Emergy Simulation Report by wchang72

Content : Project and Site General Information EPC simulation and parameter assumption EPC monthly Calibration

1-9 10 - 17 18

EPC monthly TECH OPT iteration 1

19 - 35

EPC monthly TECH OPT iteration 2

36 - 43

EPC hourly Calibration

44 - 49

EPC hourly TECH OPT iteration 1

50 - 57

EPC hourly TECH OPT iteration 2

58 - 67

Energy Plus simulation

68 - 71

Energy Plus calibration

72 - 73

Result Compare (E+, EPC, EPC Tech OPT)

74 - 75

IES VE simulation

76 - 81

Result Compare (E+, EPC, EPC Tech OPT, IES VE)

82 - 83

Window stack open study and Comfort Connection( E+, IES)

84 - 92

Perspective View and Optimization for the Building

93 - 97

Building Information

Distance between bldg location and weather station (km) Building Name Terrain class Building total Ventilated volume [m3] Building Height [m]

1.00 Chapin Building Urban / City 2879 9.40

Building schedule (summer activity, academic begin activity)

Site information DM Smith Building (Estimate height: 17.06m) Dept of Mathematics (13.02m)

Power plant (4m)

J. S. Coon Building (11.47m)

Surrounding Buildings: DM Smith Building (Estimate height: 17.06m),Power plant (4m), Dept of Mathematics (13.02m), J. S. Coon Building (11.47m) Surrounding Trees: Near building : highest (16m) *1 Outside the building: highest (19m) *3 Building Use: Zone1: Facility office(small) Zone2: Conference room for tutor(small)

Building nearby photo

Site analysis

Wind Roses(Spring: March to May)

Wind Roses(Summer: Jun to Aug)

Wind Roses(Fall: Sep to Nov)

Wind Roses(Winter: Dec to Feb)

Wind Roses(Yearly)

Wind Roses(Comparison)

Shadow Range analysis

Urban Microclimate -Spatial UTCI

Average yearly chart

Psychrometric Chart

Relative humidity chart

Direct Solar Radiation

Building system asumption Heating and Cooling Plants

HVAC System

Heating System Coefficient of Performance (COP) [KW/KW]

2.40

Cooling System Full Load COP [KW/KW]

4.40

IPLV: 0.67, Seasonal COP: 2.93

Relative COP100: for Relative Load 100%

1.00

Refer to REF sheet

Partial Load COP75 Relative Load 75%

0.85

Refer to REF sheet

Partial Load COP50 Relative Load 50%

0.60

Refer to REF sheet

Partial Load COP25 Relative Load 25%

0.25

Refer to REF sheet

Weighting of 100% Load Weighting of 75% Load Weighting of 50% Load Weighting of 25% Load

0.01 0.42 0.45 0.12

From ARI 550/590 Standard From ARI 550/590 Standard From ARI 550/590 Standard From ARI 550/590 Standard

HVAC system type: (System / Heat distrition by / Cold distribution by / room temp. cntrl) Ventilation and Cooling type Relative Humidity threshold for outside air cooling - upper limit (%) Extra ventilation above fresh air supply (liter/s) Heat recovery type Exhaust air recirculation percentage Building air leakage level (Air flow m3/h per floor area at Q4Pa) Specific fan power [W/(l/s)] Fan flow control factor

36. Direct expansion single split system 1. Mechanical system only; no provision for natural ventilation 75 0.10 No heat recovery No exhaust air recirculation 1.72E-04 1.80 1.00

Pump control for cooling

No pump for cooling

Pump control for heating

No pump for heating

HVAC System assumption: Dual duct system / Water or Water&Air / Air / Yes

(Only used for extra fan energy consumption)

Refer to REF sheet (Infiltration ACH: 0) Average electromotor efficiency: Refer to REF sheet Average control reduction factor: Refer to REF sheet

Zone input Zone Zone1 Zone2 Zone3 Space Name OMED office CSDI Confernece room Gross Floor Area (m2) 344 189 Occupancy (m2/person) 30.00 6.30 Metabolic rate (W/person) 120 120 Appliance (W/m2) 10.00 12.34 Lighting (W/m2) 10.76 14.56 Outdoor Air (liter/s/person) 8.33 8.33 DHW (liter/m2/month) 0.10 0.10

Zone4

Zone1 (Office)

Zone 1 Hour 0-1 1-2 2-3 3-4

Zone2 (Class room)

Small office(Ashre standard) Occ_WD -

Occ_WE

Zone 2

App_WD App_WE Light_WD Light_WE 0.50 0.50 0.18 0.18 0.50 0.50 0.18 0.18 0.50 0.50 0.18 0.18 0.50 0.50 0.18 0.18

Small primary school classroom(Ashre standard)

8-9

0.95

1.00

0.50

0.90

0.18

9-10

0.95

1.00

0.50

0.90

0.18

10-11

1.00

0.50

0.90

0.18

11-12

1.00

0.83

0.50

0.90

0.18

12-13

1.00

0.83

0.50

0.61

0.18

13-14

1.00

0.50

0.61

0.18

14-15

1.00

0.50

0.61

0.18

15-16

1.00

0.50

0.61

0.18

16-17

0.53

0.83

0.50

0.61

0.18

17-18 18-19

0.50 0.50

0.18 0.18

Hour Occ_WD Occ_WE App_WD App_WE Light_WD Light_WE 0-1 0.50 0.50 0.18 0.18 1-2 0.50 0.50 0.18 0.18 2-3 0.50 0.50 0.18 0.18 3-4 0.50 0.50 0.18 0.18 4-5 0.50 0.50 0.18 0.18 5-6 0.50 0.50 0.18 0.18 6-7 0.50 0.50 0.90 0.18 7-8 0.21 0.83 0.50 0.90 0.18 8-9 0.53 0.83 0.50 0.90 0.18 9-10 0.95 0.93 0.50 0.90 0.18 10-11 1.00 1.00 0.50 0.90 0.18 11-12 0.53 1.00 0.50 0.90 0.18 12-13 1.00 1.00 0.50 0.90 0.18 13-14 0.53 0.73 0.50 0.90 0.18 14-15 1.00 1.00 0.50 0.90 0.18 15-16 1.00 1.00 0.50 0.90 0.18 16-17 0.53 0.50 0.50 0.90 0.18 17-18 0.50 0.50 0.18 0.18 18-19 0.50 0.50 0.18 0.18

19-20

0.50

0.18

19-20

0.50

0.18

20-21 21-22 22-23 23-24

0.50 0.50 0.50 0.50

0.18 0.18 0.18 0.18

20-21 21-22 22-23 23-24

0.50 0.50 0.50 0.50

0.18 0.18 0.18 0.18

4-5

0.50

0.18

5-6 6-7 7-8

0.21

0.50 0.50 0.83

0.50 0.50 0.50

0.18 0.18 0.42

0.18 0.18 0.18

Shading Factor Envelope

Oqaque1

Orientation S SE E NE N NW W SW Roof(Hor)

Oqaque2

Area [m2]

Window 1 Area [m2]

224.0 126.2 238.5 126.2 363.1

Window1 Horizon Angle [degree] 45 -

0.23

0.41

0.405

Window1 Window1 Overhang Angle Fin Angle [degree] [degree]

Area [m2] 48.6 29.8 47.6 43.3 -

SRF2 0.15

0.707

SRF: Radiation factor (West/East/ North/ South)

Material number Material Type

Uvalue [W/m2/K] Absorption coefficient Roof1 Roof2 Opaque1 Opaque2 Window1 Window2

50 degree

Emissivity

Solar Transmittance

0.33

0.40

0.46

0.58 2.73

0.70 -

0.92 -

0.45

Brick Cavity Conc Block Plaster

50 degree

Outcome

Heating and Cooling Need

16.00 14.00 12.00 10.00

Heating Need [kWh/m2]

8.00

Cooling Need [kWh/m2]

6.00 4.00 2.00 -

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Delivered Energy 18.00 16.00 14.00 12.00 Monthly Method Energy Delivered [kWh/m2]

10.00 8.00 6.00 4.00 2.00 -

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Qdesign,heat,nd [kWh/m2/yr]

PRIMARY ENERGY Month

Qdesign,cool,nd [kWh/m2/yr]

Edesign,del [kWh/m2/yr]

160

Edesign,p [kWh/m2/yr]

543

CO2design [g/m2/yr]

72,754

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total

Ep [kWh/m2] 43 38 42 42 46 48 54 53 46 42 41 48 543

CO2 EMISSIONS Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total

CO2design [g/m2] 19,723 17,355 19,295 18,909 20,995 21,937 24,649 24,008 20,946 19,049 18,404 21,658 246,929

Calibration[Monthly] Calibration before: 51%

Overall difference during entire year: non-weighted

Delivered Electricity [kWh] 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000 0

Jan

Feb

Mar

Apr

May

Building Utility Data (kWh)

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Nov

Dec

Nov

Dec

Building Simulation Calculations (kWh)

District Cooling [kWh] 30,000 25,000 20,000 15,000 10,000 5,000 0

Jan

Feb

Mar

Apr

May

Building Utility Data (kWh)

Jun

Jul

Aug

Sep

Oct

Building Simulation Calculations (kWh)

District Heating [kWh] 160,000 140,000 120,000 100,000 80,000 60,000 40,000 20,000 0

Jan

Feb

Mar

Apr

May

Building Utility Data (kWh)

Jun

Jul

Aug

Sep

Oct

Building Simulation Calculations (kWh)

Calibration after : 15%

Overall difference during entire year: weighted

Delivered Electricity monthly [kWh] 10,000 8,000 6,000 4,000 2,000 0

Jan

Feb

Mar

Apr

May

Building Utility Data (kWh)

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Building Simulation Calculations (kWh)

District Cooling monthly [kWh] 35,000 30,000 25,000 20,000 15,000 10,000 5,000 0

Jan

Feb

Mar

Apr

May

Building Utility Data (kWh)

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Building Simulation Calculations (kWh)

District Heating [kWh] 30,000 25,000 20,000 15,000 10,000 5,000 0

Jan

Feb

Mar

Apr

May

Building Utility Data (kWh)

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Building Simulation Calculations (kWh)

Calibration details Calibration weight options: Percentage Differences Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Average

Electricity Chilled W. (kWh) (kWh) 0.07 0.09 0.00 0.03 0.02 0.02 0.00 0.00 0.01 0.23 0.23 0.14 0.23 0.21 0.05 0.17 0.02 0.08 0.10 0.47 0.15 0.51 0.00 0.49 7% 20%

Steam (kWh) 0.20 0.54 0.00 1.00 1.00 1.00 1.00 0.40 0.22 0.68 50.44%

Weighted Percentage Differences Gas (kWh)

Weight -

1 1 1 1 0.5 0.5 0.5 0.5 1 1 1 0.5

0% Weight

Electricity Chilled W. (kWh) (kWh) 0.07 0.09 0.00 0.03 0.02 0.02 0.00 0.00 0.00 0.11 0.11 0.07 0.12 0.10 0.02 0.09 0.02 0.08 0.10 0.47 0.15 0.51 0.00 0.24 5% 15% 1 1

Steam (kWh) 0.20 0.54 0.00 1.00 0.50 0.50 1.00 0.40 0.22 0.34 39% 1

Gas (kWh) 0% 0

Weighted month: According to some of the data I got from school’s website, I assumed that the data during student’s holiday is weight less than academic month. Since my building is tutor building, if there are no student have classes there would be any students visit the buildings. Calibration continuous variables: Building air leakage level Appliance(Zone1) Lighting(Zone1) Appliance(Zone2) Lighting(Zone2) WD/WE_Tset_heat (LOWEST) WD/WE_Tset_heat (HIGHEST) WD/WE_Tset_cool (HIGHEST) WD/WE_Tset_cool (LOWEST) Specific fan power

(m3/h)/m2 W/m2 W/m2 W/m2 W/m2 [C]ELSIUS [C]ELSIUS [C]ELSIUS [C]ELSIUS W/(l/s)

C45 G13 G14 H13 H14 G20 G27 I20 I27 C46

0.05 5 8 2 2 15.7 16.7 20.9 18 1

5 13.11 14 13.11 12 21.6 27 31.7 23.4 5

0.0500 13.1100 14.0000 13.1100 12.0000 20.4434 25.6926 20.9238 23.4000 1.0000

Zone input (zone1 and zone2): My building’s zone 1 is facility office. Normally most of the faculties come to the building at 9:00am to 17:00pm. The schedule of zone 1 is constant and all other appliance and lighting are also constant. Zone 2 is students’ tutor conference space. This zone sometimes have a lot of students but sometimes don’t. This the main reason that I separate two zone. Both of them have different conditions. Set point temperature: According to the zone schedule , two zones activity are obviously different. Although the building might own same HVAC system, I will assumed that the set temperature based on ASHERE standard is not correct. The activity of in different zone might affect set temperature . Fan power: Due to the archive, the HVAC system cannot be confirmed by any CAD files. I also assumed the fan power for my variable. Delivered energy might not only affected by heating and cooling COP but also the fan power of HVAC.

Tech Opt [Monthly/Hourly]: Labor cost ATLANTA Architect Fees (per project) $5,125.00 ATLANTA HVAC worker Earnings($/day) $200.00 ATLANTAV PV worker Earnings($/day) $120.00

ATLANTA Top End Construction Worker Earnings($/day) $308.00 ATLANTA Experienced Construction Worker Earnings($/day) $225.00 ATLANTA Starting Construction Worker Earnings($/day) $120.00

Labor cost: According to the information I found on glassdoor, I used the average number in 2018. The normal workers working is 8 hours per day. I multiply the hour and the average money workers earn in Georgia. Each construction will cost 1 or half day. I assumed that 1 dayâ&#x20AC;&#x2122;s working hour is 8 hour. The construction also can be separate into different type of level. The high level work cannot be done by the handy man and some works may need professional workers like HVAC PC etc. These different type of works may also affect the labor cost for each optimization. The other things is that the optimization may need professional architects. I assumed the whole optimization happened the same time. So the whole project only cost one architecture fee. I also assumed that the architects fee also include the construction manager fee and other fee that may cost for policy part. All the number cover in architects fee and that is the main reason I add 1000$ on the architects fee. Min-index 1

Max-index 4

Variable 1

Heat Recovery Machine instlallation Cost Room Recirculation Number Recirculation price (Total) $2,500.00 25

Min-value 0.4

Max-value 5 inf. 0.4: 1.5:

3.00 $280.00

Variable 2.00 cost

Type: Discrete Variable dropdown menu OVERALL REMODEL COST 0.00 Total labor time ESTIMATE (day)

Type: Continuous Variable OVERALL REMODEL COST 462.00 Total labor time ESTIMATE (day) 2.00 18000 0

Material Cast: Material cost also affected by the area tech opt chose. I use each materialâ&#x20AC;&#x2122;s times the whole optimization I want to operate. This number can be per square foot or per window etc. Some construction material like window or infiltration I also add the cost that workers have to tare down the old one. For the other things like the set point temperature I count the number that used by EPC lower 1 temperature cost or higher 1 temperature cost. Ref: https://www.sokanu.com/careers/construction-worker/salary/georgia/#salary-text-section

Tech Opt operate parameter: Optimization 1: Lighting daylighting factor Technology levels

Index

Starting Construction Worker

Cost $

Par.1 C22

Total Cost(Without worker fee)

A 1 - Baseline (NULL) A 2 - Partial sensor (25%) A 3 - Partial sensor (50%) A 4 - Partial sensor (75%) A 5 - Fully autom. sensor

1 2 3 4 5

0.00 375.00 750.00 1125.00 1500.00

A 1 - Baseline (NULL)

0.00

1 0.9 0.6 0.3 0 1

Lighting Sensor install: According to some of the data I got from most daylight sensor shopping website, I came up with the cost about 50$ per sensor. The lighting factor based on the product’s IR radiation numbers. For the parameter A2 the sensor I use it’s IR radiation number is 9.5μm which means These sensors detect the heat (IR radiation of 9.5 μm) from people moving within an area to determine when the space is occupied. So the more sensor the building get the less number of lighting factor will be. The calculation is based on the lighting building have for each room in the building. I have 30 rooms and for A-2 option the sensor in the building will be 7.5=7 sensors. The lighting factor will decrease to 0.9. These calculation based on the IR number times decrease number. Lighting occupancy factor Technology levels

Index

Cost $

Par.1

B 1 - Baseline (NULL) B 2 - Partial sensor (25%) B 3 - Partial sensor (50%) B 4 - Partial sensor (75%)

1 2 3 4

0.00 0.00 0.00 0.00

C23 1 0.9 0.6 0.3

B 5 - Fully autom. sensor

0.00

B 1 - Baseline (NULL)

0.00

Lighting occupancy factor: Based on the sensor I installed in the building, the occupancy factor will stick to the daylighting factor. The sensor will detect people’s occupancy and turn on or turn off the light in the room. The more the sensor building install the less the factor will get. So I assumed that the factor also stick to the lighting factor. For the cost, because the factor comes together. Both of the number will affect each other. Ref: https://goo.gl/SHKQsi https://home.costhelper.com/motion-sensor-lights.html

Optimization 2: Heating and Cooling Plants efficiencies (COPs) Technology levels

Index

HVAC worker

Cost $

Par.1

Total Cost(Without worker fee)

C28

Par.2 C29

D 1 - Baseline HVAC D 2 - HVAC variation 2 D 3 - HVAC variation 3

1 2 3

0.00 10800.00 12436.00

1.46 2.28 4.28

1.54 3.21 4.75

D 4 - HVAC variation 4

14327.00

6.28

5.37

D 1 - Baseline HVAC

0.00

1.46

1.54

HVAC reinstall: For the cooling and heating COP, I go to different brand’s website check each heating and cooling COP. The main cost I used are from the Mitsubishi’s website. The main reason is that it has most suitable system for the building. Since the chanpin building does not have any heat pump and other gas based heating system. For the installation, I count the reinstall fee plus buying the new system’s cost. I combined them together to chase the cost. These may also include the cost which hire more than one HVAC install workers. Optimization 3: Heat recovery type (the inputs for C43 must be equal to dropdown menu) Technology levels

Index

Experienced Construction Worker

Cost $

Par.1 C43

Total Cost(Without worker fee)

No heat recovery

0.00

No heat recovery

Heat exchange plates or pipes (0.65)

6250.00

Heat exchange plates or pipes (0.65)

Two-elements-system (0.6)

5800.00

Two-elements-system (0.6)

Loading cold with airconditioning (0.4)

5300.00

Loading cold with air-conditioning (0.4)

Heat-pipes (0.6)

5700.00

Heat-pipes (0.6)

Slowly rotating or intermittent heat exchangers (0.7)

6960.00

Slowly rotating or intermittent heat exchangers (0.7)

No heat recovery

0.00

No heat recovery

Heat recovery system: In this one I chose the parameter based on different heat pipe system that list on the EPC. The pipe system on the website do not include any install cost. That is the main reason that all the cost include the reinstall and install cost. Last but not least, the cost also have to include the workers’ construction fee, since it was a big construction on the site. Ref: https://goo.gl/7AMbcU https://goo.gl/6yKa1H

Optimization 4: Exhaust air recirculation percentage Technology levels

Index

Cost $

Par.1

Experienced Construction Worker

C44

No exhaust air recirculation

0.00

No exhaust air recirculation

Exhaust air recirculation 20%

3900.00

Exhaust air recirculation 20%

Exhaust air recirculation 40%

5300.00

Exhaust air recirculation 40%

Exhaust air recirculation 60%

6700.00

Exhaust air recirculation 60%

No exhaust air recirculation

0.00

No exhaust air recirculation

Heat Recovery System: Most of the machine I used are from Honeywell. The main reason is that the original one that install in Chapin Building are from Honeywell. I think the building been through one or two optimization. The other reason I used the price from Honeywell is that the cost is the highest one in recover system. These can gave building the cost arrangement that it is flexible to chose cheaper system. Optimization 5: DHW Generation System (inputs for C52 must be equal to dropdown menu) Technology Index levels Starting Construction Worker District 1 Heating (0.9) VR-Boiler 2 (0.61) Gas Boiler, HR3 Boiler (0.75) Co-Generation 4 (0.9) Electric (0.75) Heat Pump (1.4) Steam (0.61) District Heating (0.9)

Cost $

Par.1

Total Cost(Without worker fee)

C52 0.00

District Heating (0.9)

1859.00

VR-Boiler (0.61)

2469.00

Gas Boiler, HR-Boiler (0.75)

10110.00

Co-Generation (0.9)

800.00

Elextic(0.75)

1989.00

Heat Pump (1.4)

1309.00

0.00

Steam (0.61) District Heating (0.9)

DHW system: Based on the option that EPC offer, I go to Homedepot to check each different type the DHW system. Even though the effect that DHW cost is very little in chanpin building. It still has a big connection between this one and solar hot water system. The things I did was connect them together. When techopt chose normal system the solar hot water systemâ&#x20AC;&#x2122;s cost will be eliminated. Ref: http://t.cn/Etlzc1Q https://goo.gl/6yKa1H

Optimization 6: Type of BEM system installed Technology levels Experienced Construction Worker 1: Class D 2: Class C 3: Class B 4: Class A

Index

1: Class D

Cost $

Par.1

Total Cost(Without worker fee)

