 0 0 0 0 0 0 0 0
Heat Reject. 0 0 0 0 0 0 0 0 0 0
Refrigeration 0 0 0 0 0 0 0 0 0 0
Space Heat 100.19 97.81 96.25 95.222 102.23 103.3 104.3 94.296 89.057 84.370
HP Supp. 0 0 0 0 0 0 0 0 0 0
Hot Water 4.73 4.73 4.73 4.727 4.73 4.73 4.73 4.728 4.728 4.728
Vent. Fans 0 0 0 0 0 0 0 0 0 0
Pumps & Aux. 0 0 0 0 0 0 0 0 0 0
Ext. Usage 0 0 0 0 0 0 0 0 0 0
Misc. Equip. 0 0 0 0 0 0 0 0 0 0
Task Lights 0 0 0 0 0 0 0 0 0 0
Area Lights 0 0 0 0 0 0 0 0 0 0
Total 104.92 102.54 100.98 99.949 106.96 108.03 109.03 99.024 93.785 89.098
Total (therms) 1049.45 1025.65 1010.04 999.73 1069.86 1080.56 1090.56 990.48 938.07 891.19
Cost ($) 733 716 705 698 747 754 761 691 655 622
4723
GHG Emissions
(kg eCO2/therm)
5299 5670 5727 5780 5250 49725562 5436 5353
Simulation#7
Simulation#8
Simulation#9
Simulation#10
Annual Natural Gas Consumption by End Use - Comparison
Baseline
(Simulation#1)
Simulation#2
Simulation#3
Simulation#4
Simulation#5
Simulation#6

22. 21
Total Site Energy
kBTU/ft2
/yr
kBTU/yr 204120 201150 199260 198180 201960 200880 199800 198450 193050 188460
73.5 71.5 69.8
Simulation#8
Simulation#9
75.6 74.5 73.8 73.4 74.8 74.4 74
Annual Site EUI (Energy Use Intensity) - Comparison
Baseline
(Simulation#1)
Simulation#1
Simulation#2
Simulation#3
Simulation#4
Simulation#5
Simulation#6
Simulation#7
Figure 17 Calculation of Total Site Energy for all simulations for comparison with US
EPA's "Energy Star for buildings: "Target Finder"

23. 22
2.0 Building Discretions
Mather, D. (2019)