C54

1 2 3 4

0.00 13195.47 32128.10 43028.70

1 2 3 4

0.00

Building Energy Management System: This is the most difficult part to define. The building energy manage system include many part like the sensor and the software etc. This option I chose the sensor and the softwareâ&#x20AC;&#x2122;s cost. The main reason is that the building is not a very huge building. It dose not need complicated system to run the manage system. The main cost are come from the software and the installation part. This part I assumed the original building does not have nay BEM System. This may decrease the total price. Optimization 7: PV module Surface Area (m2) Technology levels PV Construction Worker Minimum # PV modules Maximum # PV modules

Value

Cost $

Par.1 C58

Par.2

Par.3

Min-value

Max-value

Variable

83.71

0 83.71 PV module area: PV module cost:

2.6 388.11

PV system: I used the module that Sol offer on his PV design excel file. The one I chose is the based on Solâ&#x20AC;&#x2122;s recommendation which is 72 cell PV module and flat roof. The other reason is the tree around the building are very tall and huge the only place that is efficient to PV is the flat roof place. Ref: http://t.cn/Etlzc1Q https://goo.gl/6yKa1H

Optimization 8: Lighting ZONE1 (W/m2) Technology levels Starting Construction Worker 100% CFL

Index 1

Cost $ Total Cost(Without worker fee)

0.00

LED and CFL combo (50% LED)

7245.00

LED

8050.00

Fluorescent lamp t5

6670.00

Fluorescent lamp t8

6900.00

Fluorescent lamp t12

7360.00

100% CFL

0.00

Lighting ZONE2 (W/m2) Technology levels Starting Construction Worker 100% CFL

Index 1

Cost $ Total Cost(Without worker fee)

Par.1 G13 5.10 2.21 2.07 2.27 2.67

3780.00

LED

4200.00

Fluorescent lamp t5

3480.00

Fluorescent lamp t8

3600.00

Fluorescent lamp t12

3840.00

100% CFL

0.00

Par.1 G14

0.00

LED and CFL combo

2.05 2.10 1.97 2.16 2.54

Lighting for Zone1 and 2 : This section I go through Amazon, Homedepot, 1000Bulds to look for answer. The option I chose not only from LED but also tradition T5,T8 T12, lighting. The main reason is that the zone might have some trade off to make it cheaper than using LED. The different zone have its different lighting condition. That also may affected the use if the lighting. Ref: https://www.homedepot.com/ http://t.cn/EtlL6cv

Optimization 9: Roof Improvement Technology levels Experienced Construction Worker Roof Baseline 1 Roof Improvement 2.0 mm( new insulationEX Membrane) Roof Improvement 1.8 mm( new insulation EX Membrane) Roof Improvement 1.6 mm( new insulation EX Membrane) Roof Improvement 1.2 mm( new insulation EX Membrane) Roof Baseline 1

Index

Cost $

Par.1

Par.2

Total Cost(Without worker fee)

G64

H64

Par.3 I64

0.00

0.6

0.54

0.9

43572.00

0.45

0.6

0.9

68989.00

0.3

0.6

0.9

79882.00

0.2

0.6

0.9

94406.00

0.13

0.6

0.9

0.00

0.6

0.54

0.9

Wall improvement Technology levels Starting Construction Worker Wall Baseline 1 Wall Improvement 2 (R38 insulation) Wall Improvement 3 (R30 insulation) Wall Improvement 3 (R21 insulation) Wall Improvement 4 (R19 insulation) Wall Improvement 5 (R13 insulation) Wall Improvement 6 (R11 insulation) Wall Baseline 1

Index

Cost $

Par.1

Par.2

Total Cost(Without worker fee)

G66

H66

Par.3 I66

0.00

1.72

0.42

0.62

13761.83

1.7

0.4

0.62

15102.26

1.69

0.38

0.62

18229.95

1.67

0.35

0.62

21849.13

1.65

0.33

0.62

24172.56

1.63

0.32

0.62

27032.16

1.6

0.3

0.62

0.00

1.72

0.42

0.62

Construction for optimization: Infiltration in different area I chose to renew the infiltration, instead of changing the whole material . The main reason for that is to make the optimization doable. The roof and the wall I chose different kind of infiltration which have different U value. I minus the original one and than add new infiltration to the opaque and roof. These also cost the workers to tare down old one and install new to the wall.

Ref: https://www.acehardware.com/ http://t.cn/EtlL6cv

Optimization 10: Window Replacement Technology levels Starting Construction Worker

Index

Window Baseline 1 Double Glz: 6mm air Double Glz (Uncoated CLR CLR):3mm/12mm air (SHGC:0.66) Double Glz: 6mm argon Double Glz (e=0.40 surface2 or 3):12mm argon Triple Glz: 12mm argon Quadruple Glz (e=0.10):12mm argon Window Baseline 1 North window ratio Technology levels Starting Construction Worker Minimize Maximum Ratio

Index

Cost $

Par.1

Par.2

Par.3

Min-index

Total Cost(Without worker fee)

G68

I68

J68

1 WINDOW BUYING 0.53 COST(PER WINDOW)

0.00

5.91

21900.00

2.16

0.4

0.6

165

24300.00

2.27

0.8

0.2

205

25200.00

1.77

0.69

0.31

220

25800.00

1.99

0.51

0.49

230

31800.00

1.65

0.59

0.41

330

36000.00

0.68

0.8

0.2

400

0.00

5.91

0.53

Cost $

Par.1

Total Cost(Without worker fee)

S54

Par.2

Par.3

Min-index

Max-index

Variable

0.1

0.8

0.2

Total Glazing Area

Average Window Area

0.1 0.8

Tare down window NUMBER(per window)

0 2.78 Average Window Average Window Area install Area install cost Put up window cost (Tare (Tare or intall) PER NUMBER(per window) PLUS intall) WINDOW PER WINDOW $240.00 $390.00 0 Type Window Use Window Type($) Cost(Total) 0 0

166.70

0.00

0.2

Building Window Opt: This part I chose to change window. Not only changing the glazing but also changing the ratio of each face. I add on a new cell in tech opt that can count each window ratio. According to the cell, the average add on window area is 2,78 square meter. The ratio cell and window U value cell also connect to each other. When the cell change the other one will change. This can make the window part more accurate.

Optimization 11: Set point Heat Temp Technology levels

Index

Minimize delta T

-9

Maximum delta T

Cost $

Par.1

Par.2

Par.3

K20

Min-index

Max-index

-9

Average Winter Temp 11

Set point Cool Temp Technology levels

Index

Minimize delta T Maximum delta T

Cost $

Average Summer Temp

Par.1 K22

-9 5

0.00

Building Temperature Set-point Schedule Hour 0-1 1-2 2-3 3-4 4-5 5-6 6-7 7-8 8-9 9-10 10-11 11-12 12-13 13-14 14-15 15-16 16-17 17-18 18-19 19-20 20-21 21-22 22-23 23-24

WD_Tset_heat 20.4 20.4 20.4 20.4 20.4 20.4 20.4 25.7 25.7 25.7 25.7 25.7 25.7 25.7 25.7 25.7 25.7 25.7 25.7 20.4 20.4 20.4 20.4 20.4

WE_Tset_heat

WD_Tset_c ool 20.4 20.9 20.4 20.9 20.4 20.9 20.4 20.9 20.4 20.9 20.4 20.9 20.4 20.9 20.4 23.4 20.4 23.4 20.4 23.4 20.4 23.4 20.4 23.4 20.4 23.4 20.4 23.4 20.4 23.4 20.4 23.4 20.4 23.4 20.4 23.4 20.4 20.9 20.4 20.4 20.4 20.4 20.4

20.9 20.9 20.9 20.9 20.9

WE_Tset_cool

Delta T( Heat Tset) 20.9 0.0 20.9 Delta T( Cool Tset) 20.9 0.0 20.9 20.9 20.9 20.9 20.9 20.9 20.9 20.9 20.9 20.9 20.9 20.9 20.9 20.9 20.9 20.9 20.9 20.9 20.9 20.9 20.9

Temperature change : I count the set temperature change based on the monthly EPC. The heat set temperature minus 1 the deliver energy will decrease 2 KWH on the other hand if the set point temperature add 1 degree the deliver energy will increase 2 KWH. I use these number multiple the electricity cost and multiple the whole massing area in the building . These number can count the temperature setting in the building. Since it is a big impact on cooling and heating need.

Optimization 12: South Shading-South Overhang Angle Technology levels Index Starting Construction Worker Baseline 1 30 Degree 2 45 Degree 3 60 Degree 4 Baseline

Cost $

Par.1

Total Cost(Without worker fee)

Overhang

South Shading-South Fin Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree Baseline South Shading-South Horizontal Angle Technology levels Index Starting Construction Worker Baseline 1 10 Degree 2 20 Degree 3 30 Degree 4 40 Degree 5 50 Degree 6 60 Degree 7 70 Degree 8 80 Degree 9 Baseline 1

Index 1 2 3 4

0.00 6600.00 7600.00 8120.00

0 30 45 60

0.00

Cost $ Total Cost(Without worker fee)

0.00 13200.00 15200.00 16240.00

Par.1 Fin Angle

0 30 45 60

0.00 Cost $

0 Par.1

Horizontal Angle

Total Cost(Without worker fee) 0.00 6600.00 6760.00 6920.00 7080.00 7240.00 7400.00 7560.00 7700.00 0.00

0 10 20 30 40 50 60 70 80 0

Shading Change: Since everybody know the north south side should use vertical shading and west east side should use horizontal shading. However, the site condition of chaping building is the other shading. The site was surrounding tall building and tall trees. The shading reduction factor is different from face to face. The difference make the shading for each side is very important. According to the reason , I separate each faceâ&#x20AC;&#x2122;s shading condition. The main reason is to let tech opt to help me chose the best shading angle for each side. Last but not least the different shading can built simultaneously this also make the assumption reasonable.

Tech Opt Outcome[Monthly] iteration 1: Iteration 1: The first iteration I tried is Energy saving / Total cost. This iteration I put the number to maximum. These means that in order to accomplish the number I set, Tech Opt will chose the one has less total cost and the max energy saving option. Here is the result I got from Tech Opt. OBJECTIVE FUNCTION (NPC) = Total premium cost + electricity cost $221,665.02

Edesign,del (SAVED) [kWh/m2/yr]

Premium cost of mix of technologies (Plus Labor cost) $40,663.37 460.649171211

PI Qdesign,heat,nd(Opt Before) [kWh/m2/yr] Qdesign,cool,nd(Opt Before) [kWh/m2/yr] Edesign,del (Opt Before) [kWh/m2/yr] Edesign,p (Opt Before) [kWh/m2/yr] CO2design (Opt Before) [g/m2/yr]

From Monthly Calculation

PI Qdesign,heat,nd [kWh/m2/yr] Qdesign,cool,nd [kWh/m2/yr] Edesign,del [kWh/m2/yr] Edesign,p [kWh/m2/yr] CO2design [g/m2/yr]

From Monthly Calculation

PI Qdesign,heat,nd (SAVED) [kWh/m2/yr] Qdesign,cool,nd (SAVED) [kWh/m2/yr] Edesign,del (SAVED) [kWh/m2/yr] Edesign,p (SAVED) [kWh/m2/yr] CO2design (SAVED) [g/m2/yr]

From Monthly Calculation

152 196.736511911047 651 2,209 295,771.184093838

40.737727588407 158.424608774917 190.243597045682 645.686768373044 86,448.301023752900

111.300386366 38.311903136 460.649171211 1,563.443287092 209,322.883070085

Result: Based on the result, the building after operation low down a lot of heating load. The main issue for that I think is the micro climate near Georgia Tech usually do not need that much heating load. The main deliver energy that based on the EPC calibration is heating load. However, this iteration do not have any constrain which means most of the number is over normally operation can do. The main method I solved this problem is using the Energy saving and Total money costâ&#x20AC;&#x2122;s fraction to make it possible to overcome some of the constrain.

Tech Opt Outcome Option[Monthly]: Lighting daylighting factor Technology levels Starting Construction Worker A 1 - Baseline (NULL) A 2 - Partial sensor (25%) A 3 - Partial sensor (50%) A 4 - Partial sensor (75%) A 5 - Fully autom. sensor

Index

Cost $ Total Cost(Without worker fee)

1 2 3 4 5

A 2 - Partial sensor (25%)

0.00 375.00 750.00 1125.00 1500.00

Par.1 C22 1 0.9 0.6 0.3 0

375.00

0.9

Lighting constant illumination control factor Technology levels Experienced Construction Worker C 1 - Baseline (NULL) C 2 - Partial dimmer C 3 - Fully autom. Dimmer C 3 - Fully autom. Dimmer C 3 - Fully autom. Dimmer

Index

Cost $

Par.1 C24

Total Cost(Without worker fee)

C 1 - Baseline (NULL)

1 2

0.00 400.00

1 0.9

800.00

0.6

1200.00

0.3

1600.00

0.00

Heat recovery type (the inputs for C43 must be equal to dropdown menu) Technology levels Experienced Construction Worker No heat recovery Heat exchange plates or pipes (0.65) Two-elementssystem (0.6) Loading cold with airconditioning (0.4) Heat-pipes (0.6) Slowly rotating or intermittent heat exchangers (0.7) Loading cold with airconditioning (0.4)

Index

Cost $

Par.1

Total Cost(Without worker fee)

C43

0.00

No heat recovery

6250.00

Heat exchange plates or pipes (0.65)

5800.00

Two-elements-system (0.6)

5300.00

Loading cold with air-conditioning (0.4)

5700.00

Heat-pipes (0.6)

6960.00

Slowly rotating or intermittent heat exchangers (0.7)

5300.00

Loading cold with air-conditioning (0.4)

Exhaust air recirculation percentage (inputs for C44 must be equal to dropdown menu) Technology levels Experienced Construction Worker No exhaust air recirculation Exhaust air recirculation 20% Exhaust air recirculation 40% Exhaust air recirculation 60% No exhaust air recirculation

Index

Cost $

Par.1 C44

0.00

No exhaust air recirculation

3900.00

Exhaust air recirculation 20%

5300.00

Exhaust air recirculation 40%

6700.00

Exhaust air recirculation 60%

0.00

No exhaust air recirculation

Building air leakage level (Air flow m3/h per floor area at Q4Pa) Technology levels Top End Construction Worker Minimum infiltration Maximum infiltration

Value

Cost $

Par.1 C45

0.4 5

-23096.63

2.91

DHW Generation System (inputs for C52 must be equal to dropdown menu) Technology levels Starting Construction Worker District Heating (0.9) VR-Boiler (0.61) Gas Boiler, HRBoiler (0.75) Co-Generation (0.9)

Index

Cost $

Par.1

Total Cost(Without worker fee)

C52

0.00

District Heating (0.9)

1859.00

VR-Boiler (0.61)

2469.00

Gas Boiler, HR-Boiler (0.75)

10110.00

Co-Generation (0.9)

Electric (0.75)

800.00

Elextic(0.75)

Heat Pump (1.4)

1989.00

Heat Pump (1.4)

Steam (0.61)

1309.00

Steam (0.61)

VR-Boiler (0.61)

1859.00

VR-Boiler (0.61)

Type of BEM system installed Technology levels

Index

Experienced Construction Worker

Cost $

Par.1

Total Cost(Without worker fee)

C54

1: Class D

0.00

2: Class C

13195.47

3: Class B

32128.10

4: Class A

43028.70

2: Class C

13195.47

PV module Surface Area (m2) Technology levels PV Construction Worker Minimum # PV modules Maximum # PV modules

Value

Cost $

Par.1 C58

0 83.71

4269.21 Solar Collector Surface Area (m2) Technology levels PV Construction Worker Minimum # Solar Col. Maximum # Solar Col.

Value

Cost $

28.60 Par.1 C64

0 45.45

0.00

Lighting ZONE1 (W/m2) Technology levels Starting Construction Worker 100% CFL LED and CFL combo (50% LED) LED Fluorescent lamp t5 Fluorescent lamp t8 Fluorescent lamp t12 LED and CFL combo (50% LED)

Index 1 2 3 4 5 6 2

Lighting ZONE2 (W/m2) Technology levels Starting Construction Worker 100% CFL LED and CFL combo LED Fluorescent lamp t5 Fluorescent lamp t8 Fluorescent lamp t12 100% CFL Roof Improvement Technology levels Experienced Construction Worker Roof Baseline 1 Roof Improvement 2.0 mm( new insulationEX Membrane) Roof Improvement 1.8 mm( new insulation EX Membrane) Roof Improvement 1.6 mm( new insulation EX Membrane) Roof Improvement 1.2 mm( new insulation EX Membrane) Roof Baseline 1

Wall improvement Technology levels Starting Construction Worker Wall Baseline 1 Wall Improvement 2 (R-38 insulation) Wall Improvement 3 (R-30 insulation) Wall Improvement 3 (R-21 insulation) Wall Improvement 4 (R-19 insulation) Wall Improvement 5 (R-13 insulation) Wall Improvement 6 (R-11 insulation) Wall Baseline 1 Technology levels Starting Construction Worker Window Baseline 1 Double Glz: 6mm air Double Glz (Uncoated CLR CLR):3mm/12mm air (SHGC:0.66) Double Glz: 6mm argon Double Glz (e=0.40 surface2 or 3):12mm argon Triple Glz: 12mm argon Quadruple Glz (e=0.10):12mm argon Window Baseline 1

Cost $ Total Cost(Without worker fee)

Index

Cost $ Total Cost(Without worker fee)

1 2 3 4 5 6 1

Index

Cost $

Par.1

Par.2

Total Cost(Without worker fee)

G64

H64

0.00 7245.00 8050.00 6670.00 6900.00 7360.00 7245.00

0.00 3780.00 4200.00 3480.00 3600.00 3840.00 0.00

Par.1 G13

14 5.10 2.21 2.07 2.27 2.67 5.103197674

Par.1 G14

12 2.05 2.10 1.97 2.16 2.54 12

Par.3 I64

0.00

0.6

0.54

0.9

43572.00

0.45

0.6

0.9

68989.00

0.3

0.6

0.9

79882.00

0.2

0.6

0.9

94406.00

0.13

0.6

0.9

0.00

0.6

0.54

0.9

Index

Cost $

Par.1

Par.2

Total Cost(Without worker fee)

G66

H66

Par.3 I66

0.00

1.72

0.42

0.62

13761.83

1.7

0.4

0.62

15102.26

1.69

0.38

0.62

18229.95

1.67

0.35

0.62

21849.13

1.65

0.33

0.62

24172.56

1.63

0.32

0.62

27032.16

1.6

0.3

0.62

0.00

1.72

0.42

0.62

Index

Cost $

Par.1

Par.2

Total Cost(Without worker fee)

G68

I68

Par.3 J68

1 2

0.00 21900.00

5.91 2.16

0 0.4

0.53 0.6

24300.00

2.27

0.8

0.2

25200.00

1.77

0.69

0.31

25800.00

1.99

0.51

0.49

31800.00

1.65

0.59

0.41

36000.00

0.68

0.8

0.2

0.00

5.91

0.53

North window ratio Technology levels Starting Construction Worker Minimize Maximum Ratio

Index 0.1 0.8

Cost $ Total Cost(Without worker fee)

Par.1 S54

2060.23 South window ratio Technology levels Starting Construction Worker Minimize Maximum Ratio

Index 0.1 0.8

Cost $ Total Cost(Without worker fee)

0.1

Par.1 S50

2060.23 West window ratio Technology levels Starting Construction Worker Minimize Maximum Ratio

Index 0.1 0.8

Cost $ Total Cost(Without worker fee)

0.1

Par.1 S56

2060.23 East window ratio Technology levels Starting Construction Worker Minimize Maximum Ratio

Index 0.1 0.8

Cost $ Total Cost(Without worker fee)

0.1

Par.1 S52

2060.23 Set point Heat Temp Technology levels Minimize delta T Maximum delta T

Index

Cost $

0.1

Par.1 K20

-9 5

767.40 Technology levels Minimize delta T Maximum delta T

Index

Cost $

-6 Par.1 K22

-9 5

0.00

South Shading-South Overhang Angle Technology levels Index Starting Construction Worker Baseline 1 30 Degree 2 45 Degree 3 60 Degree 4

Baseline

Cost $

Baseline

Index 1 2 3 4

East Shading-South Fin Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree

Baseline East Shading-South Horizontal Angle Technology levels Starting Construction Worker Baseline 10 Degree 20 Degree 30 Degree 40 Degree 50 Degree 60 Degree 70 Degree 80 Degree Baseline

0.00 6600.00 7600.00 8120.00

0 30 45 60

0.00

Cost $ Total Cost(Without worker fee)

0.00 13200.00 15200.00 16240.00

South Shading-South Horizontal Angle Technology levels Index Starting Construction Worker Baseline 1 10 Degree 2 20 Degree 3 30 Degree 4 40 Degree 5 50 Degree 6 60 Degree 7 70 Degree 8 80 Degree 9 Baseline 1

Baseline

Overhang

Total Cost(Without worker fee)

South Shading-South Fin Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree

East Shading-South Overhang Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree

Par.1

Par.1 Fin Angle

0.00

Cost $

Par.1

Total Cost(Without worker fee)

Horizontal Angle 0.00 6600.00 6760.00 6920.00 7080.00 7240.00 7400.00 7560.00 7700.00 0.00

Index 1 2 3 4

Cost $ Total Cost(Without worker fee)

Index 1 2 3 4

1 2 3 4 5 6 7 8 9 1

0 10 20 30 40 50 60 70 80 0

0.00 6600.00 7600.00 8120.00

Par.1 Overhang

0 30 45 60

0.00

Cost $ Total Cost(Without worker fee)

Index

0 30 45 60

0.00 13200.00 15200.00 16240.00

Par.1 Fin Angle

0 30 45 60

0.00

Cost $ Total Cost(Without worker fee)

0.00 6600.00 6760.00 6920.00 7080.00 7240.00 7400.00 7560.00 7700.00 0.00

Par.1 Horizontal Angle

0 10 20 30 40 50 60 70 80 0

Tech Opt Result[Monthly] iteration 1: Tech Opt Heating and Cooling Need difference 45.00 40.00 35.00 30.00

Original Heating Need [kWh/m2]

25.00

Original Cooling Need [kWh/m2] Heating Need [kWh/m2]

20.00

Cooling Need [kWh/m2]

15.00 10.00 5.00 -

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Tech Opt Delivered Energy difference 90.00 80.00 70.00 60.00

Original Monthly Method Energy Delivered [kWh/m2]

50.00

Monthly Method Energy Delivered [kWh/m2]

40.00 30.00 20.00 10.00 -

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Box without window ? Based on the result Tech Opt had chose, it is clear that the window ratio and the set point temperature is the most thing Tech Opt chose. The main reason is that most of the cost about these options are very cheap. The most expensive one is changing window ratio. I think windows options are really a trade of for energy modeling. The more window area building get the more energy cost it will get. However, the less window, the window people feel comfortable in the building. The other things are also very interesting. Lighting also is a big impact for the building. The building especially for building in campus, really need a lot of lighting use. Although changing the lighting into LED may affect the cost, it is also worth to do it. Last but not least, the shading part is really a surprised to me. I think the main reason that Tech Opt do not chose shading is because the SRF number for the whole building. It is not worth to change shading than changing other things.

Tech Opt Outcome[Monthly] iteration2 : Iteration 2: The second iteration I tried is minimum cost and energy saving larger than 30%. This time I set the restriction for the EPC. The restriction I set is the money cost. The money cost must lower than $339,769.09. This number comes from the total GT budget status for renovation in 2018. I divide the whole academic building and got the number. The main purpose for these one is to give tech opt a different view to renovation the building. Not only to make it more efficient but also doable. Energy saving% 70.77%

OBJECTIVE FUNCTION (NPC) = Total premium cost + electricity cost $215,395.33

Edesign,del (SAVED) [kWh/m2/yr]

474.535351149

PI Qdesign,heat,nd(Opt Before) [kWh/m2/yr] Qdesign,cool,nd(Opt Before) [kWh/m2/yr] Edesign,del (Opt Before) [kWh/m2/yr] Edesign,p (Opt Before) [kWh/m2/yr] CO2design (Opt Before) [g/m2/yr]

From Monthly Calculation

PI Qdesign,heat,nd [kWh/m2/yr] Qdesign,cool,nd [kWh/m2/yr] Edesign,del [kWh/m2/yr] Edesign,p [kWh/m2/yr] CO2design [g/m2/yr]

From Monthly Calculation

PI Qdesign,heat,nd (SAVED) [kWh/m2/yr] Qdesign,cool,nd (SAVED) [kWh/m2/yr] Edesign,del (SAVED) [kWh/m2/yr] Edesign,p (SAVED) [kWh/m2/yr] CO2design (SAVED) [g/m2/yr]

From Monthly Calculation

152 196.736511911047 651 2,209 295,771.184093838

26.628280051490 154.134903062374 176.357417107916 598.557073664266 80,138.303305187200

125.409833903 42.601608849 474.535351149 1,610.572981800 215,632.880788651

Result: The result is very surprising. The deliver energy and the cost is even lower than the iteration without restriction. Not only the saving energy is way more higher than 30% but also the total money also lower than before. It is worth to see the result what tech opt had chose.

Tech Opt Outcome Option iteration 2[Monthly]: Lighting daylighting factor Technology levels Starting Construction Worker A 1 - Baseline (NULL) A 2 - Partial sensor (25%) A 3 - Partial sensor (50%) A 4 - Partial sensor (75%) A 5 - Fully autom. sensor

Index

Cost $ Total Cost(Without worker fee)

1 2 3 4 5

A 2 - Partial sensor (25%)

0.00 375.00 750.00 1125.00 1500.00

Par.1 C22 1 0.9 0.6 0.3 0

375.00

0.9

Index

Cost $

Par.1 C24

Total Cost(Without worker fee)

C 1 - Baseline (NULL)

1 2

0.00 400.00

1 0.9

800.00

0.6

1200.00

0.3

1600.00

0.00

Heating and Cooling Plants efficiencies (COPs) Technology levels

Index

HVAC worker D 1 - Baseline HVAC D 2 - HVAC variation 2 D 3 - HVAC variation 3 D 4 - HVAC variation 4

D 3 - HVAC variation 3

Cost $

Par.1

Par.2

Total Cost(Without worker fee)

C28

C29

0.00

1.46

1.54

10800.00

2.28

3.21

12436.00

4.28

4.75

14327.00

6.28

5.37

12436.00

4.28

4.75

Index

Cost $

Par.1

Total Cost(Without worker fee)

C43

0.00

No heat recovery

6250.00

Heat exchange plates or pipes (0.65)

5800.00

Two-elements-system (0.6)

5300.00

Loading cold with air-conditioning (0.4)

5700.00

Heat-pipes (0.6)

6960.00

Slowly rotating or intermittent heat exchangers (0.7)

5300.00

Loading cold with air-conditioning (0.4)

Building air leakage level (Air flow m3/h per floor area at Q4Pa) Technology levels Top End Construction Worker Minimum infiltration Maximum infiltration

Value

Cost $

Par.1 C45

0.4 5

-23096.63

2.91

Index

Cost $

Par.1

Total Cost(Without worker fee)

C52

0.00

District Heating (0.9)

1859.00

VR-Boiler (0.61)

2469.00

Gas Boiler, HR-Boiler (0.75)

10110.00

Co-Generation (0.9)

Electric (0.75)

800.00

Elextic(0.75)

Heat Pump (1.4)

1989.00

Heat Pump (1.4)

Steam (0.61)

1309.00

Steam (0.61)

VR-Boiler (0.61)

1859.00

VR-Boiler (0.61)

Type of BEM system installed Technology levels

Index

Experienced Construction Worker

Cost $

Par.1

Total Cost(Without worker fee)

C54

1: Class D

0.00

2: Class C

13195.47

3: Class B

32128.10

4: Class A

43028.70

2: Class C

13195.47

PV module Surface Area (m2) Technology levels PV Construction Worker Minimum # PV modules Maximum # PV modules

Value

Cost $

Par.1 C58

0 83.71

4269.21 Solar Collector Surface Area (m2) Technology levels PV Construction Worker Minimum # Solar Col. Maximum # Solar Col.

Value

Cost $

28.60 Par.1 C64

0 45.45

0.00

Lighting ZONE1 (W/m2) Technology levels Starting Construction Worker 100% CFL LED and CFL combo (50% LED) LED Fluorescent lamp t5 Fluorescent lamp t8 Fluorescent lamp t12 Fluorescent lamp t5

Index 1 2 3 4 5 6 4

Cost $ Total Cost(Without worker fee)

Index

Cost $ Total Cost(Without worker fee)

1 2 3 4 5 6 1

Index

Cost $

Par.1

Par.2

Total Cost(Without worker fee)

G64

H64

0.00 7245.00 8050.00 6670.00 6900.00 7360.00 6670.00

0.00 3780.00 4200.00 3480.00 3600.00 3840.00 0.00

Par.1 G13

14 5.10 2.21 2.07 2.27 2.67 2.072674419

Par.1 G14

12 2.05 2.10 1.97 2.16 2.54 12

Par.3 I64

0.00

0.6

0.54

0.9

43572.00

0.45

0.6

0.9

68989.00

0.3

0.6

0.9

79882.00

0.2

0.6

0.9

94406.00

0.13

0.6

0.9

0.00

0.6

0.54

0.9

Index

Cost $

Par.1

Par.2

Total Cost(Without worker fee)

G66

H66

Par.3 I66

0.00

1.72

0.42

0.62

13761.83

1.7

0.4

0.62

15102.26

1.69

0.38

0.62

18229.95

1.67

0.35

0.62

21849.13

1.65

0.33

0.62

24172.56

1.63

0.32

0.62

27032.16

1.6

0.3

0.62

0.00

1.72

0.42

0.62

Index

Cost $

Par.1

Par.2

Total Cost(Without worker fee)

G68

I68

Par.3 J68

1 2

0.00 21900.00

5.91 2.16

0 0.4

0.53 0.6

24300.00

2.27

0.8

0.2

25200.00

1.77

0.69

0.31

25800.00

1.99

0.51

0.49

31800.00

1.65

0.59

0.41

36000.00

0.68

0.8

0.2

0.00

5.91

0.53

North window ratio Technology levels Starting Construction Worker Minimize Maximum Ratio

Index 0.1 0.8

Cost $ Total Cost(Without worker fee)

Par.1 S54

2118.56 South window ratio Technology levels Starting Construction Worker Minimize Maximum Ratio

Index 0.1 0.8

Cost $ Total Cost(Without worker fee)

Par.1 S50

2171.57 West window ratio Technology levels Starting Construction Worker Minimize Maximum Ratio

Index 0.1 0.8

Cost $ Total Cost(Without worker fee)

Index 0.1 0.8

Cost $ Total Cost(Without worker fee)

Minimize delta T Maximum delta T

Index

0.105663109

Par.1 S52

2072.24 Set point Heat Temp Technology levels

0.105404377

Par.1 S56

2171.57 East window ratio Technology levels Starting Construction Worker Minimize Maximum Ratio

0.102831148

Cost $

0.100583247

Par.1 K20

-9 5

1023.21 Technology levels Minimize delta T Maximum delta T

Index

Cost $

-8 Par.1 K22

-9 5

0.00

South Shading-South Overhang Angle Technology levels Index Starting Construction Worker Baseline 1 30 Degree 2 45 Degree 3 60 Degree 4

Baseline

Cost $

Baseline

Index 1 2 3 4

East Shading-South Fin Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree

Baseline East Shading-South Horizontal Angle Technology levels Starting Construction Worker Baseline 10 Degree 20 Degree 30 Degree 40 Degree 50 Degree 60 Degree 70 Degree 80 Degree Baseline

0.00 6600.00 7600.00 8120.00

0 30 45 60

0.00

Cost $ Total Cost(Without worker fee)

0.00 13200.00 15200.00 16240.00

Baseline

Overhang

Total Cost(Without worker fee)

South Shading-South Fin Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree

East Shading-South Overhang Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree

Par.1

Par.1 Fin Angle

0.00

Cost $

Par.1

Total Cost(Without worker fee)

Horizontal Angle 0.00 6600.00 6760.00 6920.00 7080.00 7240.00 7400.00 7560.00 7700.00 0.00

Index 1 2 3 4

Cost $ Total Cost(Without worker fee)

Index 1 2 3 4

1 2 3 4 5 6 7 8 9 1

0 10 20 30 40 50 60 70 80 0

0.00 6600.00 7600.00 8120.00

Par.1 Overhang

0 30 45 60

0.00

Cost $ Total Cost(Without worker fee)

Index

0 30 45 60

0.00 13200.00 15200.00 16240.00

Par.1 Fin Angle

0 30 45 60

0.00

Cost $ Total Cost(Without worker fee)

0.00 6600.00 6760.00 6920.00 7080.00 7240.00 7400.00 7560.00 7700.00 0.00

Par.1 Horizontal Angle

0 10 20 30 40 50 60 70 80 0

Tech Opt Result [Monthly] iteration 2:

Tech Opt Heating and Cooling Need difference 45.00 40.00 35.00 30.00

Original Heating Need [kWh/m2]

25.00

Original Cooling Need [kWh/m2] Heating Need [kWh/m2]

20.00

Cooling Need [kWh/m2]

15.00 10.00 5.00 -

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Tech Opt Delivered Energy difference 90.00 80.00 70.00 60.00

Original Monthly Method Energy Delivered [kWh/m2]

50.00

Monthly Method Energy Delivered [kWh/m2]

40.00 30.00 20.00 10.00 -

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Same way to renovation The result shows that the best way to renovate my building is to change the window ratio , lower set point heating temperature, install PV, improve lighting and ventilation. According to the report, the most these thing work the best way for renovation. My building most of the time are covered by tree and tall environment. These is main reason that tech opt do not chose to renovate the shading. The result show that most of the work can be finished by normal people or handy man . It is good to know the result. The result is not only for install more PV. The tech opt gave some choice that is achievable and doable. The most of the thing that cannot be easily achieve is the window ratio. These option may not be a good suggestion for the renovation.

Tech Opt Result iteration 1 and 2 difference[Monthly]: Heating and Cooling Need iteration difference percentage 1.20 Hourly Method Heating Need Percentage Difference (Iteration 1)

1.00 0.80

Hourly Method Cooling Need Percentage Difference (Iteration 1)

0.60

Hourly Method Heating Need Percentage Difference (Iteration 2)

0.40

Hourly Method Cooling Need Percentage Difference (Iteration 2)

0.20 -

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Delivered Energy iteration difference percentage 0.90 0.80 0.70 Hourly Method Energy Delivered Percentage Difference (Interation 1)

0.60 0.50

Hourly Method Energy Delivered Percentage Difference (Iteration2)

0.40 0.30 0.20 0.10 -

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Difference I reconstruct two iteration that can show the whole pros and cons for each of them. The graph shows that for energy part of view they both use the same way to reduce total or increase the saving energy. However, on the other side of view the heating energy are very different. The heating need suppose not to be any of them because of the weather. Based on the iteration2â&#x20AC;&#x2122;s number, during summer time school should lower the heating system. This might cause the reason that the energy for heating is way more different than others.

Calibration[Hourly] Calibration before (Use monthly information after monthly calibration): Overall difference during entire year: non-weighted Overall difference during entire year: weighted

34.59% 28%

District Cooling [kWh] 100 80 60 40 20 0 Building Utility Data (original inputs)

Building Utility Data (kWh)

District Cooling [kWh] 90 80 70 60 50 40 30 20 10 0

000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000 Building Utility Data (original inputs)

Building Utility Data (kWh)

District Heating [kWh] 80 60 40 20 0 Building Utility Data (original inputs)

Building Simulation Calculations (kWh)

70 60 50 40 30 20 10 0

35 30 25 20 15 10 5 0 2017/1/1 上午… 2017/1/11 下… 2017/1/21 下… 2017/1/31 下… 2017/2/10 下… 2017/2/21 上… 2017/3/3 上午… 2017/3/13 下… 2017/3/23 下… 2017/4/2 下午… 2017/4/12 下… 2017/4/23 上… 2017/5/3 上午… 2017/5/13 上… 2017/5/23 上… 2017/6/2 下午… 2017/6/12 下… 2017/6/22 下… 2017/7/2 下午… 2017/7/13 上… 2017/7/23 上… 2017/8/2 上午… 2017/8/12 上… 2017/8/22 下… 2017/9/1 下午… 2017/9/11 下… 2017/9/21 下… 2017/10/2 上… 2017/10/12… 2017/10/22… 2017/11/1 上… 2017/11/11… 2017/11/21… 2017/12/1 下… 2017/12/11… 2017/12/22…

2017/1/1 上… 2017/1/11… 2017/1/21… 2017/1/31… 2017/2/10… 2017/2/21… 2017/3/3 上… 2017/3/13… 2017/3/23… 2017/4/2 下… 2017/4/12… 2017/4/23… 2017/5/3 上… 2017/5/13… 2017/5/23… 2017/6/2 下… 2017/6/12… 2017/6/22… 2017/7/2 下… 2017/7/13… 2017/7/23… 2017/8/2 上… 2017/8/12… 2017/8/22… 2017/9/1 下… 2017/9/11… 2017/9/21… 2017/10/2… 2017/10/12… 2017/10/22… 2017/11/1… 2017/11/11… 2017/11/21… 2017/12/1… 2017/12/11… 2017/12/22…

30 25 20 15 10 5 0

2017/1/1 上午… 2017/1/11 下午… 2017/1/21 下午… 2017/1/31 下午… 2017/2/10 下午… 2017/2/21 上午… 2017/3/3 上午… 2017/3/13 下午… 2017/3/23 下午… 2017/4/2 下午… 2017/4/12 下午… 2017/4/23 上午… 2017/5/3 上午… 2017/5/13 上午… 2017/5/23 上午… 2017/6/2 下午… 2017/6/12 下午… 2017/6/22 下午… 2017/7/2 下午… 2017/7/13 上午… 2017/7/23 上午… 2017/8/2 上午… 2017/8/12 上午… 2017/8/22 下午… 2017/9/1 下午… 2017/9/11 下午… 2017/9/21 下午… 2017/10/2 上午… 2017/10/12 上… 2017/10/22 上… 2017/11/1 上午… 2017/11/11 下… 2017/11/21 下… 2017/12/1 下午… 2017/12/11 下… 2017/12/22 上…

Calibration after : Overall difference during entire year: non-weighted Overall difference during entire year: weighted

Building Utility Data (original inputs)

25.28% 19%

Delivered Electricity [kWh]

Building Simulation Calculations (kWh)

District Cooling [kWh]

Building Simulation Calculations (kWh)

District Heating [kWh]

Building Simulation Calculations (kWh)

Hourly Calibration details Calibration weight options: Percentage Differences Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Average

Electricity Chilled W. (kWh) (kWh) 0.07 0.09 0.00 0.03 0.02 0.02 0.00 0.00 0.01 0.23 0.23 0.14 0.23 0.21 0.05 0.17 0.02 0.08 0.10 0.47 0.15 0.51 0.00 0.49 34.39% 20%

Steam (kWh) 0.20 0.54 0.00 1.00 1.00 1.00 1.00 0.40 0.22 0.68 19.88%

Weighted Percentage Differences Gas (kWh)

Weight -

1 1 1 1 0.7 0.7 0.7 0.7 1 1 1 0.7

0% Weight

Electricity Chilled W. (kWh) (kWh) 0.07 0.09 0.00 0.03 0.02 0.02 0.00 0.00 0.00 0.11 0.11 0.07 0.12 0.10 0.02 0.09 0.02 0.08 0.10 0.47 0.15 0.51 0.00 0.24 25% 33.43% 1 1

Steam (kWh) 0.20 0.54 0.00 1.00 0.50 0.50 1.00 0.40 0.22 0.34 16.91% 1

Gas (kWh) 0% 0

Weighted month: Different from the month calibration, I did not list all information in this report. I calibrate each hour in 365 days. The weight I chose based on the monthly calibration. The whole May, June, July, August, December are weighted 0.7 and other stay the same. All average based on the number I got from hourly calibration. Turn the number in monthly to hourly change the difference between each of them. The number become more reasonable in hourly. The chart between hourly and monthly stay the same form. I will show the graph in the next page. This means that both of them manage same way and the information also reasonable. Calibration continuous variables: Calibration Parameters (continuous variables) Parameter Heating COP Cooling COP Building air leakage level Appliance(Zone1) Lighting(Zone1) Appliance(Zone2) Lighting(Zone2) WD/WE_Tset_heat Delta T WD/WE_Tset_cool Delta T Roof Uvalue Wall Uvalue Specific fan power

Unit. kW/kW kW/kW (m3/h)/m2 W/m2 W/m2 W/m2 W/m2 [C]ELSIUS [C]ELSIUS [W/m2/K] [W/m2/K] W/(l/s)

Cell C26 C27 C45 G13 G14 H13 H14 K20 K22 G64 G66 C46

Minimum 2 2 0.05 5 8 2 2 -5 -5 0.348 0.297 1

Maximum 3 3 5 13.11 14 13.11 12 9 9 1.056 2.7 5

Selection 2.5 2.5 0.0500 9.3390 11.2531 11.7136 6.2508 -5.0000 5.7205 0.7933 0.6113 2.3692

WD/WE Tset delta T: Based on the result I got from Tech Opt, the set point temperature delta t is one of the things I add in the new hourly calibration. This can make EPC more focus on heat and cooling difference. Roof and Wallâ&#x20AC;&#x2122;s U value: In the monthly EPC I did not change any of these number. However, in the hourly calibration in order to get the result closer to the utility data, I set the U value to be changeable. The number will give EPC some range to adjust the U value and make the cooling and heating load closer than monthly

2017/1/1 上午 12:00:00.000 2017/1/11 上午 06:00:00.000 2017/1/21 上午 03:00:00.000 2017/1/31 上午 12:00:00.000 2017/2/9 下午 09:00:00.000 2017/2/19 下午 06:00:00.000 2017/3/1 下午 03:00:00.000 2017/3/11 下午 06:15:00.000 2017/3/21 下午 04:15:00.000 2017/3/31 下午 01:15:00.000 2017/4/10 上午 10:15:00.000 2017/4/20 上午 07:15:00.000 2017/4/30 上午 04:15:00.000 2017/5/10 上午 01:15:00.000 2017/5/19 下午 10:15:00.000 2017/5/29 下午 07:15:00.000 2017/6/8 下午 04:15:00.000 2017/6/18 下午 01:15:00.000 2017/6/28 上午 10:15:00.000 2017/7/8 上午 07:15:00.000 2017/7/18 上午 04:15:00.000 2017/7/28 上午 01:15:00.000 2017/8/6 下午 10:15:00.000 2017/8/16 下午 07:15:00.000 2017/8/26 下午 04:15:00.000 2017/9/5 下午 01:15:00.000 2017/9/15 上午 10:15:00.000 2017/9/25 上午 07:15:00.000 2017/10/5 上午 04:15:00.000 2017/10/15 上午 01:15:00.000 2017/10/24 下午 10:15:00.000 2017/11/3 下午 07:15:00.000 2017/11/13 下午 03:15:00.000 2017/11/23 下午 12:15:00.000 2017/12/3 上午 09:15:00.000 2017/12/13 上午 06:15:00.000 2017/12/23 上午 03:15:00.000

Hourly Calibration and Monthly Calibration Hourly calibration Delivered Electricity [kWh]

Building Utility Data (original inputs)

Jan

Feb

Mar

Apr

May

Building Utility Data (kWh) Building Simulation Calculations (kWh)

Monthly calibration Delivered Electricity [kWh]

9,000

8,000

7,000

6,000

5,000

4,000

3,000

2,000

1,000

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Building Simulation Calculations (kWh)

2017/1/1 上午 12:00:00.000 2017/1/11 下午 12:00:00.000 2017/1/21 下午 03:00:00.000 2017/1/31 下午 06:00:00.000 2017/2/10 下午 09:00:00.000 2017/2/21 上午 12:00:00.000 2017/3/3 上午 03:00:00.000 2017/3/13 下午 01:15:00.000 2017/3/23 下午 04:15:00.000 2017/4/2 下午 07:15:00.000 2017/4/12 下午 10:15:00.000 2017/4/23 上午 01:15:00.000 2017/5/3 上午 04:15:00.000 2017/5/13 上午 07:15:00.000 2017/5/23 上午 10:15:00.000 2017/6/2 下午 01:15:00.000 2017/6/12 下午 04:15:00.000 2017/6/22 下午 07:15:00.000 2017/7/2 下午 10:15:00.000 2017/7/13 上午 01:15:00.000 2017/7/23 上午 04:15:00.000 2017/8/2 上午 07:15:00.000 2017/8/12 上午 10:15:00.000 2017/8/22 下午 01:15:00.000 2017/9/1 下午 04:15:00.000 2017/9/11 下午 07:15:00.000 2017/9/21 下午 10:15:00.000 2017/10/2 上午 01:15:00.000 2017/10/12 上午 04:15:00.000 2017/10/22 上午 07:15:00.000 2017/11/1 上午 10:15:00.000 2017/11/11 下午 12:15:00.000 2017/11/21 下午 03:15:00.000 2017/12/1 下午 06:15:00.000 2017/12/11 下午 09:15:00.000 2017/12/22 上午 12:15:00.000

Hourly Calibration and Monthly Calibration Hourly calibration District Cooling [kWh]

Building Utility Data (original inputs)

Jan

Feb

Mar

Apr

May

Building Utility Data (kWh) Building Simulation Calculations (kWh)

Monthly calibration District Cooling [kWh]

35,000

30,000

25,000

20,000

15,000

10,000

5,000

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Building Simulation Calculations (kWh)

Hourly Calibration and Monthly Calibration Hourly calivration District Heating [kWh]

Building Utility Data (original inputs)

Jan

Feb

Mar

Apr

May

Building Utility Data (kWh) Building Simulation Calculations (kWh)

Monthly calibration District Heating [kWh]

30,000

25,000

20,000

15,000

10,000

5,000

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Building Simulation Calculations (kWh)

Tech Opt Outcome iteration 1 [Hourly]: Iteration 1: and 2 : Both iteration I used the same way as monthly. All the option and technology options are the same as monthly.

OBJECTIVE FUNCTION (NPC) = Total premium cost + electricity cost

OVERALL Construction Fee

$412,480.14

$381,936.67

Saved Edesign,p [kWh/m2/yr]

582.631936754846000

PI Qdesign,heat,nd [kWh/m2/yr] Qdesign,cool,nd [kWh/m2/yr] Edesign,del [kWh/m2/yr] Edesign,p [kWh/m2/yr] CO2design [g/m2/yr]

From Hourly Calculation

PI Original Qdesign,heat,nd [kWh/m2/yr] Original Qdesign,cool,nd [kWh/m2/yr] Original Edesign,del [kWh/m2/yr] Original Edesign,p [kWh/m2/yr] Original CO2design [g/m2/yr]

From Hourly Calculation

PI Saved Qdesign,heat,nd [kWh/m2/yr] Saved Qdesign,cool,nd [kWh/m2/yr] Saved Edesign,del [kWh/m2/yr] Saved Edesign,p [kWh/m2/yr] Saved CO2design [g/m2/yr]

From Hourly Calculation

25.4021980971684 8.9268502436061 32.10302308140 108.957660338272 14,587.8854595404

39 49 203.76829613822 692 92,594

13.880757753041400 39.953190657801500 171.665273056820 582.631936754846000 78,006.1533265545000000

Result: Based on the first iteration in hourly EPC Tech OPT result, It is surprised that the result is pretty dramatic. All numbers are higher than monthly EPC. Not only the energy saved but also total cost . All numbers are way more higher than monthly. I think the main reason is that based on the time changed. The hourly calibration or tech opt use different way to calculate energy load. The different way the EPC use might affect the cost and other loads.

Tech Opt Outcome Option iteration 2[Monthly]: Lighting daylighting factor Technology levels

Index

A 1 - Baseline (NULL) A 2 - Partial sensor (25%) A 3 - Partial sensor (50%) A 4 - Partial sensor (75%) A 5 - Fully autom. sensor

1 2 3 4 5

0.00 375.00 750.00 1125.00 1500.00

Par.1 C22 1 0.9 0.6 0.3 0

A 4 - Partial sensor (75%)

1125.00

0.3

Lighting occupancy factor Technology levels

Index

Cost $

B 1 - Baseline (NULL) B 2 - Partial sensor (25%) B 3 - Partial sensor (50%) B 4 - Partial sensor (75%) B 5 - Fully autom. sensor

1 2 3 4 5

0.00 0.00 0.00 0.00 0.00

Par.1 C23 1 0.9 0.6 0.3 0

B 3 - Partial sensor (50%)

0.00

0.6

Lighting constant illumination control factor Technology levels

Index

Cost $

C 1 - Baseline (NULL) C 2 - Partial dimmer C 3 - Partialy autom. Dimmer (50%) C 4 - Partialy autom. Dimmer (75%) C 5 - Fully autom. Dimmer

1 2 3 4 5

0.00 400.00 800.00 1200.00 1600.00

Par.1 C24 1 0.9 0.6 0.3 0

C 4 - Partialy autom. Dimmer (75%)

1200.00

0.3

Exhaust air recirculation percentage (inputs for C44 must be equal to dropdown menu) Technology levels

Index

Cost $

Par.1 C44

No exhaust air recirculation

0.00

No exhaust air recirculation

Exhaust air recirculation 20%

3900.00

Exhaust air recirculation 20%

Exhaust air recirculation 40% Exhaust air recirculation 60%

3 4

5300.00 6700.00

Exhaust air recirculation 40% Exhaust air recirculation 60%

Exhaust air recirculation 40%

5300.00

Exhaust air recirculation 40%

Heat recovery type (the inputs for C43 must be equal to dropdown menu) Technology levels

Index

Cost $

Par.1 C43

No heat recovery

0.00

6250.00

Heat exchange plates or pipes (0.65)

5800.00

Two-elements-system (0.6)

5300.00

Loading cold with air-conditioning (0.4)

Heat-pipes (0.6)

5700.00

Heat-pipes (0.6)

Slowly rotating or intermittent heat exchangers (0.7)

6960.00

Slowly rotating or intermittent heat exchangers (0.7)

Heat-pipes (0.6)

5700.00

Heat-pipes (0.6)

Heat exchange plates or pipes (0.65) Two-elementssystem (0.6) Loading cold with air-conditioning (0.4)

No heat recovery

Building air leakage level (Air flow m3/h per floor area at Q4Pa) Technology levels Value Minimum infiltration Maximum infiltration

Cost $

Par.1 C45

0.05 5

-53014.79

4.74

DHW Generation System (inputs for C52 must be equal to dropdown menu) Technology levels

Index

Electric (0.75) VR-Boiler (0.61) Gas Boiler, HR-Boiler (0.75) Co-Generation (0.9) District Heating (0.9) Heat Pump (1.4) Steam (0.61) Steam (0.61)

1 2

0.00 1859.00

Par.1 C52 Electric (0.75) VR-Boiler (0.61)

2469.00

Gas Boiler, HR-Boiler (0.75)

4 5 6 7 7

10110.00 800.00 1989.00 1309.00 1309.00

Co-Generation (0.9) District Heating (0.9) Heat Pump (1.4) Steam (0.61) Steam (0.61)

Type of BEM system installed Technology levels

Cost $

Index

Cost $

Par.1 C54 1

1: Class D

0.00

2: Class C

13195.47

3: Class B 4: Class A

3 4

32128.10 43028.70

3 4

3: Class B

32128.10

PV module Surface Area (m2) Technology levels

Value

Minimum # PV modules Maximum # PV modules

0 83.71

Cost $

Par.1 C58

20181.72

Solar Collector Surface Area (m2) Technology levels

Value

Minimum # Solar Col. Maximum # Solar Col.

0 45.45

Cost $

135.20

Par.1 C64

15680.00

45.20

Lighting zone1 (W/m2) Technology levels

Index

100% CFL LED and CFL combo (50% LED) LED Fluorescent lamp t5 Fluorescent lamp t8 Fluorescent lamp t12 Fluorescent lamp t5

1 2 3 4 5 6 4

Lighting zone2 (W/m2) Technology levels

Par.1 G13

0.00 7245.00 8050.00 6670.00 6900.00 7360.00 6670.00

Index

100% CFL LED and CFL combo (50% LED) LED Fluorescent lamp t5 Fluorescent lamp t8 Fluorescent lamp t12 LED and CFL combo (50% LED) Roof1

Cost $

1 2 3 4 5 6 2

Par.1 G14

0.00 3780.00 4200.00 3480.00 3600.00 3840.00 3780.00

Index

Roof Baseline 1 Roof Improvement 2.0 mm( new insulationEX Membrane) Roof Improvement 1.8 mm( new insulation EX Membrane) Roof Improvement 1.6 mm( new insulation EX Membrane) Roof Improvement 1.2 mm( new insulation EX Membrane)

0.00

43572.00

0.45

0.6

0.9

68989.00

0.3

0.6

0.9

79882.00

0.2

0.6

0.9

94406.00

0.13

0.6

0.9

68989.00

0.3

0.6

0.9

Opaque1

Technology levels

Index

Wall Baseline 1 Wall Improvement 2 (R-38 insulation) Wall Improvement 3 (R-30 insulation) Wall Improvement 3 (R-21 insulation) Wall Improvement 4 (R-19 insulation) Wall Improvement 5 (R-13 insulation) Wall Improvement 6 (R-11 insulation) Wall Improvement 6 (R-11 insulation)

1 2 3 4 5 6 7 7

Window1 Technology levels Window Baseline 1 Double Glz: 6mm air Double Glz (Uncoated CLR CLR):3mm/12mm air (SHGC:0.66) Double Glz: 6mm argon Double Glz (e=0.40 surface2 or 3):12mm argon Triple Glz: 12mm argon Quadruple Glz (e=0.10):12mm argon Double Glz (Uncoated CLR CLR):3mm/12mm air (SHGC:0.66)

Index

Cost $ 0.00 13761.83 15102.26 18229.95 21849.13 24172.56 27032.16 27032.16

Cost $

Par.1 G64

Par.1 G66

Par.1 G68

0.79

0.61 1.7 1.69 1.67 1.65 1.63 1.6 1.6

5.91 2.16

Par.2 H64

6.25 2.05 2.10 1.97 2.16 2.54 2.048062672

Technology levels

Roof Improvement 1.8 mm( new insulation EX Membrane)

Cost $

11.25 5.10 2.21 2.07 2.27 2.67 2.072674419

Par.2 H66

Par.2 I68

0.54

0.42 0.4 0.38 0.35 0.33 0.32 0.3 0.3

0 0.4

Par.3 I64

Par.3 I66

Par.3 J68

0.9

0.62 0.62 0.62 0.62 0.62 0.62 0.62 0.62

1 2

0.00 21900.00

0.53 0.6

24300.00

2.27

0.8

0.2

25200.00

1.77

0.69

0.31

25800.00

1.99

0.51

0.49

31800.00

1.65

0.59

0.41

36000.00

0.68

0.8

0.2

24300.00

2.27

0.8

0.2

North window ratio Technology levels Minimize Maximum Ratio

Index

Cost $

Par.1 S54

0.1 0.8

11801.09 South window ratio Technology levels Starting Construction Worker Minimize Maximum Ratio

Index 0.1 0.8

Cost $ Total Cost(Without worker fee)

0.231047466 Par.1 S50

32647.49 West window ratio Technology levels Starting Construction Worker Minimize Maximum Ratio

Index 0.1 0.8

Cost $ Total Cost(Without worker fee)

0.680564216 Par.1 S56

12779.62 East window ratio Technology levels Starting Construction Worker Minimize Maximum Ratio

Index 0.1 0.8

Cost $ Total Cost(Without worker fee)

0.472852846 Par.1 S52

20482.99 Set point Heat Temp Technology levels Minimize delta T Maximum delta T

Index

Cost $

0.757881629 Par.1 K20

-9 5

639.50 Set point Cool Temp Technology levels Minimize delta T Maximum delta T

Index

Cost $

-5.00 Par.1 K22

-9 5

-383.70

3.00

South Shading-South Overhang Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree 30 Degree South Shading-South Fin Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree 30 Degree South Shading-South Horizontal Angle Technology levels Starting Construction Worker Baseline 10 Degree 20 Degree 30 Degree 40 Degree 50 Degree 60 Degree 70 Degree 80 Degree 50 Degree East Shading-South Overhang Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree 60 Degree East Shading-South Fin Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree 45 Degree East Shading-South Horizontal Angle Technology levels Starting Construction Worker Baseline 10 Degree 20 Degree 30 Degree 40 Degree 50 Degree 60 Degree 70 Degree 80 Degree 60 Degree

Index 1 2 3 4

Cost $ Total Cost(Without worker fee) 0.00 6600.00 7600.00 8120.00

6600.00

Index 1 2 3 4

Cost $ Total Cost(Without worker fee) 0.00 13200.00 15200.00 16240.00

13200.00

Index

Par.1 Overhang

30 Par.1 Fin Angle

Par.1 Horizontal Angle

1 2 3 4

Cost $ Total Cost(Without worker fee) 0.00 6600.00 7600.00 8120.00

Par.1 Overhang

8120.00

Index

Index 1 2 3 4

Cost $ Total Cost(Without worker fee) 0.00 13200.00 15200.00 16240.00

15200.00

Index 1 2 3 4 5 6 7 8 9 7

Cost $ Total Cost(Without worker fee) 0.00 6600.00 6760.00 6920.00 7080.00 7240.00 7400.00 7560.00 7700.00 7400.00

0 30 45 60 30

Cost $ Total Cost(Without worker fee) 0.00 6600.00 6760.00 6920.00 7080.00 7240.00 7400.00 7560.00 7700.00 7240.00

1 2 3 4 5 6 7 8 9 6

0 30 45 60

0 10 20 30 40 50 60 70 80 50

0 30 45 60 60

Par.1 Fin Angle

0 30 45 60 45

Par.1 Horizontal Angle

0 10 20 30 40 50 60 70 80 60

North Shading-South Overhang Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree 30 Degree North Shading-South Fin Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree 30 Degree North Shading-South Horizontal Angle Technology levels Starting Construction Worker Baseline 10 Degree 20 Degree 30 Degree 40 Degree 50 Degree 60 Degree 70 Degree 80 Degree 30 Degree West Shading-South Overhang Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree 45 Degree West Shading-South Fin Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree 45 Degree West Shading-South Horizontal Angle Technology levels Starting Construction Worker Baseline 10 Degree 20 Degree 30 Degree 40 Degree 50 Degree 60 Degree 70 Degree 80 Degree 20 Degree

Index 1 2 3 4

Cost $ Total Cost(Without worker fee) 0.00 6600.00 7600.00 8120.00

6600.00

Index 1 2 3 4

Cost $ Total Cost(Without worker fee) 0.00 13200.00 15200.00 16240.00

13200.00

Index

Par.1 Overhang

30 Par.1 Fin Angle

Par.1 Horizontal Angle

1 2 3 4

Cost $ Total Cost(Without worker fee) 0.00 6600.00 7600.00 8120.00

Par.1 Overhang

7600.00

Index

Index 1 2 3 4

Cost $ Total Cost(Without worker fee) 0.00 13200.00 15200.00 16240.00

15200.00

Index 1 2 3 4 5 6 7 8 9 3

Cost $ Total Cost(Without worker fee) 0.00 6600.00 6760.00 6920.00 7080.00 7240.00 7400.00 7560.00 7700.00 6760.00

0 30 45 60 30

Cost $ Total Cost(Without worker fee) 0.00 6600.00 6760.00 6920.00 7080.00 7240.00 7400.00 7560.00 7700.00 6920.00

1 2 3 4 5 6 7 8 9 4

0 30 45 60

0 10 20 30 40 50 60 70 80 30

0 30 45 60 45

Par.1 Fin Angle

0 30 45 60 45

Par.1 Horizontal Angle

0 10 20 30 40 50 60 70 80 20

Tech Opt Result iteration 1[Hourly]:

Tech Opt Heating and Cooling Need Difference 16.00 14.00 12.00

Heating Need [kWh/m2] (After)

10.00

Cooling Need [kWh/m2] (After)

8.00

Heating Need [kWh/m2] (Before)

6.00

Cooling Need [kWh/m2] (Before)

4.00 2.00 -

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Tech Opt Delivered Energy Difference 35.00 30.00 25.00

Hourly Method Energy Delivered [kWh/m2] (Original)

20.00

Hourly Method Energy Delivered [kWh/m2] (After)

15.00 10.00 5.00 -

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Different iteration : The result show dramatically different with monthly. The result drop dramatically. In the options part, EPC chose the number in different way. It almost change everything in the option. The things include shading and ration. It is very surprised that the monthly did not use the same option as hourly. Even though the iteration and the options are the same as monthly. Like the ratio part, monthly changed the ration to minimum. However, the hourly do not change it into minimum. The other option that is very different is the shading part. Based on the SRF number we got in the monthly and hourly EPC. Adding any shading can be a great impact on each direction. However, the monthly did not change any things. It is said that the hourly EPC Tech opt is way more correct than monthly EPC. The whole iteration seems very reasonable.

Tech Opt Outcome iteration 2 [Hourly]: Iteration 1: and 2 : Both iteration I used the same way as monthly. All the option and technology options are the same as monthly.

OBJECTIVE FUNCTION (NPC) = Total premium cost + electricity cost

OVERALL Construction Fee

$339,682.45

$251,964.91

Saved Edesign,del [kWh/m2/yr]

111.571895990735

OBJECTIVE FUNCTION (NPC) = Total premium cost + electricity cost $339,682.45 Money Saved $154,308.49 Energy saving/ Cost 0.0003 NET Enterprise Innovation Institute [$] $339,769.09

Energy saving% 121.02% ENERGY Saving Restriction [%] 30.00%

PI Original Qdesign,heat,nd [kWh/m2/yr] Original Qdesign,cool,nd [kWh/m2/yr] Original Edesign,del [kWh/m2/yr] Original Edesign,p [kWh/m2/yr] Original CO2design [g/m2/yr]

From Hourly Calculation

PI Saved Qdesign,heat,nd [kWh/m2/yr] Saved Qdesign,cool,nd [kWh/m2/yr] Saved Edesign,del [kWh/m2/yr] Saved Edesign,p [kWh/m2/yr] Saved CO2design [g/m2/yr]

From Hourly Calculation

39 49 203.76829613822 692 92,594

18.568630437738900 23.038841355392500 111.571895990735 378.675014992556000 50,699.2140612329000000

Result: The iteration 2 has some restriction for schoolâ&#x20AC;&#x2122;s budget and energy saving percentages. Based on the constrain, EPC hourly can still manage the better option than monthly. In iteration 1 shows the potential which EPC can reach. In iteration 2 with restriction, EPC hourly not only maintain the object but also not even reach Â˝ potential in iteration 1. This result is really surprising and it is easy to see that the hourly EPC is more number correct than monthly EPC.

Tech Opt Outcome Option iteration 2[Hourly]: Lighting daylighting factor Technology levels

Index

Cost $

Par.1 C22 1 0.9 0.6 0.3 0

A 1 - Baseline (NULL) A 2 - Partial sensor (25%) A 3 - Partial sensor (50%) A 4 - Partial sensor (75%) A 5 - Fully autom. sensor

1 2 3 4 5

0.00 375.00 750.00 1125.00 1500.00

A 1 - Baseline (NULL)

0.00

Lighting occupancy factor Technology levels

Index

B 1 - Baseline (NULL) B 2 - Partial sensor (25%) B 3 - Partial sensor (50%) B 4 - Partial sensor (75%) B 5 - Fully autom. sensor

1 2 3 4 5

0.00 0.00 0.00 0.00 0.00

Par.1 C23 1 0.9 0.6 0.3 0

B 4 - Partial sensor (75%)

0.00

0.3

Lighting constant illumination control factor Technology levels

Index

Cost $

C 1 - Baseline (NULL) C 2 - Partial dimmer C 3 - Partialy autom. Dimmer (50%) C 4 - Partialy autom. Dimmer (75%) C 5 - Fully autom. Dimmer

1 2 3 4 5

0.00 400.00 800.00 1200.00 1600.00

Par.1 C24 1 0.9 0.6 0.3 0

C 2 - Partial dimmer

400.00

0.9

Exhaust air recirculation percentage (inputs for C44 must be equal to dropdown menu) Technology levels

Index

Cost $

Par.1 C44

No exhaust air recirculation

0.00

No exhaust air recirculation

Exhaust air recirculation 20%

3900.00

Exhaust air recirculation 20%

Exhaust air recirculation 40% Exhaust air recirculation 60%

3 4

5300.00 6700.00

Exhaust air recirculation 40% Exhaust air recirculation 60%

No exhaust air recirculation

0.00

No exhaust air recirculation

Heat recovery type (the inputs for C43 must be equal to dropdown menu) Technology levels

Index

Cost $

Par.1 C43

No heat recovery Heat exchange plates or pipes (0.65) Two-elementssystem (0.6) Loading cold with air-conditioning (0.4) Heat-pipes (0.6) Slowly rotating or intermittent heat exchangers (0.7) Loading cold with air-conditioning (0.4)

0.00

No heat recovery

6250.00

Heat exchange plates or pipes (0.65)

5800.00

Two-elements-system (0.6)

5300.00

Loading cold with air-conditioning (0.4)

5700.00

Heat-pipes (0.6)

6960.00

Slowly rotating or intermittent heat exchangers (0.7)

5300.00

Loading cold with air-conditioning (0.4)

Building air leakage level (Air flow m3/h per floor area at Q4Pa) Technology levels Value Minimum infiltration Maximum infiltration

Cost $

Par.1 C45

0.05 5

-46831.88

DHW Generation System (inputs for C52 must be equal to dropdown menu) Technology levels Index Electric (0.75) VR-Boiler (0.61) Gas Boiler, HR-Boiler (0.75) Co-Generation (0.9) District Heating (0.9) Heat Pump (1.4) Steam (0.61) Gas Boiler, HR-Boiler (0.75)

1 2

0.00 1859.00

Par.1 C52 Electric (0.75) VR-Boiler (0.61)

2469.00

Gas Boiler, HR-Boiler (0.75)

4 5 6 7

10110.00 800.00 1989.00 1309.00

Co-Generation (0.9) District Heating (0.9) Heat Pump (1.4) Steam (0.61)

2469.00

Gas Boiler, HR-Boiler (0.75)

Type of BEM system installed Technology levels

Cost $

4.36

Index

Cost $

Par.1 C54 1

1: Class D

0.00

2: Class C

13195.47

3: Class B 4: Class A

3 4

32128.10 43028.70

3 4

1: Class D

0.00

PV module Surface Area (m2) Technology levels

Value

Minimum # PV modules Maximum # PV modules

0 83.71

Cost $

Par.1 C58

12807.63

Solar Collector Surface Area (m2) Technology levels

Value

Minimum # Solar Col. Maximum # Solar Col.

0 45.45

Cost $

33 85.80

Par.1 C64

8624.00

11 24.86

Lighting zone1 (W/m2) Technology levels

Index

100% CFL LED and CFL combo (50% LED) LED Fluorescent lamp t5 Fluorescent lamp t8 Fluorescent lamp t12 LED and CFL combo (50% LED)

1 2 3 4 5 6 2

Lighting zone2 (W/m2) Technology levels

Par.1 G13

0.00 7245.00 8050.00 6670.00 6900.00 7360.00 7245.00

Index

100% CFL LED and CFL combo (50% LED) LED Fluorescent lamp t5 Fluorescent lamp t8 Fluorescent lamp t12 Fluorescent lamp t5 Roof1

Cost $

1 2 3 4 5 6 4

Par.1 G14

0.00 3780.00 4200.00 3480.00 3600.00 3840.00 3480.00

Index

0.00

43572.00

0.45

0.6

0.9

68989.00

0.3

0.6

0.9

79882.00

0.2

0.6

0.9

94406.00

0.13

0.6

0.9

68989.00

0.3

0.6

0.9

Opaque1

Technology levels

Index

1 2 3 4 5 6 7 1

Index

Cost $ 0.00 13761.83 15102.26 18229.95 21849.13 24172.56 27032.16 0.00

Cost $

Par.1 G64

Par.1 G66

Par.1 G68

0.79

0.61 1.7 1.69 1.67 1.65 1.63 1.6 0.61

5.91 2.16

Par.2 H64

6.25 2.05 2.10 1.97 2.16 2.54 1.969087444

Technology levels

Roof Improvement 1.8 mm( new insulation EX Membrane)

Cost $

11.25 5.10 2.21 2.07 2.27 2.67 5.103197674

Par.2 H66

Par.2 I68

0.54

0.42 0.4 0.38 0.35 0.33 0.32 0.3 0.42

0 0.4

Par.3 I64

Par.3 I66

Par.3 J68

0.9

0.62 0.62 0.62 0.62 0.62 0.62 0.62 0.62

1 2

0.00 21900.00

0.53 0.6

24300.00

2.27

0.8

0.2

25200.00

1.77

0.69

0.31

25800.00

1.99

0.51

0.49

31800.00

1.65

0.59

0.41

36000.00

0.68

0.8

0.2

25800.00

1.99

0.51

0.49

North window ratio Technology levels Minimize Maximum Ratio

Index

Cost $

Par.1 S54

0.1 0.8

37478.69 South window ratio Technology levels Starting Construction Worker Minimize Maximum Ratio

Index 0.1 0.8

Cost $ Total Cost(Without worker fee)

0.704188164 Par.1 S50

3270.60 West window ratio Technology levels Starting Construction Worker Minimize Maximum Ratio

Index 0.1 0.8

Cost $ Total Cost(Without worker fee)

0.169025428 Par.1 S56

3270.60 East window ratio Technology levels Starting Construction Worker Minimize Maximum Ratio

Index 0.1 0.8

Cost $ Total Cost(Without worker fee)

0.284628225 Par.1 S52

2144.87 Set point Heat Temp Technology levels Minimize delta T Maximum delta T

Index

Cost $

0.196750179 Par.1 K20

-9 5

255.80 Set point Cool Temp Technology levels Minimize delta T Maximum delta T

Index

Cost $

-2.00 Par.1 K22

-9 5

-127.90

1.00

South Shading-South Overhang Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree Baseline South Shading-South Fin Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree 45 Degree South Shading-South Horizontal Angle Technology levels Starting Construction Worker Baseline 10 Degree 20 Degree 30 Degree 40 Degree 50 Degree 60 Degree 70 Degree 80 Degree 30 Degree East Shading-South Overhang Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree 30 Degree East Shading-South Fin Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree 30 Degree East Shading-South Horizontal Angle Technology levels Starting Construction Worker Baseline 10 Degree 20 Degree 30 Degree 40 Degree 50 Degree 60 Degree 70 Degree 80 Degree 50 Degree

Index 1 2 3 4

Cost $ Total Cost(Without worker fee) 0.00 6600.00 7600.00 8120.00

0.00

Index 1 2 3 4

Cost $ Total Cost(Without worker fee) 0.00 13200.00 15200.00 16240.00

15200.00

Index

Par.1 Overhang

0 Par.1 Fin Angle

Par.1 Horizontal Angle

1 2 3 4

Cost $ Total Cost(Without worker fee) 0.00 6600.00 7600.00 8120.00

Par.1 Overhang

6600.00

Index

Index 1 2 3 4

Cost $ Total Cost(Without worker fee) 0.00 13200.00 15200.00 16240.00

13200.00

Index 1 2 3 4 5 6 7 8 9 6

Cost $ Total Cost(Without worker fee) 0.00 6600.00 6760.00 6920.00 7080.00 7240.00 7400.00 7560.00 7700.00 7240.00

0 30 45 60 45

Cost $ Total Cost(Without worker fee) 0.00 6600.00 6760.00 6920.00 7080.00 7240.00 7400.00 7560.00 7700.00 6920.00

1 2 3 4 5 6 7 8 9 4

0 30 45 60

0 10 20 30 40 50 60 70 80 30

0 30 45 60 30

Par.1 Fin Angle

0 30 45 60 30

Par.1 Horizontal Angle

0 10 20 30 40 50 60 70 80 50

North Shading-South Overhang Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree 45 Degree North Shading-South Fin Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree Baseline North Shading-South Horizontal Angle Technology levels Starting Construction Worker Baseline 10 Degree 20 Degree 30 Degree 40 Degree 50 Degree 60 Degree 70 Degree 80 Degree 70 Degree West Shading-South Overhang Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree 30 Degree West Shading-South Fin Angle Technology levels Starting Construction Worker Baseline 30 Degree 45 Degree 60 Degree 30 Degree West Shading-South Horizontal Angle Technology levels Starting Construction Worker Baseline 10 Degree 20 Degree 30 Degree 40 Degree 50 Degree 60 Degree 70 Degree 80 Degree 40 Degree

Index 1 2 3 4

Cost $ Total Cost(Without worker fee) 0.00 6600.00 7600.00 8120.00

7600.00

Index 1 2 3 4

Cost $ Total Cost(Without worker fee) 0.00 13200.00 15200.00 16240.00

0.00

Index

Par.1 Overhang

45 Par.1 Fin Angle

Par.1 Horizontal Angle

1 2 3 4

Cost $ Total Cost(Without worker fee) 0.00 6600.00 7600.00 8120.00

Par.1 Overhang

6600.00

Index

Index 1 2 3 4

Cost $ Total Cost(Without worker fee) 0.00 13200.00 15200.00 16240.00

13200.00

Index 1 2 3 4 5 6 7 8 9 5

Cost $ Total Cost(Without worker fee) 0.00 6600.00 6760.00 6920.00 7080.00 7240.00 7400.00 7560.00 7700.00 7080.00

0 30 45 60 0

Cost $ Total Cost(Without worker fee) 0.00 6600.00 6760.00 6920.00 7080.00 7240.00 7400.00 7560.00 7700.00 7560.00

1 2 3 4 5 6 7 8 9 8

0 30 45 60

0 10 20 30 40 50 60 70 80 70

0 30 45 60 30

Par.1 Fin Angle

0 30 45 60 30

Par.1 Horizontal Angle

0 10 20 30 40 50 60 70 80 40

Tech Opt Result iteration 2[Hourly]: Tech Opt Heating and Cooling Need Difference 16.00 14.00 12.00

Heating Need [kWh/m2] (After)

10.00

Cooling Need [kWh/m2] (After)

8.00

Heating Need [kWh/m2] (Before)

6.00

Cooling Need [kWh/m2] (Before)

4.00 2.00 -

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Tech Opt Delivered Energy Difference 35.00 30.00 25.00

Hourly Method Energy Delivered [kWh/m2] (Original)

20.00

Hourly Method Energy Delivered [kWh/m2] (After)

15.00 10.00 5.00 -

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Iteration 2: The result show dramatically different with iteration 1. With the restriction, it is very surprised that EPC do not use the same decision as iteration 1. It is oblivious that EPC raise the north side window ratio into 0.8. This almost the maximum number of the whole wall. It is probably that the north side do not get a lot of radiation and was block by DS Smith building. The raising ratio of window can reduce cooling need which is the most concern for this site. The other things is that the EPC use a lot of building change instead of system change which is very interesting outcome. Last but not least EPC also do not use the whole PV to reduce energy. This is also a good discover that the optimization do not always need PV to solve the problems

Tech Opt Result iteration 1 and 2 difference[Hourly]: Delivered Load Difference percentage 1.20 1.00 Hourly Method Heating Need Percentage Difference (Iteration 1)

0.80 0.60

Hourly Method Cooling Need Percentage Difference (Iteration 1)

0.40

Hourly Method Heating Need Percentage Difference (Iteration 2)

0.20 -

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Hourly Method Cooling Need Percentage Difference (Iteration 2)

Delivered Energy Difference percentage 1.20 1.00 0.80

Hourly Method Energy Delivered Percentage Difference (Interation 1)

0.60

Hourly Method Energy Delivered Percentage Difference (Iteration2)

0.40 0.20 -

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Difference The cooling need is the most different part. It is oblivious that the hourly cooling load is more accurate than monthly. EPC hourly turn the cooling load in December to 0. This seems reasonable. The rest of the chartâ&#x20AC;&#x2122;s form is very similar to monthly. Although in some area it seems a little bit different, it still looks the same as the monthly.

Tech Opt iteration 1 and 2 difference[Hourly and Monthly]: Monthly and hourly Delivered Energy Difference percentage 1.20 1.00 0.80

Hourly Method Energy Delivered Percentage Difference (Interation 1)

0.60

Hourly Method Energy Delivered Percentage Difference (Iteration2)

0.40

Monthly Method Energy Delivered Percentage Difference (Interation 1)

0.20

Monthly Method Energy Delivered Percentage Difference (Iteration2)

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Monthly and hourly Delivered Load Difference percentage Hourly Method Heating Need Percentage Difference (Iteration 1)

1.20

Hourly Method Cooling Need Percentage Difference (Iteration 1)

1.00

Hourly Method Heating Need Percentage Difference (Iteration 2)

0.80

Hourly Method Cooling Need Percentage Difference (Iteration 2)

0.60

Monthly Method Heating Need Percentage Difference (Iteration 1)

0.40

Monthly Method Cooling Need Percentage Difference (Iteration 1)

0.20 -

Monthly Method Heating Need Percentage Difference (Iteration 2)

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Monthly Method Cooling Need Percentage Difference (Iteration 2)

Difference According to the result it is very surprised that the monthlyâ&#x20AC;&#x2122;s option do not transfer dramatically as monthly. Bothe energy and load difference are more smooth line than monthly. The reason I think is the monthly counting matrix are very different than the hourly EPC.

Energy Plus and Open Studio Zoning:.

Total and Environment Zoning

Construction Zoning

Space Type Zoning

Thermal Zoning

HVAC Zoning

Zoning and energy plus In this stage I began using energy plus and open studio. The difference between the EPC and the energy plus is that in energy plus and open studio I define the zone more specificity. I define the space using different space use. The 1 floor has open office and closed office. The 2 floor also has open and closed office. For two floor they both have restroom and corridor. The only difference is that the energy plus model has ground floor which is ELE room. For the HVAC zone I separate each floor with different thermal zone. For the HVAC system part because I do not have very clear Electric pluming drawing. I assumed the system is going to be the VAV system which motored by electricity. Each floor has one HVAC (VAV) system. The other setting remains the same as EPC.

Energy Plus HVAC system 1F HVAC system

2F HVAC system

B1F HVAC system

VRF system

Clearer than EPC The difference between the energy plus and EPC is the HVAC system. Energy plus is more accurate than EPC in HVAC part. The system I used is VRF system. The main reason is that the system very simple in small zoning building. Since the system CAD is not clear enough for me to confirm it is right or not, I use the general system in every building. I sperate into three system since my building has three floor. The cooling coil and heating coil in this stage I can set it connect to the District cooling and heating system.

Energy Plus result Electricity Difference 3E+10 2.5E+10 2E+10 Energy Plus (Before Calibration)

1.5E+10

EPC ELE UTILIY E

1E+10 5E+09 0

District Cooling Difference 100,000,000,000.00 80,000,000,000.00 60,000,000,000.00

Energy Plus( Before Calibration) EPC COOLING

40,000,000,000.00

UTILIY E

20,000,000,000.00 0.00

10 11 12

District Heating Difference 1E+11 9E+10 8E+10 7E+10 6E+10 5E+10 4E+10 3E+10 2E+10 1E+10 0

Energy Plus (Before Calibration) EPC HEAT UTILITY H

Parameter change Based on the result I got from energy plus, it is very clear that some of the parameter I set in EPC like occupancy , lighting , appliance is not the right parameter based on the difference between energy plus and utility data. According to the graph most of the number still have small gap between utility data but the form is the same. I proposed the main reason is that the parameter I just talked about is not the correct number. In the calibration this parameters have to be changed. The other reason is that the utility data show that the data that combine with internal load and indirect energy consume. I have to break it up to discover the reason that cause the problem.

Energy Plus Calibration Calibration parameter:. 8IN Concrete HW thickness

0.03

0.05

0.3

Brick thickness

0.03

0.24

0.5

COPPER thickness

0.03

0.2

0.5

Metal Decking

0.01

0.05

0.5

WindowMaterial:SimpleGlazingSystem U value

0.68

5.91

7.2

OMED close 1 light

CP Building CSID 1 light

ElectricEquipment, OMED close 2,

13.11

ElectricEquipment CSID APPLIENCE

13.11

ZoneInfiltration:DesignFlowRate close

0.0001

0.000226568

0.006

ZoneInfiltration:DesignFlowRate OpenOffice CSID

0.0001

0.000226568

0.006

Design Specification :Outdoor Air-Close Office Ventilation

0.0001

0.002359737

0.006

Design Specification : Outdoor Air-OpenOffice Ventilation

0.0001

0.002359737

0.006

After calibration parameter :. 8IN Concrete HW thickness

0.03

0.043024857

0.3

Brick thickness

0.03

0.276695461

0.5

COPPER thickness

0.03

0.064818727

0.5

Metal Decking

0.01

0.5

WindowMaterial:SimpleGlazingSystem U value

0.68

5.911908749

7.2

OMED close 1 light

25.55814371

CP Building CSID 1 light

18.0516069

ElectricEquipment, OMED close 2,

24.6023491

ElectricEquipment CSID APPLIENCE

20.8573945

Zone Infiltration: Design Flow Rate close

0.0001

0.000190415343483954 0.006

ZoneInfiltration:DesignFlowRate OpenOffice CSID

0.0001

0.0001 0.006

Design Specification :Outdoor Air-Close Office Ventilation

0.0001

0.004611261 0.006

Design Specification: Outdoor Air-OpenOffice Ventilation

0.0001

0.005840046 0.006

Calibration driven The parameter I set is based on some of the result I got from the energy plus simulation. The reason I set the some materialâ&#x20AC;&#x2122;s thickness is the I do not fully know the section of the construction and the cooling load and heat load are very different from utility data that can conclude that the U value of the material is not correct. I took several different material that maybe the main material of the building and recount its U value. I also reset the infiltration of the building. Two of these can change the cooling and heating load of the building. Also the other one is the lighting and equipment. The two of them can also affect the heating load and cooling load. The other reason that I set the appliance and lighting is that these two can also affect the electricity. From the result, the electricity have some gaps in between the utility data and result.

Energy Plus Calibration Electricity Difference 4E+10 3.5E+10 3E+10 Energy Plus (Before Calibration)

2.5E+10 2E+10

EPC ELE

1.5E+10

UTILIY E Energy Plus (After Calibration)

1E+10 5E+09 0

District Cooling Difference 100,000,000,000.00 90,000,000,000.00 80,000,000,000.00 70,000,000,000.00 60,000,000,000.00 50,000,000,000.00 40,000,000,000.00 30,000,000,000.00 20,000,000,000.00 10,000,000,000.00 0.00

Energy Plus( Before Calibration) EPC COOLING UTILIY E Energy Plus (After Calibration)

9 10 11 12

District Heating Difference 1E+11 9E+10 8E+10 7E+10 6E+10 5E+10 4E+10 3E+10 2E+10 1E+10 0

Energy Plus (Before Calibration) EPC HEAT UTILITY H Energy Plus('0212-1Meter(ep and epc differen'!$M$17 1

After Calibration The result showed that the parameter I set is very the problem I assumed in the front paragraph. The other things in cooling load for the building according to the utility data show the summer month is very high-loaded. The reason is that the building in summer time they active a activity for African student from 9am to 16pm. The activity is about the introduce to the campus and other touring work. This cost the building a lot of cooling load. This also help in the beginning of the winter semester. This is main reason that cause the building high cooling and heating load in utility data. The other things is that the energy plus model I set include the schedule which have summer vacation and winter vacation. That is main reason that cause the gap between the calibration.

Total Difference (Building load) Thermal Load (Heating) 45

Energy Plus Heating Load

KWH/M2

40 35

Energy Plus Heating Load (after calibration)

EPC Monthly( Before Calibration)

EPC Monthly( After Calibration)

EPC Monthly( After Tech Opt)it1

15 EPC Monthly( After Tech Opt)it2

EPC Hourly( Before Calibration)

5 0

EPC Hourly( After Calibration) EPC Hourly( After Tech Opt)it1

Thermal Load (Cooling) 45

KWH/M2

Energy Plus Cooling Load

Energy Plus Cooling Load (after calibration)

EPC Monthly( Before Calibration)

EPC Monthly( After Calibration)

20 15

EPC Monthly( After Tech Opt)it1 EPC Monthly( After Tech Opt)it2

10 5 0

EPC Hourly( Before Calibration) EPC Hourly( After Calibration) EPC Hourly( After Tech Opt)it1

Result The result showed that the difference between the monthly EPC and hourly EPC change drastically. The hourly EPC outcome is close to the energy plus data. It is also interested that the form between the EPC hourly calibration and energy plus calibration is very similar. I assumed that the reason is that both of them are driven by the utility data. Last but least, I also discovered that building thermal load will increase after the Tech opt modify. I think the main reason is that the tech opt change the appliance number although it can make the energy performance become efficient but it will also cost the load problem because the appliance.

Total Difference (Direct and indirect deliver energy) HVAC Delievery energy 70 Energy Plus HVAC ENERGY (before calibration)

Energy Plus HVAC ENERGY (after calibration)

KWH/M2

EPC Monthly( Before Calibration)

EPC Monthly( After Calibration)

EPC Monthly( After Tech Opt)it1

EPC Monthly( After Tech Opt)it2

EPC Hourly( Before Calibration) EPC Hourly( After Calibration)

EPC Hourly( After Tech Opt)it1

Other Deliever energy 20 18 16

KWH/M2

14 12 10 8 6 4 2 0

Energy Plus Other ENERGY (before calibration) Energy Plus Other ENERGY (after calibration) EPC Monthly( Before Calibration) EPC Monthly( After Calibration) EPC Monthly( After Tech Opt)it1 EPC Monthly( After Tech Opt)it2 EPC Hourly( Before Calibration) EPC Hourly( After Calibration)

Result According to the parameter I set in both EPC and energy plus, there occupancy and lighting appliance is all the same. However, there still have some difference between each other. The main reason is that from monthly to hourly then to energy plus, there load counting method are not the same. The most difference I found out is fan load. I think the main reason for that is EPCâ&#x20AC;&#x2122;s HVAC system load counting method are not the same as energy plus HVAC counting method. Last but not least, the calibration also will make the difference. According to the parameters I set, appliance and infiltration will affect the HVAC energy. The system will be affected by the building environment( materials, wall ). These caused both energy raise.

IES VE Simulations

IESVE Simulation I input the geometry into the IESVE. In the IESVE model the energy consumption is more precise. I can set up the holiday and week day during the whole year. The most different in the IESVE model is their micro flow and daylight analysis. It can make these into count during the simulation process. These are a big impact for building performance. The Chanping buildingâ&#x20AC;&#x2122;s dimension is not as big as the other building. The daylight and infiltration are very big impact for these reason. From IESVE counting it is very surprised that the result is not as I consumption in the beginning. The daylight analysis is not big impact during the day. The infiltration is actually the things that make it difference.

IES VE Daylight Simulations First floor:.

Second floor:.

Result According to the result I got from the IES VE, it is very surprised that the daylight lux is not as high I thought. I assume the main reason is that the environment near the site are cover with big tree and tall building. First floor get more daylight based on the some of tree. The trees near the building their leaf part are in the second floor. These might have caused the reason that the second floor’s daylight is lesser than the first floor. The first floor only covered by surrounding building. However, the surrounding buildings are not very closed to the site. Each of them have more than 3 meter’s distance. These is main reason that some first floor’s edge have overheated by daylight. Last but least, for the second floor the open office in the east’s edge daylight is caused by the uncovered of the environment.

Daylight Simulations Legend

Daylight Category( From Tarek Rakhaâ&#x20AC;&#x2122;s lecture) 750 lux The legend I used for the dalylight simulation are come from the LUX legend for activity. I picked 750 lux for normal activity in the whole room. It is said that 750 lux is the normal limit for the office or normal visual task in the room. The highest limit for the daily room task in the whole zone. In reality the simulation limits can also be fulfil the other legend like 300lux 500lux. Last but not least, the legend also make sense that the occupancy and activity in Chanpin Building is not severe like CRC or other high activity zone.

IES VE Daylight Simulations (Basement) Basement uncover:.

Result Based on the result of the simulation, It is very surprised that even in the basement can reach the legend. Although some space do not reach 750lux, it still can reach about 50% which is about 300lux. The main reason is that the space is not whole basement, it still have half of the area expose to outside area. This make the whole zoneâ&#x20AC;&#x2122;s daylight performance not as bad as the one in the underground. The other reason is that the exposed area which have some windows are exposed to the outside. The area that is exposed to the outside do not covered by any trees or tall building. The environment around basement is school power plant which have low density building area.

IES VE Daylight Simulations (1F) 1F north closed office:.

1F south closed office:.

1F east open office:

Result The first floor area’s simulation shows that some of the area are over 750lux. The result shows that the north and south have severe difference and the east also has these problem. The main reason for the north and south closed office is the windows in both zone do not covered by environment’s tree branch. The daylight can easily get into to the zone. Theses might come to an interesting conclusion, the closer to tree not always to be the good performance zone. The result also shows that the east office also have glare problem. Just like basement the east side of the site is school’s power plant. The building density there is very low. These might be the main reason that caused the glare problem. Based on the simulation, it can also come to conclusion how to separate zone.

IES VE Daylight Simulations (2F) 2F north closed office:

2F south closed office:

2F east open office:

Result Different from the first floor, second floor are all covered by trees. The tree near the site have a big impact on the building. These caused the second floor zone daylight condition are pretty much the same. However, even the daylight performance are the same, it still have a big difference in detail. The limit I set is 750lux. The right hand side's graph shows that the difference still exist in lower legend like 300lux or 500lux. To conclude the daylight simulation, It is a good method to give modeler a clue how to separate zone. The main reason is that the daylight is going to be a big impact on thermal load. In this case, Chanpin building north and south and east are the three different face in the whole simulation. I will used these three to separate zone.

Result with and without ventilation Total deliver energy:

Boiler load before and after vent

Chiller load before and after vent

30 25 20 15

MWH

25 20 15

Result The result I got from IES VE is pretty much the same as EPC. The difference between each two is the result not in cooling and heating design month. I will try talk about this in next chapter. The other thing about the difference I would like to talk about is the result with and without ventilation. It is obvious that in the Atlanta 3A climate the ventilation can actually make the big difference in thermal load. However, the HVAC and ventilation relationship is the difference story. It is said that the ventilation can only help a little reduce for the energy performance in HVAC. The conclusion is that for user who want to use nature ventilation have to consider carefully about the HVACâ&#x20AC;&#x2122;s problem in 3A climate zone. The best way is always adding a sensor to control HVAC when opening the window.

Total Difference (Building load)

KWH/M2

Thermal Load (Heating) 45

Energy Plus Heating Load

40 35

Energy Plus Heating Load (after calibration) EPC Monthly( Before Calibration)

EPC Monthly( After Calibration)

EPC Monthly( After Tech Opt)it1

EPC Monthly( After Tech Opt)it2

EPC Hourly( Before Calibration) EPC Hourly( After Calibration)

EPC Hourly( After Tech Opt)it1

EPC Hourly( After Tech Opt)i2

IES VE Heating Load

Thermal Load (Cooling)

KWH/M2

Energy Plus Cooling Load

Energy Plus Cooling Load (after calibration) EPC Monthly( Before Calibration)

EPC Monthly( After Calibration)

EPC Monthly( After Tech Opt)it1

EPC Monthly( After Tech Opt)it2

EPC Hourly( Before Calibration)

15 10 5 0

EPC Hourly( After Calibration) EPC Hourly( After Tech Opt)it1 EPC Hourly( After Tech Opt)it2 IES VE Cooling Load

Result The cooling load result of EPC coincides with that of EnergyPlus very well. However, the result of IESVE is quite different for the other two. The cooling load fluctuation between summer and winter of the IESVE result is much larger than the EPC and EnergyPlus results. One possible reason is that in IESVE model some internal zones are not connected tightly to adjacent zones, so that there is more heat transfer between the internal zones and the environment through these gaps and this leads to significantly more heating load and less cooling load in winter for the IESVE result.

Total Difference (Direct and indirect deliver energy) HVAC Delievery energy 70 60

EPC Monthly( After Calibration)

KWH/M2

Energy Plus HVAC ENERGY (before calibration) Energy Plus HVAC ENERGY (after calibration) EPC Monthly( Before Calibration)

EPC Monthly( After Tech Opt)it1

EPC Monthly( After Tech Opt)it2 EPC Hourly( Before Calibration)

EPC Hourly( After Calibration) 20

EPC Hourly( After Tech Opt)it1 EPC Hourly( After Tech Opt)it2

IES VE HVAC ENERGY

Other Deliever energy 18

Energy Plus Other ENERGY (before calibration) Energy Plus Other ENERGY (after calibration) EPC Monthly( Before Calibration)

EPC Monthly( After Calibration)

KWH/M2

14 12 10 8 6 4 2 0

EPC Monthly( After Tech Opt)it1 EPC Monthly( After Tech Opt)it2 EPC Hourly( Before Calibration) EPC Hourly( After Calibration) EPC Hourly( After Tech Opt)it1 EPC Hourly( After Tech Opt)it2 IES VE Other ENERGY

Result The result I got from IES VE is pretty much the same as other software. The only difference is that I try to be more precise in IES, the software let me set more specific HVAC detail and other detail in equipment and lighting. The main difference in these is the other deliver energy. The IES It give me the option to set detail equipment in the other zone like stair or restroom The software decrease these zoneâ&#x20AC;&#x2122;s lighting and equipment load, Energy plus set the uniform energy load in these area. That is main reason tat caused the difference. The HVACâ&#x20AC;&#x2122;s difference is caused by the heat recovery in restroom zone. These decrease the energy load of the restroom and caused the difference between IES and energy plus.

Case study(Window open and without open thermal load) 1F OMED closed office:.

Result For this part, I chose the first floorâ&#x20AC;&#x2122;s closed office as my stack opening case study. The main reason that I chose this room is that the daylight performance in this room is not very well. The area have glare problem during the whole year. This might cause the area have temperature difference during the whole year. According to the IES VE result the ventilation in Atlanta is very important for lower the cooling load. The opening I set is the room have seriously impacted by the outside condition. Based on this assumption, I set the outdoor temperature and humidity as sensor and put the opening schedule as variable. With these assumption, the window will open based on the indoor condition and outdoor condition .

Open Ratio(ATL) WINDOWVENTILATIONSCH:Schedule Value [](Hourly) 1.2 1 0.8 0.6 0.4 0.2

07/21 01/04 01/14 01/24 02/03 02/13 02/23 03/05 03/15 03/25 04/04 04/14 04/25 05/05 05/15 05/25 06/04 06/14 06/24 07/04 07/14 07/24 08/03 08/13 08/24 09/03 09/13 09/23 10/03 10/13 10/23 11/02 11/12 11/22 12/02 12/12 12/23

01:00:00 03:00:00 05:00:00 07:00:00 09:00:00 11:00:00 13:00:00 15:00:00 17:00:00 19:00:00 21:00:00 23:00:00 01:00:00 03:00:00 05:00:00 07:00:00 09:00:00 11:00:00 13:00:00 15:00:00 17:00:00 19:00:00 21:00:00 23:00:00 01:00:00 03:00:00 05:00:00 07:00:00 09:00:00 11:00:00 13:00:00 15:00:00 17:00:00 19:00:00 21:00:00 23:00:00 01:00:00

01/01 01/11 01/21 01/31 02/10 02/20 03/03 03/13 03/23 04/02 04/12 04/22 05/03 05/13 05/23 06/02 06/12 06/22 07/03 07/13 07/23 08/02 08/12 08/22 09/02 09/12 09/22 10/02 10/12 10/22 11/02 11/12 11/22 12/02 12/12 12/22

40 35 30 25 20 15 10 5 0 -5 -10 -15

01:00:00 05:00:00 09:00:00 13:00:00 17:00:00 21:00:00 01:00:00 05:00:00 09:00:00 13:00:00 17:00:00 21:00:00 01:00:00 05:00:00 09:00:00 13:00:00 17:00:00 21:00:00 01:00:00 05:00:00 09:00:00 13:00:00 17:00:00 21:00:00 01:00:00 05:00:00 09:00:00 13:00:00 17:00:00 21:00:00 01:00:00 05:00:00 09:00:00 13:00:00 17:00:00 21:00:00

Environment:Site Outdoor Air Drybulb Temperature [C](Hourly)

Result According to the result from energy plus, it is said that most of the time is fulfil the program I set. It is suggest that most of the time should open the window. The opening ratio is also make sense since the outdoor drybulb temperature in most of the time is very high than normal city. It can also shows that the open ratioâ&#x20AC;&#x2122;s form is approximate the drybulb temperature. In this condition, the system suggest that people in the building should always open the window. Since some of the time in Atlanta outdoor temperature is higher than indoor. For example in Aug night time the outdoor temperature is the highest so during this time the system suggest that building should not open any window. On the other hand, like March during the day, the temperature outside is lower than other day in the whole year. So during this time the system suggest the building should add ratio as big as possible.

Open window’s cooling load and uncomfort hour (ATL) Zone Cooling load difference(AL) 400000000 350000000 300000000

[J]

250000000 200000000 150000000 100000000 50000000 0

OMED CLOSED OFFICE 1F IDEAL LOADS AIR SYSTEM:Zone Ideal Loads Supply Air Latent Cooling Energy [J](Without open) OMED CLOSED OFFICE 1F IDEAL LOADS AIR SYSTEM:Zone Ideal Loads Supply Air Latent Cooling Energy [J](With open)

Uncomfort Hour 350 300 250 200 150 100 50 0

OMED CLOSED OFFICE 1F:Zone Thermal Comfort ASHRAE 55 Simple Model Summer or Winter Clothes Not Comfortable Time [hr](WITHOUT OPEN) OMED CLOSED OFFICE 1F:Zone Thermal Comfort ASHRAE 55 Simple Model Summer or Winter Clothes Not Comfortable Time [hr](WITH OPEN)

Result For this part, I start to compare the thermal load between open and unopen window’s condition. It is obvious that open window lower the cooling load. It is also reasonable that the cooling load in summer is obvious decrease. The main reason is that the summer cooling load in Atlanta is higher than any other cities. Temperature during that time is very high. However, opening the window can lower the cooling load, it is surprised that the uncomfort hour do not decrease. For my point of view the main reason is that the comfort hour is decided by different kind of criteria. Not only the temperature but also the relative humidity. Since the increase hour is in winter time, the opening can improve energy performance but it cannot make people feel comfortable during winter.

01/01 01/10 01/20 01/29 02/08 02/18 02/27 03/09 03/19 03/28 04/07 04/16 04/26 05/06 05/15 05/25 06/04 06/13 06/23 07/02 07/12 07/22 07/31 08/10 08/20 08/29 09/08 09/17 09/27 10/07 10/16 10/26 11/05 11/14 11/24 12/03 12/13 12/23

01:00:00 16:00:00 07:00:00 22:00:00 13:00:00 04:00:00 19:00:00 10:00:00 01:00:00 16:00:00 07:00:00 22:00:00 13:00:00 04:00:00 19:00:00 10:00:00 01:00:00 16:00:00 07:00:00 22:00:00 13:00:00 04:00:00 19:00:00 10:00:00 01:00:00 16:00:00 07:00:00 22:00:00 13:00:00 04:00:00 19:00:00 10:00:00 01:00:00 16:00:00 07:00:00 22:00:00 13:00:00 04:00:00 01/01 01/10 01/20 01/29 02/08 02/18 02/27 03/09 03/19 03/28 04/07 04/16 04/26 05/06 05/15 05/25 06/04 06/13 06/23 07/02 07/12 07/22 07/31 08/10 08/20 08/29 09/08 09/17 09/27 10/07 10/16 10/26 11/05 11/14 11/24 12/03 12/13 12/23

Open Ratio(SF) WINDOWVENTILATIONSCH:Open Ratio (Hourly)

1.2

0.8

0.6

0.4

0.2

Environment:Site Outdoor Air Drybulb Temperature [C](Hourly)

Result To finish the case study, I tried in different climate. The area I tried is San Francisco. The reason I tried SF is because the marine climate. During summer time in SF the temperature is not like Atlanta it is cold and cool. During the whole year the climate is comfortable and dry. According to the result, it is clear that the system open the window whole year, the main reason is that the climate in CA is marine climate. The temperature in summer time is still cool as fall time in Atlanta. It is also good to test if the climate area in CA is good for opening window to reduce cooling load or it will cost more heat load even in the summer time. For this I will test in the next section.

Open windowâ&#x20AC;&#x2122;s cooling load and uncomfort hour (SF) Load difference in window open and closed 2E+10 1.5E+10 1E+10 5E+09 0

OMED CLOSED OFFICE 1F IDEAL LOADS AIR SYSTEM:Zone Ideal Loads Supply Air Latent Cooling Energy [J](Monthly) OMED CLOSED OFFICE 1F IDEAL LOADS AIR SYSTEM:Zone Ideal Loads Supply Air Total Cooling Energy [J](Monthly) OMED CLOSED OFFICE 1F IDEAL LOADS AIR SYSTEM:Zone Ideal Loads Supply Air Total Heating Energy [J](WITHOUT OPEN) OMED CLOSED OFFICE 1F IDEAL LOADS AIR SYSTEM:Zone Ideal Loads Supply Air Total Heating Energy [J](With open)

Uncomfort Hour 350 300 250 200 150 100 50 0

OMED CLOSED OFFICE 1F:Zone Thermal Comfort ASHRAE 55 Simple Model Summer or Winter Clothes Not Comfortable Time [hr](without open) OMED CLOSED OFFICE 1F:Zone Thermal Comfort ASHRAE 55 Simple Model Summer or Winter Clothes Not Comfortable Time [hr](with open)

Result According to the result, it is not very surprised that the cooling load did not have any drastically change during the whole year. The main reason like I said the summer temperature in CA is lower than normal climate area. So when the time which other area is good to open the window CA have different story. Opening will not improve the cooling load but it will increase the heat load because the outdoor temperature is too cold. According to this, the uncomfort hour increase seems reasonable. People will feel too cold and too dry during the window opening time. That is also the main reason that CA always need different strategy to solve climate problem like mix zone air flow air exchange or daylighting to increase indoor temperature in the same time during ventilation process.

Stack Open from IES VE Open schedule

Window opening in IES During the setting and modify in IES, I discovered that the software has limitation on open ratio. The stack open cannot be modified by formula. Though the window open can still be opened by boundary condition, it still cannot control the same way energy plus. Based on this limitations, I set the window fully open on particular condition which I use the same condition in energy plus. However, this time I also add another condition which is the relative humanity ratio. When the interior relative humanity ratio is greater than outdoor relative humanity ratio, the window will fully open. According to this, the window will open more often than the one I set in energy plus. The main reason is that the weather in Atlanta sometime get very humid. I will get the result on the next page.

Stack Open from IES VE Window open energy input and output

Result According to the result, I got from IES VE the window opening is based on energy consumption form. Since I looked up the introduction in IES, the only number that can display the stack open is the MacroFlo external ventilation. The result is heat gain based. It is said when the outside temperature is lower than indoor temperature or the indoor temperature is higher than 18 degree, people will open the window (fully). During this time, the window open will cause the area heat gain increase. From the graph it is very oblivious that the outdoor air temperature flow graph show totally different graph that heat gain graph. When outdoor temperature is higher than indoor or 18 degree most of the MacroFlo graph is going to be high as well. These also show that the simulation result can be trusted.

Stack Open thermal load from IES VE Open schedule

Stack open Closed Office Thermel load 16 14

kWh/m2

12 10 8 6 4 2 0

IES VE closed office Cooling Load(without open)

IES VE closed office Cooling Load(with open)

Stack open Closed Office Thermel load 14 12

kWh/m2

10 8 6 4 2 0

IES VE closed office Heating Load (without open)

IES VE closed office Heating Load (with open)

Result For the thermal load part, I tried to compare the energy plus ‘s result with IES ‘s result. The result shows that most of the cooling load is higher than energy plus’s result. The main reason for that is the metrics’ differences. Energy plus’s result is fully control by the stack open ratio. This means that the window sometimes will open but not fully open like IES’s result. The other things also shows that the IES result is not as trustable as energy plus since the window is only been set as fully closed. The result will absolute higher than energy plus in both cooling and heating load. To warp it up, I personally prefer energy plus’s result. The main reason is that the result is fully control and closer to reality situation which means in reality people are not going to accept the window fully open. With the open ratio’s formula, it do make the result from energy plus more correct.

Sum up: IES VE and Energy Plus Stack Open Stack open Closed Office Thermel load 16 14

kWh/m2

12 10 8 6 4 2 0

IES VE closed office Cooling Load(without open)

IES VE closed office Cooling Load(with open)

Zone Cooling load difference(AL) 400000000 350000000 300000000

[J]

250000000 200000000 150000000 100000000 50000000 0

Warp it up: Perspective view for the Chapin Building Daylight and thermal load

1F daylight(LUX)

2F daylight(LUX)

Total Cooling Need 4E+09 3.5E+09 3E+09

2.5E+09 2E+09 1.5E+09 1E+09 500000000 0

Result Based on the result I got from the simulation of all other software, I discovered that the result I can improve is mostly concerned on the cooling load and heating load. I tried to get the reason that why the cooling need in our building is a very big issue. Based on the result from IES VE and energy plus, I discovered that the tree cover is a very big issue in my building. On the second floor most of the area is covered by leaves and branches but on the first floor it is only tree’s trunk. Since landscape near Chapin Building is more ‘conifer like’. This caused the second floor cooling load is lower than the first floor. Not to say the building covered by surrounding building’s shadow. These two reasons make second floor daylighting is not enough. I will assumed that the daylighting is kind of big reason for the thermal load.

Daylight and thermal load

1F daylight(LUX)

2F daylight(LUX)

Total Heating Need 2E+10

1.5E+10 1E+10 5E+09 0

Result On the other hand, I still test the heating load for different floor. This also proof the assumption for my result. Since the second floor is covered by treeâ&#x20AC;&#x2122;s leaves, the heating need is higher than the first floor. With these two I will tried to solve the daylighting problem. Not only to improve daylighting and make it more general but also make the indoor area get more thermal temperature. Last but not least, I think the other way to solve the indoor heating need is to lower the first floor window ratio. The first floor actually get more sunlight than second floor. Based on this result, I think mini the window ratio in the first floor can probably solve the problem too. The other one is to make the first floor window open ratio less than second floor since the both floor do not concern the shading condition.

Light Shelf Lighting Improvement Before adding light shelf

After adding light shelf

Result Based on the simulation result from DIVA, the strategy I did for solving the daylight problem is adding light shelf. This action actually make the daylighting more general and I assume the action will also make the indoor heating and cooling need be more general. The other things is that the light shelf also lower the in glare problem. Based on the result, before adding the light shelf the indoor daylighting actually are going to have some glare problems however, after the result the glare problem do lower a little bit.

Fully stack open Thermal Load Comparison

Thermal Load (Cooling) before stack open 1.4E+09 1.2E+09 1E+09 800000000 600000000 400000000 200000000 0

Thermal Load (Cooling) After stack open 4000000 3500000 3000000 2500000 2000000 1500000 1000000 500000 0

Result In the former result I do see the stack open really help the indoor cooling load a lot. In that condition, I only go with one zone and one window. This time I start to improve it to the whole building. This result also based on the open ratio formula I used on the energy plus stack opening method. The only things I do feel a little bit strange is that the cooling load in August to October do not have any difference. I think the main reason is that during that the outdoor temperature do not fulfil the formulaâ&#x20AC;&#x2122;s boundary condition. This make the system chose to not open the window. During that time it is also Atlanta's raining season. I think that make the boundary condition do not fulfill the assumption. The other result seems reasonable , it do improve the thermal cooling load.

The things I had learned

1. In energy simulation point of view: For a medium size building with regular partitions like Chapin, it is good and quick to merge adjacent rooms with the same function into one thermal zone. This will simplify the building of the model and reduce the amount of computation required greatly. As long as heating load and cooling load donâ&#x20AC;&#x2122;t exist simultaneously in two rooms, the merging of them will result in little inaccuracy. 2. The other quick view on energy simulation: For a building with a large inner zone and a large internal heat gain, there is a large potential for cooling with ventilation. From the IESVE result, we can learn that if we ventilate the building with fresh air from September to June of the next year, the cooling load can be decreased significantly. Therefore, for a building with obvious difference between inner zone and peripheral zone, two separate HVAC systems can be employed to achieve the lowest energy consumption. 3. The building innovation can be easy and it also can be complicated. Depend on the usersâ&#x20AC;&#x2122; preference or the budget limits. The trade off might be the more energy performance or efficient the building will be the less design uses that building can be used( Like ceiling down to floor window, high ceiling etc.) 4. Building in Atlanta can easily reach energy efficient just open window let the wind air flow into the house. However, not all U.S state can use the same strategies as Atlanta. Like my simulation in SF. Stack is a very good and cheap strategy to solve the high thermal load problem but it also have to make sure the surrounding weather. 5.PV and other BEM system are not the only case that be used for the building to reach net zero or HPB. The trade off for these two are either the price or install fee.. However, the both of them are essential for the the performance and energy efficient, these can encounter a trade off that the price and the performance part. 6.Some of the result are effected by the activity in the building. This is very clear when I start to do the calibration, However, not always the building will encounter that kind of activity in the whole year. The schools schedule are also a big impact on the building. In the future, the best way to optimize the performance is including the summer and winter vacation. Make good use of these period of time.

Content : Project overview and zoning

1-2

TAS Daylight Simulations

3 - 12

TAS Outcome and Zone Distribute and Trouble Shoot

13 - 16

TAS Outcome NULL and Internal wall Difference

17 - 19

Null Wall and Internal Wall Impact in TAS TAS Result Combine

20 21 - 22

TAS Annual Building Load

TAS Building Load and Energy Plus EPC Comparison

TAS Building Deliver Energy and Energy Plus EPC Comparison

TAS Building Optimize Simulation – Daylight and Lighting

26 - 29

TAS Building Optimize Simulation – Ventilation and Infiltration

30 - 34

TAS Operable window study: The ELA in TAS

TAS Operable window HVAC function control

36 - 38

TAS OPT result compare (Cooling and Heating)

39 - 40

TAS / EPC / Energy Plus / IES

41 - 43

TAS Simulations

TAS Simulation In the next part case study, I start to use TAS to simulate the same building I did in the first part. I will try to discover the differences and pro and cons between the four software. I discovered that in TAS the geometry building is very difference. It can easily to build up the complicated architecture feature in the whole software. The features can be plenums or sliding roof last but least the shading. These feature can easily impact the simulation result either the cooling load or heating load. The other feature that TAS can do is that it can easily build up construction group. These group can tried to make the simulation model similar to the real model. It can also make user easily distinguish the construction agenda to make operable or not.

TAS Simulations Zone Name and Position First floor:.

Second floor:.

Basement:.

In the zoning part, I use the same zone position as E+ and other software. However, the one part is different than other software. In TAS it ask me to distinguish the interior wall or it can also be â&#x20AC;&#x2DC;NULLâ&#x20AC;&#x2122; These two can be difference in the simulation out outcome. I will come back to these in the later part. These also happened to the other construction agenda either the exterior wall or the interior ceiling.

TAS Daylight Simulations (Daylight Factor) First floor:.

Second floor:.

Result According to the daylight factor result, the result kind of like the same as the outcome from IES or DIVA. The legend I set for the factor is based on the LUX and normal working plane. The result show that some of the room solar gain might be the main issue. The other things for mine surprised is that the null interior wall. The wall is stand for separate zone but not for blocking or reflecting the daylight . It is obvious that these might have some impact on the solar gain counting in the final result. Last but not least about the result, the tree model in the TAS model can be improve. Based on the result I got from the former report, the tree has a big impact on the solar gain. Not only it block the sunlight which is main cooling load in my building but also it create the shading in sun rising time. These two can impact the result. Instead of giving tree special transparency, TAS using the same strategy as E+ to define treeâ&#x20AC;&#x2122;s shading.

Daylight Simulations Legend

TAS Daylight Simulations (Basement)

TAS Daylight Simulations Report (1F)

(Units: Lux)

1F closed office:.

Overall Daylight Results Minimum Point Lux 252.07 Level: Maximum Point Lux 3117.92 Level: Average Lux Level: 693.70 Uniformity (Min lux / 0.36 Avg Lux):

Material Properties Building Element Name Internal Floor Internal Floor/Internal Ceiling External Wall w3-down-frame w3-down-pane w3-up-frame w3-up-pane w4-down-frame w4-down-pane w4-up-frame w4-up-pane w1-down-frame w1-down-pane w1-up-frame w1-up-pane d1-frame d1-pane d1 window-frame d1 window-pane fd1-frame fd1-pane FD1 Window-frame FD1 Window-pane

Area (m²) 246.05 245.87 242.59 1.19 5.18 1.09 4.40 0.36 1.43 0.36 1.43 1.34 6.85 1.34 6.85 0.39 2.67 0.19 0.83 0.49 4.93 0.23 1.09

Minimum Point 0.20 Daylight Factor: Maximum Point 2.53 Daylight Factor: Average Daylight 0.56 Factor: % of Grid Points With 0.22 a DF Above 2%:

Reflectance Outer Inner 0.80 0.30 0.80 0.30 0.50 0.50 0.50 0.50 0.17 0.17 0.50 0.50 0.17 0.17 0.50 0.50 0.17 0.17 0.50 0.50 0.17 0.17 0.50 0.50 0.17 0.17 0.50 0.50 0.17 0.17 0.50 0.50 0.50 0.50 0.50 0.50 0.17 0.17 0.50 0.50 0.17 0.17 0.50 0.50 0.17 0.17

Transmittance Outer Inner 0.64 0.64 0.64 0.64 0.64 0.64 0.64 0.64 0.64 0.64 0.64 0.64 0.64 0.64 0.64 0.64 0.64 0.64

Result According to the result I got from the TAS daylight report, the average LUX level for one of the first floor main zone is 653.7 which is good for the working area. It is interesting that TAS can also tell you the each surface lighting condition which give me a clue that which window or surface’s material cause the daylight problem in the whole model. In the first floor closed office goes to the window that facing the power plant. The main reason is that these two window do not blocked by any trees’ shading.

TAS Daylight Simulations Report (1F)

(Units: Lux)

1F open office:.

Overall Daylight Results Minimum Point Lux 395.64 Level: Maximum Point Lux 2585.84 Level: Average Lux Level: 1239.00 Uniformity (Min lux / 0.32 Avg Lux):

Minimum Point 0.32 Daylight Factor: Maximum Point 2.10 Daylight Factor: Average Daylight 1.01 Factor: % of Grid Points With 1.90 a DF Above 2%:

Material Properties Reflectance Building Element Name

Transmittance

Area (mÂ˛)

Outer

Inner

Outer

Inner

Internal Floor

137.43

0.80

0.30

Internal Floor/Internal Ceiling

137.41

0.80

0.30

External Wall

147.81

0.50

w1-down-frame

1.12

0.50

w1-down-pane

5.71

0.17

0.64

w1-up-frame

1.12

0.50

w1-up-pane

5.71

0.17

0.64

w3-down-frame

1.58

0.50

w3-down-pane

6.91

0.17

0.64

w3-up-frame

1.45

0.50

w3-up-pane

5.87

0.17

0.64

d2-frame

0.42

0.50

d2-pane

3.92

0.50

D2 Window-frame

0.25

0.50

D2 Window-pane

1.32

0.17

0.64

Result The first floor open office result is very surprised for me the average LUX goes to 1239. These number make me a little surprised. The main reason is caused by the east side low height power plant and no trees shading. With these two reason and the zone is facing south. Combine these two reason the result shows that the 40% of the area is going to be overheated by the solar gain.

TAS Daylight Simulations Report (2F)

(Units: Lux)

2F closed office:.

Overall Daylight Results Minimum Point Lux 299.76 Level: Maximum Point Lux 2048.27 Level: Average Lux Level: 750.79 Uniformity (Min lux / 0.40 Avg Lux):

Minimum Point 0.24 Daylight Factor: Maximum Point 1.66 Daylight Factor: Average Daylight 0.61 Factor: % of Grid Points With a 0.00 DF Above 2%:

Material Properties Reflectance Building Element Name

Transmittance

Area (mÂ˛)

Outer

Inner

Outer

Inner

Internal Floor

137.43

0.80

0.30

Internal Floor/Internal Ceiling

137.41

0.80

0.30

External Wall

147.81

0.50

w1-down-frame

1.12

0.50

w1-down-pane

5.71

0.17

0.64

w1-up-frame

1.12

0.50

w1-up-pane

5.71

0.17

0.64

w3-down-frame

1.58

0.50

w3-down-pane

6.91

0.17

0.64

w3-up-frame

1.45

0.50

w3-up-pane

5.87

0.17

0.64

d2-frame

0.42

0.50

d2-pane

3.92

0.50

D2 Window-frame

0.25

0.50

D2 Window-pane

1.32

0.17

0.64

Result The second floor closed office is another difference story in these case. Base on the result it is very clear that the null interior wall do not exist impact on the simulation. Since the second floor closed office has a lot of separate interior null separate wall. Based on the result the reflection do not get any impact on the daylight performance. These might caused a lot impact on the load performance. I will talk more in later chapter.

TAS Daylight Simulations Report (2F)

(Units: Lux)

2F open office:.

Overall Daylight Results Minimum Point Lux 418.85 Level: Maximum Point Lux 2534.37 Level: Average Lux Level: 1135.42 Uniformity (Min lux / 0.37 Avg Lux):

Minimum Point 0.34 Daylight Factor: Maximum Point 2.06 Daylight Factor: Average Daylight 0.92 Factor: % of Grid Points With 0.17 a DF Above 2%:

Material Properties Reflectance Building Element Name

Transmittance

Area (mÂ˛)

Outer

Inner

Outer

Inner

Internal Floor/Internal Ceiling

226.52

0.80

0.30

Internal Ceiling

226.65

0.80

0.30

External Wall

244.41

0.50

w3-down-frame

1.19

0.50

w3-down-pane

5.18

0.17

0.64

w3-up-frame

1.09

0.50

w3-up-pane

4.40

0.17

0.64

w1-down-frame

1.79

0.50

w1-down-pane

9.14

0.17

0.64

w1-up-frame

1.79

0.50

w1-up-pane

9.14

0.17

0.64

w2-down-frame

0.17

0.50

w2-down-pane

0.60

0.17

0.64

w2-up-frame

0.17

0.50

w2-up-pane

0.60

0.17

0.64

w4-down-frame

0.18

0.50

w4-down-pane

0.71

0.17

0.64

w4-up-frame

0.18

0.50

Result Same as the first floor opened office. The second floor opened office is clearly overheat. The main reason is also the same as the first floor . However, the second floor do get a little bit less sunlight than the first. The main reason for that is caused by the treesâ&#x20AC;&#x2122; branch next to them. And the other reason that that the zone do not separated by any interior wall. The light will diffuse in the whole zone. .

TAS Daylight Simulations Report (B1)

(Units: Lux)

Overall Daylight Results Minimum Point Lux 0.00 Level: Maximum Point Lux 4.78 Level: Average Lux Level: 2.09 Uniformity (Min lux / 0.00 Avg Lux):

Minimum Point 0.00 Daylight Factor: Maximum Point 0.00 Daylight Factor: Average Daylight 0.00 Factor: % of Grid Points With a 0.00 DF Above 2%:

Overall Daylight Results Minimum Point Lux 0.01 Level: Maximum Point Lux 6.82 Level: Average Lux Level: 2.07 Uniformity (Min lux / 0.00 Avg Lux):

Minimum Point 0.00 Daylight Factor: Maximum Point 0.01 Daylight Factor: Average Daylight 0.00 Factor: % of Grid Points With a 0.00 DF Above 2%:

Overall Daylight Results Minimum Point Lux 0.74 Level: Maximum Point Lux 14.57 Level: Average Lux Level: 3.44 Uniformity (Min lux / 0.22 Avg Lux):

Minimum Point 0.00 Daylight Factor: Maximum Point 0.01 Daylight Factor: Average Daylight 0.00 Factor: % of Grid Points With a 0.00 DF Above 2%:

TAS Daylight Simulations Report (1F other zone)

(Units: Lux)

Overall Daylight Results Minimum Point Lux 321.60 Level: Maximum Point Lux 663.47 Level: Average Lux Level: 560.19 Uniformity (Min lux / 0.57 Avg Lux):

Minimum Point 0.26 Daylight Factor: Maximum Point 0.54 Daylight Factor: Average Daylight 0.45 Factor: % of Grid Points With a 0.00 DF Above 2%:

Overall Daylight Results Minimum Point Lux 513.96 Level: Maximum Point Lux 2481.18 Level: Average Lux Level: 1189.12 Uniformity (Min lux / 0.43 Avg Lux):

Minimum Point 0.42 Daylight Factor: Maximum Point 2.01 Daylight Factor: Average Daylight 0.96 Factor: % of Grid Points With a 0.74 DF Above 2%:

Overall Daylight Results Minimum Point Lux 267.75 Level: Maximum Point Lux 2518.76 Level: Average Lux Level: 633.48 Uniformity (Min lux / 0.42 Avg Lux):

Minimum Point 0.22 Daylight Factor: Maximum Point 2.04 Daylight Factor: Average Daylight 0.51 Factor: % of Grid Points With a 0.26 DF Above 2%:

TAS Daylight Simulations Report (2F other zone)

(Units: Lux)

Overall Daylight Results Minimum Point Lux 363.00 Level: Maximum Point Lux 681.84 Level: Average Lux Level: 593.29 Uniformity (Min lux / 0.61 Avg Lux):

Minimum Point 0.29 Daylight Factor: Maximum Point 0.55 Daylight Factor: Average Daylight 0.48 Factor: % of Grid Points With a 0.00 DF Above 2%:

Overall Daylight Results Minimum Point Lux 1042.02 Level: Maximum Point Lux 3474.49 Level: Average Lux Level: 2335.52 Uniformity (Min lux / 0.45 Avg Lux):

Minimum Point 0.85 Daylight Factor: Maximum Point 2.82 Daylight Factor: Average Daylight 1.90 Factor: % of Grid Points With a 48.96 DF Above 2%:

Overall Daylight Results Minimum Point Lux 310.26 Level: Maximum Point Lux 805.07 Level: Average Lux Level: 470.48 Uniformity (Min lux / 0.66 Avg Lux):

Minimum Point 0.25 Daylight Factor: Maximum Point 0.65 Daylight Factor: Average Daylight 0.38 Factor: % of Grid Points With a 0.00 DF Above 2%:

TAS Daylight Simulations Sum Up First floor:.

Second floor:.

Basement:. Result The trees near the building their leaf part are in the second floor. These might have caused the reason that the second floor’s daylight is lesser than the first floor. The first floor only covered by surrounding building. However, the surrounding buildings are not very closed to the site. Each of them have more than 3 meter’s distance. These is main reason that some first floor’s edge have overheated by daylight. Last but least, for the second floor the open office in the east’s edge daylight is caused by the uncovered of the environment.

TAS Outcome and Zone Distribute and Trouble Shoot First Iteration:.

Final Iteration:.

Result Come to the result in TAS simulation, I got two different result. The first oneâ&#x20AC;&#x2122;s cooling load in holiday period is way lower than final one which is the one is closer to the result I got from the other software. Based on the study the problem might caused by the internal condition and the zoning problem in the interior area. The first iteration, I applied the whole same condition to the whole building on the other hand the final iteration I used different internal condition to different zone. The other main issue is that the internal wall for separate the zone or room. These two might be the reason. I will explain in later chapter.

TAS Outcome and Zone Distribute and Trouble Shoot First Iteration:.

Cooling Load Comparison

60000

50000

40000

30000

20000

10000

1, 1 10, 22 20, 19 30, 16 40, 13 50, 10 60, 7 70, 4 80, 1 89, 22 99, 19 109, 16 119, 13 129, 10 139, 7 149, 4 159, 1 168, 22 178, 19 188, 16 198, 13 208, 10 218, 7 228, 4 238, 1 247, 22 257, 19 267, 16 277, 13 287, 10 297, 7 307, 4 317, 1 326, 22 336, 19 346, 16 356, 13

Before Cooling Load (W)

After Cooling Load (W)

Zone Internal Condition Change in Holiday Season:.

Trouble Shoot To solve the problem I first try to use the different internal condition in two main zone. The one is closed office and the other is open office. The main issue for the result happened in summer time which I set for the system to count it as the school holiday (5/1-8/17) and the spring or fall break. These season caused the cooling loadâ&#x20AC;&#x2122;s difference. The two different internal condition during the holiday which I remodify have different infiltration since the open office has ability to solve the cross ventilation the other do not. Other sensible load remain the same but the open office is going to be little big than closed office since there is school activity in these building during holiday.

TAS Outcome NULL and total zone After sperate different condition zone in School Holiday Total zone Heat Transfer :.

Before sperate different condition zone in School Holiday Total zone Heat Transfer :.

After Heat Transfer- Before Heat Transfer 20000 15000 10000 5000 -5000 -10000

1, 1 12, 3 23, 5 34, 7 45, 9 56, 11 67, 13 78, 15 89, 17 100, 19 111, 21 122, 23 134, 1 145, 3 156, 5 167, 7 178, 9 189, 11 200, 13 211, 15 222, 17 233, 19 244, 21 255, 23 267, 1 278, 3 289, 5 300, 7 311, 9 322, 11 333, 13 344, 15 355, 17

-15000 -20000 -25000 -30000 -35000

Result The main issue I found in TAS is the NULL interior wall and the normal interior wall difference. In TAS I founded that it will default count heat transfer between zone to zone. The null in TAS is like a very thing wall in heat transfer part it do not exist however, in the solar gain part it will count the solar gain individually and divide its area. Back to the heat transfer, I tried to minus the before separate the zone and after separate the zone. I found out that the transfer gain might be one of the reason that the difference. It also shows that the mine strategy is correct.

TAS Outcome NULL and total zone (other strategy) After sperate different condition zone in School Holiday Total zone Heat Transfer :.

After Heat Transfer- Before Heat Transfer 30000 20000 10000

-10000

1, 1 11, 12 21, 23 32, 10 42, 21 53, 8 63, 19 74, 6 84, 17 95, 4 105, 15 116, 2 126, 13 136, 24 147, 11 157, 22 168, 9 178, 20 189, 7 199, 18 210, 5 220, 16 231, 3 241, 14 252, 1 262, 12 272, 23 283, 10 293, 21 304, 8 314, 19 325, 6 335, 17 346, 4 356, 15

-20000 -30000 -40000 After Heat Transfer- Before Heat Transfer After Adding Internal Wall Heat Transfer- Before Heat Transfer

Strategy Thermal Load Comparison 12 10

kWh/m2

8 6 4 2 0

Change Internal Condition Heating Load

Change Internal Condition Cooling Load

After Adding internal wall Heating Load

After Adding internal wall Cooling Load

Result To double check my strategy, I remodify the internal wall part from null to normal internal wall and the internal condition is the one in first iteration which the whole zone stay the same during the holiday. It is very surprised that the heat transfer in the summer time stay the same as the strategy which change the different internal zone condition. The only difference is the heating load. The internal wall conserved the each roomâ&#x20AC;&#x2122;s heat. It make the cooling load stay low during the winter time.

TAS Outcome NULL and Internal wall Difference With Null Wall Solar Gain:.

Lower Null Wall Solar Gain

Result The result I output in this slide is about the nullâ&#x20AC;&#x2122;s use in TAS. The null allow user using TAS to separate open floor plan area into different zone. Since some of the area might have different Solar Gain based on different orientation. TAS will count the null area individually and then divide the null area. Based on this method, I output different solar gain. The figure show that the with lower null wall which means less divided by the area the solar gain is much bigger than the one have less null wall area. To conclude that the null not only impact the load but also the solar gain.

TAS Outcome NULL and Internal wall Difference Lower Null Wall Solar Gain

Turn Null Wall to internal wall Solar Gain

Result The other I would like to test is that if the internal solid wall have the same function as the null wall in solar gain counting part. Based on the result, it is clear to see that both strategy is the same. The null wall and internal wall have the same function for setting system to count the solar gain. Both this two can be use to define open plan in simulation. The solar gain counting will only affected by the sperate area but not for the wall condition or material.

Lower Null Wall Air Movement Gain

Turn Null Wall to internal wall Air Movement Gain

800

Air Movement Gain Comparison

600 400 200

-200

1, 1 10, 16 20, 7 29, 22 39, 13 49, 4 58, 19 68, 10 78, 1 87, 16 97, 7 106, 22 116, 13 126, 4 135, 19 145, 10 155, 1 164, 16 174, 7 183, 22 193, 13 203, 4 212, 19 222, 10 232, 1 241, 16 251, 7 260, 22 270, 13 280, 4 289, 19 299, 10 309, 1 318, 16 328, 7 337, 22 347, 13 357, 4

-400 -600 -800

Wall Air Movement Gain (W)

Null Air Movement Gain (W)

Result The other things I would like to test is to turn NULL wall into internal wall. The meaning of this test is to check if internal wall do effect the heat transfer and air movement gain in the whole zone. The result shows that the air movement do affected by the internal solid wall. According to the result with solid internal wall, the air movement gain drastically goes down and become very smooth. To sum up these comparison, the internal wall has a great impact on the whole buildingâ&#x20AC;&#x2122;s load calculation. That also the main difference that TAS is different from others.

Null Wall and Internal Wall Impact in TAS Null Wall

Internal Wall

Result To warp it up one of the main difference between the null wall and normal solid internal wall, the main difference is the one agenda called AIR MOVEMENT GAIN. This agenda which means the heat in the interior area from one are move to another areaâ&#x20AC;&#x2122;s gain. The reason caused the heat transfer is the temperature difference or other difference in the whole building. The AIR MOVEMENT GAIN mainly happened in building which inside the building heat transfer caused by air. In order to make the simulation correct, I got two way based on my former study. One is to make sure the 3D model match the realistic condition which means define the right place to put solid wall or null wall. The other ways to do it is to separate different zone condition which means define more detail or finesse internal condition. To sum up these two strategies, the make sure the system have difference in each zone in different timing period. Last but not least, build the model as real as possible.

TAS Result Combine Air Movement Gain 800 600 400 200

-200

-400 -600 -800

Day,Hour Air Movement Gain Before (W)

Air Movement Gain After (W)

Infiltration and Ventilaiton 10000

-10000

1, 1 11, 5 21, 9 31, 13 41, 17 51, 21 62, 1 72, 5 82, 9 92, 13 102, 17 112, 21 123, 1 133, 5 143, 9 153, 13 163, 17 173, 21 184, 1 194, 5 204, 9 214, 13 224, 17 234, 21 245, 1 255, 5 265, 9 275, 13 285, 17 295, 21 306, 1 316, 5 326, 9 336, 13 346, 17 356, 21

-20000

-30000

-40000

-50000 Air Movement Gain After (W)

Inf/Vent Gain (W)

Result After solving the main difference, I tried to find out what caused the difference between the first iteration’s cooling load and the final one’s cooling load. It turns out that caused the difference is not only the air movement gain but also the infiltration. In the former model, I did not set any infiltration in the model which is not totally correct. After changing the holiday’s internal condition to different one, I apply 0.33 ach infiltration to the one way ventilation area and apply 0.66 ach to two way open window zone. Although the number might not be very precise, it can give me a clue that how these two going to be big impact on the model.

TAS Result Combine

Cooling Load Comparison 60000

50000

40000

30000

20000

10000

Before Cooling Load (W)

After Cooling Load (W)

Result After combining two gain (air movement gain and infiltration gain), I discovered that the cooling load in first iteration is the same as the final one. Although the main issue is in holiday period, it seems that the other month are still a problem for the first iteration. Some of the gain might be negative and some of them might be positive with combine these two number and then get the final one. The other issue is the negative parameter in the gain. I assumed that the reason for that is caused by the internal zone conditionâ&#x20AC;&#x2122;s difference and for the infiltration it is normal that some air in the room might get through the leakage gap in the window and caused the negative gain.

TAS Annual Building Load TAS Monthly Load BreakDown 10.00 9.00 8.00

kW·h/m²

7.00 6.00 5.00 4.00 3.00 2.00 1.00 0.00

Heating

Cooling

Humidify

Dehumidify

Lighting

Occupancy

Equipment

Internal (L,O,E)

Solar

TAS Annual Load Breakdown 90.00 80.00 70.00

kW·h/m²

60.00 50.00 40.00 30.00 20.00 10.00 0.00

Result The final result I got from TAS seems very reasonable. The solar gain in the load break down got the 2th load in the whole years which is not a very big surprised based on the daylight calculation in the former report. It is clear to see that even though the internal sensible load during holiday is very low the cooling load still impacted by the out door temperature and the solar gain. TAS is very good at dynamic simulation which can help me see the breakdown of the whole simulation and give use a clue that which one affect building the most.

TAS Building Load and Energy Plus EPC Comparison Thermal Load Cooling Comparison 16 14

kW·h/m²

12 10 8 6 4 2 0

TAS Cooling Load

Energy Plus Cooling Load

EPC Hourly( After Calibration)

IES VE Cooling Load

Thermal Load Heating Comparison 14 12

kW·h/m²

10 8 6 4 2 0

TAS Heating Load

Energy Plus Heating Load (after calibration)

EPC Hourly( After Calibration)

IES VE Heating Load

Result After all the former research the result shows that the cooling and heating load form is very similar with other software.. The heating load based on the heat transfer gain which improve the cooling load in the summer the heating load is going to be lesser than others. On the cooling load part, the only difference is in summer, the infiltration and ventilation I set in the internal condition make the cooling load (JULY and AUGUST) lesser and smooth in these period.

TAS Building Deliver Energy and Energy Plus EPC Comparison HVAC Energy Consumption 40 35 30

kwH/m2

25 20 15 10 5 0

TAS HVAC ENERGY

EPC Hourly HVAC ENERGY( After Calibration)

Energy Plus HVAC ENERGY (after calibration)

Other Energy Consumption 16 14 12

kwH/m2

10 8 6 4 2 0

TAS OTHER ENERGY

EPC Hourly OTHER ENERGY

Energy Plus OTHER ENERGY

Result Since building normal district heating and cooling system in TAS is going to be a pain, I assumed my building in TAS has its own cooling and heating system. This assume works as same as EPC hourly did. The COP in this strategy have to be assumed an abstract number. The number I go with for cooling COP is 2.3 and heating going to be 3.6. Based on the result graph it is clear to see that the graph works perfectly the same as EPC. I assumed that the reason for that is because they use the same strategy for counting the COP. On the other energy part the graph shows difference in summer holiday. The main reason that caused this problem is that the holiday periodâ&#x20AC;&#x2122;s condition is different in infiltration and it also separate in to different zone to solve the air movement problem.

TAS Building Optimize Simulation – Upper Hang Shading

Shading Comparison 10 9 8

kWh/m2

7 6 5 4 3 2 1 0

Original Cooling Load

Add Shading Cooling Load

Result For the rest of the slide, I will use TAS’s supreme part which is merging model rom model to make the optimization in TAS. The first one I used I the upper shading in the upper window. Based on the result from the annual load breakdown, the solar gain is the second big impact in the simulation. To solve these problems I tried to ran a new simulation include whole upper shading on the building façade. The result shows that adding shading is efficient to help the building during summer to lower its cooling load. It also shows a simple way to get down load.

TAS Building Optimize Simulation â&#x20AC;&#x201C; Upper Hang Shading Solar Gain Comparison 35000 30000 25000 20000 15000 10000 5000

Before adding shade Solar Gain (W)

After adding shade Solar Gain (W)

Adding Shading Air Movement Gain Comparison 800 600 400 200

-200

-400 -600 -800 Before adding shading Air Movement Gain (W)

After adding shading Air Movement Gain (W)

Result On the other hand I still extend the study to test if the shading do what kind of impact on the model. The result shows that the main things is the solar gain. The solar gain do have clear impacted by the shading. According to the result, the solar gain do become lesser than before. The other impact is the air movement gain. Although the air movement gain do have be affected by the shading, the air movement did not have a big affect by the shading. Based on this , it is clear that the radiation is not the main reason that make air movement gain goes up and down.

TAS Building Optimize Simulation â&#x20AC;&#x201C; Lighting Dimming Profile Lighting Control Comparison 12000 10000 8000 6000 4000 2000

1, 1 16, 22 32, 19 48, 16 64, 13 80, 10 96, 7 112, 4 128, 1 143, 22 159, 19 175, 16 191, 13 207, 10 223, 7 239, 4 255, 1 270, 22 286, 19 302, 16 318, 13 334, 10 350, 7

Before Lighting Gain (W)

After Lighting Gain (W)

Lighting Control Load Comparison 10 9 8 7 6 5 4 3 2 1 0

Before Lighting Cooling Load

After Lighting Control Cooling Load

Result The other strategy for improving the performance is the lighting control. Based on the daylight simulation I did in the former report, I select August to be the legend to generate the daylight dimming profile for the building. The result do show a lot of improve on the lighting gain. Since the solar gain is the second large sensible load. It is good to use these disadvantages to improve the performance. The result shows that the dimming profile actually works better than the shading during the whole year.

TAS Building Optimize Simulation â&#x20AC;&#x201C; Lighting Dimming Profile Lighting Control AMG comparison 800 600 400 200

-200

-400 -600 -800 After lighting control Air Movement Gain (W)

Before lighitng control Air Movement Gain (W)

Indoor Zone Mean Radiant Temperature Comparison 35 30 25 20 15 10 5

After Lighting Control Mean R Temperature

Before lighting control Mean R Temperture

Result According to the result, it still have a slightly changed in air movement gain. The main reason for that is caused by the sensible load changed in the outcome. The gain change is original changed from the in door radiant temperature changed in each zone. After light dimming profile the load goes down. Then the indoor temperature have slightly goes down. The air movement gain also going down based on that. To this outcome it is clear to see that the temperature and sensible load all tided together. Each of them have some impact on each other.

TAS Building Optimize â&#x20AC;&#x201C; Mechanical Function Ventilation Ventilation Gain 4 3.5 3 2.5 2 1.5 1 0.5

1, 1 10, 4 19, 7 28, 10 37, 13 46, 16 55, 19 64, 22 74, 1 83, 4 92, 7 101, 10 110, 13 119, 16 128, 19 137, 22 147, 1 156, 4 165, 7 174, 10 183, 13 192, 16 201, 19 210, 22 220, 1 229, 4 238, 7 247, 10 256, 13 265, 16 274, 19 283, 22 293, 1 302, 4 311, 7 320, 10 329, 13 338, 16 347, 19 356, 22

Before ME Ventilation (kg/s)

After ME Ventilation (kg/s)

Ventilation Load Comparison 10 9 8 7 6 5 4 3 2 1 0

Before Ventilation Cooling Load

After Ventilation Cooling Load

Result The other strategy is the ME ventilation. The ventilation is triggered by dry bulb temperature. If indoor temperature is too high the ME ventilation will be triggered. However, the cooling load in June to July, the cooling load almost do not have any changes in these period. The main reason I assumed is that the indoor temperature in these period is high enough but the load for running the machine is going to change its form to the raise up the cooling load. The other reason is that the control function I set start at 0 degree c to 26.6 c the indoor temperature might goes out this period. The high temperature in summer do not be activated in my setting.

TAS Building Optimize â&#x20AC;&#x201C; Mechanical Function Ventilation

Air Movement Gain 800 600 400 200

-200

-400 -600 -800 Winout Any Ventilation Strategy Air Movement Gain (W) Function ME Ventilation Air Movement Gain (W)

Result As usual I will still test the air movement gain in this agenda. With ME ventilation help the air movement gain do have some changes. According to the result, the air movement gain is lower than the one without ME ventilation. This means that the some of the day time which I set the function the air movement become positive or even higher than before. This also came to the conclusion that the air movement gain is a constant gain in TAS. The positive mans the indoor air heat transfer the negative which means the number for infiltration the number from indoor to outdoor.

TAS Operable window study

Temperature Compare (1F) 40 35 30 25 20 15 10 5 -5 -10

-15 External Temperature (°C)

First Floor Open Office Dry Bulb (°C)

First Floor Closed Office Dry Bulb (°C)

Result This part I start another test with the operable window in TAS. TAS have the same strategy I used I energy plus. The main metrics for the operable window is based on indoor dry bulb temperature. The difference between it opening ration is its boundary condition. In energy plus its function in boundary condition is more complicated. Not only it control by the RH and temperature factor it also has Cp which means the efficiency to control window. In TAS the operable in control by the temperature period as an boundary condition when temperature reach the set point you set it start to open till the other set point it become totally open.

TAS Operable window study

Air Movement Gain 2000

-2000

-4000 -6000 -8000 -10000 -12000 Winout Any Ventilation Strategy Air Movement Gain (W)

Operable Window Air Movement Gain (W)

Result It is also good to test how air movement gain looks like in the operable window condition. The operable window means that the air go into the room. According to the outcome from the air movement gain, before the operable window the operable the air movement gain is driven by the indoor air movement in each room. On the other hand in operable window, the air movement gain is going to impacted by the out air. The graph shows that the negative air movement gain occupy the whole year which indirectly means that the window do open and control by temperature. It is also clear that the operable did not work Booleanly. It have 0-1 control parameter.

TAS Operable window study Operable Window Load Compare 10 9 8 7 6 5 4 3 2 1 0

Before Operable Window Cooling Load

After Operable Window Cooling Load

ME ventilation and Nature Ventilation Compare 12 11 10 9 8 7 6 5 4 3 2 1 0

After ME Ventilation Cooling Load

After Operable Window Cooling Load

Result Then come to the cooling load to test how it looks like after the window control in TAS. The former in ventilation shows that how it looks like in the cooling load. Seems the ventilation in June and July do not have good impact in this two month. On the other hand, which one might be the good way to solve the ventilation in my building ? I also did a compare between the function ME ventilation and operable window ventilation. The result shows that the ME ventilation did a nice job in my building. I assumed that main reason for that is because the ME ventilation will bring drastically ACH to the zone but in operable the ACH is not very constant as ME did.

TAS Operable window study: The ELA in TAS Operable Window Load Compare 10 9 8 7 6 5 4 3 2 1 0

Before Operable Window Cooling Load

After Operable Window Cooling Load

[J]

Operable window in Energy Plus 400000000 350000000 300000000 250000000 200000000 150000000 100000000 50000000 0

Lets compare the cooling load after the operable between E+ and the TAS. It is very clear that TAS result shows that the open window is not very effective strategy to be for lower the cooling load. To research this reason I look through the user manual of the breathing building in TAS. I founded that in TAS their have a place in operable window control can let you enter the ELA number in the control function. It also gave me the matric to count the ELA function and combine the window control panel. I assumed that these part can be the main reason that cause the window open different between the E+ and TAS. The ELA is mainly impact in infiltration but the open window is another kind of infiltration. This topic is great to talk about. Unfortunately, In this report I did not have time to go that far. I might leave it to the future.

TAS Operable window HVAC function control First Floor Surface ure Opening (0-1) 1.2 1 0.8 0.6 0.4 0.2

Result The other things I havenâ&#x20AC;&#x2122;t have chance to do is the HVAC control in system part. In TAS is very easy to achieve that. The main control I set is in plumbing fan to the zone and the cooling system in VAV. The boundary condition I set in the system is based on the operable window . When the window open ratio is bigger than 0.4 the cooling system and plumbing fan to the system will shut down. The flow rate will be completely be 0 in this function. The main reason I set 0.4 is that it is basically operable rate in the whole year. This number can be give me a more general look in changing system or shut down the HVAC system.

TAS Operable window HVAC function control

Result Based on the part camera in the plumbing and cooling system , it is very clear that the how flow goes down or completely stop in this period . It is also a feature in TAS to see how it looks like in the each plumb cooling coil or heating boiler. It gave user a quick look how may cause the system energy to goes up or which plumb runs incorrectly.

TAS Operable window HVAC function control Other Energy Consumption 16 14

kwH/m2

12 10 8 6 4 2 0

TAS OTHER ENERGY

EPC Hourly OTHER ENERGY

Energy Plus OTHER ENERGY

After Operable Window Control

HVAC Energy Consumption 40 35

kwH/m2

30 25 20 15 10 5 0

TAS HVAC ENERGY EPC Hourly HVAC ENERGY( After Calibration) Energy Plus HVAC ENERGY (after calibration) HVAC Energy DeliverEnergy after operable window control

Result TASâ&#x20AC;&#x2122;s deliver energy is separate from the load part. This make me good to compare the setting I set in the system. Based is philosophy, letâ&#x20AC;&#x2122;s take a look how it happened after the control function in the system. For me surprised that when the operable window and system work simultaneously it really help the building to low down the energy consumption. Then I tried to compare each parameter with E+ and others. It is clear that in other energy part because the plumbing and fan is under controlled by the function I set. For the HVAC part, I mainly control on the cooling part so the winter month do not much but it do have big change in summer month.

TAS OPT result compare (Cooling Load) Total OPT Cooling Load Compare 10 9 8 7 6 5 4 3 2 1 0

Origin Cooling

Op window Cooling

Lighting Control Cooling

add shading Cooling

Mechanical Cooling

Total Air Movement Gain Compare 20000 10000

-10000

-20000 -30000 -40000 Origin Air Movement Gain (W)

Add Shading Air Movement Gain (W)

Lighting Control Air Movement Gain (W)

ME ventilation Air Movement Gain (W)

OP Window Air Movement Gain (W)

Result Based on all outcome from the OPT simulation in TAS, the outcome shows that the one which is best for lower cooling load is ME ventilation and operable window. It seems very similar with the E+ or EOP optimization in the former report. Even though the ME ventilation and operable window do not perform that well when compare with E+, they still are very efficient way to solve the cooling load problem in the Atlanta hot humid climate. To do a double check to make sure the result, the air movement gain can clearly shows that. The original air movement gain from high to low. This shoe how each strategy impact each indoor areaâ&#x20AC;&#x2122;s energy flow. Strategy shows the less energy moving gain leads to low temperature difference.

TAS OPT result compare (Heating Load) Total OPT Heating Load Compare 14 12 10 8 6 4 2 0

Origin Heating

Op window Heating

Lighting Control Heating

add shading Heating

Mechanical Heating

Building Heat Transfer OPT Compare 60000 40000 20000

-20000

-40000 -60000 Original Building Heat Transfer (W)

Lighting Control Building Heat Transfer (W)

ME Ventilation Building Heat Transfer (W)

Operable Windwo Building Heat Transfer (W)

Adding Shading Building Heat Transfer (W)

Result On the other hand the heating load part, the best way for heating load is stay with the original one. The main reason is the trade off from the cooling load. The one got the best cooling load not always the one got enough heating in the same time but due to the weather in ATL the heating is not always a problem when comes to energy performance. The other things that this outcome can show is the parameter called Building Heat Transfer Gain in TAS. This is also like the AMG the one with high heat transfer gain got the best heating load. Main reason for is that the more heat transfer gain it got the less heating load it need .The heat will move through each zone and lower the heating load in the winter period.

TAS / EPC / Energy Plus / IES Geometry (E+):.

Geometry (IES):.

Geometry (TAS):.

Result To warp it up each software, I start in geometry part. In E+ the geometry is very easy to build up since it is based on sketch up plugin but it is also have a lot of bug when you using the software. It also will automatically define the internal wall and window for you but not give you a lot of space to modify the model. In IES and TAS is kind of like the same its model building is very not easy to use. However, in TAS the system is more stable and it also give you a lot of chance to modify the model. You can define the model construction component whatever you want. I founded that is very useful, since you cannot do that in IES or E+ .These changes do impact the final result.

TAS / EPC / Energy Plus / IES System (E+):.

System (IES):.

System (TAS):.

Result The final part is the system. In E+ system and energy deliver is combine together. The system will usually impact the energy demand. However, in TAS it usually separate with the system and load calculation. The main reason is that the way each software treat system. The E+ based on system in the energy load part. In TAS, the system usually set for solving load caused by the sensible load. The system is to solve the problem that load cased. The other things is that it is very easy to custom system in TAS. It can do it like grasshopper battery form. On the other hand in E+ and IES it does not five that capability to reconstruct your system.

Things I have learned in TAS and total wrap up Before changing internal holiday condition air movement gain in JUNE 01

After changing internal holiday condition air movement gain in JUNE 01

Result To warp it up the whole TAS study to one world, I would said MERGE. TAS system separate each simulatorâ&#x20AC;&#x2122;s function into different software. This made the system sustainable and comparable. Some simulation might need the dynamic result like in different material or different construction type. TAS can easily do that based on its softwareâ&#x20AC;&#x2122;s characteristic. The other things about TAS is it automation in simulation. These characteristic are very clear when it goes to the air movement gain or heat transfer gain. If user do not set up anything in the system, it will still count the default heat transfer phenomenon inside the building. However, these can usually cause another problems when the users did not give system clear condition in the simulator the outcome usually not going to be correct. These going to be different story when it comes to E+ or IES VE. In the end the things I learned from this case study is priceless. As simulation student these also taught me that always know which things you are simulate is very important !