Capstone Project - LEED Gold v4 optimization by wchang72

Capstone Project LEED Optimization With Smith Group Bristol 2 Vincent Chang

Table of content:

Start Up - Outline

Project Introduction

Simulation â&#x20AC;&#x201C;Proposed Model

Proposed Model Detail Simulation

Common Question Test and Solve

LEED Gold and Baseline Model

107

Energy Performance Optimization

115

LEED Gold Whole Section Optimization

145

LEED Optimizer and Final Result

154

Acronyms and Abbreviations ANSI American National Standards Institute ASHRAE American Society of Heating, Refrigerating and Air-Conditioning Engineers BECP Building Energy Codes Program Btu British thermal units Btu/h British thermal units per hour CAV constant air volume CBECS Commercial Buildings Energy Consumption Survey CFM cubic feet per minute CHW chilled water COP coefficient of HVAC in heating or cooling DDC direct digital control DOE U.S. Department of Energy DX direct expansion EER energy efficiency ratio EIA Energy Information Administration ERV energy recovery ventilator Et thermal efficiency EPC Energy Performance Calculator (Ga Tech HPB LAB PORPERTY) EPC TECH OPT Energy performance calculator technology optimization software FEMP Federal Energy Management Program ft feet or foot ft2 square feet or square foot gpm gallons per minute hp horsepower HVAC heating, ventilating, and air conditioning Honeybee Energy performance software plugin in grasshopper by MIT IECC International Energy Conservation Code IES Illuminating Engineering Society IESNA Illuminating Engineering Society of North America LBNL Lawrence Berkeley National Laboratory LCCA life-cycle cost analysis Lady bug Energy analysis software from MIT lm lumens PHP Philippines dollar prEN 15232 Energy performance of buildings â&#x20AC;&#x201D; Impact of Building Automation Control and Building Management mph miles per hour MSC Mechanical Subcommittee (SSPC 90.1) NFRC National Fenestration Rating Council NIST National Institute of Standards and Technology NREL National Renewable Energy Laboratory VAV variable air volume W watt WWR window-to-wall ratio TAS EDSL TAS simulation software USGBC U.S. Green Building Council VT visible transmittance

Prolog HPB: Being an architect in Building simulation work is not a very easy work but here I am. I always though each design should its own logic. The logic that can make sense. The logic that form the building. In academia we found lots of them. For here energy is the one I would like to discuss about. Being a designer is not only creating beautiful stuff but also helping the society to grow to lean. This time in energy strategies I could be proud each line and each step is not only a beautiful line works but also can make the building and High-Performance Building ! First, I would like to thank to Smith Group Bill and John give a lot of information to finished this cap stone Then I would like to thanks for all help from HPB Group fellows and professor. I learned a lot. I would like to thanks all my classmate that give me a lot of help. Finally I would like to thanks professor Augenbroe guiled me through all these difficult stuff I hope you have a happy journey after retirement.

Start Up - Outline Tis part is the part I start my project. The content include the research outline and its goal . It also include the expectation of the final result how I finished it and what kind of problem I will encounter.

Research Outline Research Motive and Goal Motive: During my internship in Smith Group, I encounter several projects I discovered that instead of caring the design in each project, most of them missing the part in energy consuming. I founded that I would be great if architect can start the design or even solve the energy consuming problem in design face the problem about energy and design problem can be solved in the same time. This time I will focus on project â&#x20AC;&#x153; Bristol 2â&#x20AC;?. The project is residential tower in Philopenas. The process is going to be design driven. Instead of using simulation to give the feedback to the building, the process is to give design option to the architects to let them chose each option that can match their design and match the energy performance target. Goal: 1. Simulate energy model with actual practice project 2. Solving complicated modeling in problem in complex design 3. Offer design strategies and simulation result for each strategies to solve energy problem in architecture face. 4. Generate trade off for the project and help client decide is the their goal is worth to chase

II. Main problems I will solve in this research 1. Simulate the project and make sure the project meet LEED GOLD certificate. 2. Testing some major or common design strategies for the project 3. Figure out the LEED point which cost relatively more for the whole project 4. To get GOLD project want to add LEED energy points up to the level where the additional energy point is more expensive than a point in other categories

Project Information

Location: Filinvest City, Alabang, Philippines Climate: Tropical, Winter warm, summer hot Building type: Residential, High rise Buildng1 42 floors Building 2 36 floors

Research framework

Basic Architecture Model

TAS Simulation Coordinate

TAS Ashrae 90.1 Rating for LEED

EPC Basic Simulation

Result Calibration with EPC and TAS

EPC Tech OPT Optimization

E+ Model Simulation For Client Need

RISK analysis &Uncertainty For Result

Conclude Final Decision Final Impact

LEED Optimization To talk about the LEED optimization framework the main process is based on EDSL TAS 90.1 wizard’s simulation. Then using EPC to do the calibration to make sure the TAS result is correct to use. The other reason for calibration is that next step’s optimization should use EPC Tech opt’s solver to figure out each improvement’s cost. Finally then using @Risk to do conclude the main impact of the model and conclude the final optimization score in my own LEED price tag optimizer. 1. Using EPC for general simulation look for the two options: • EPC give the project a general look for weather file or wind rose to give later process a hint how I can generate strategy for the project. • Optimization Solver in excel which can lower computation problem and let result comparable 2. Using TAS for simulation and its 90.1 wizard to fulfill LEED gold energy rating method: Mainly use TAS is because TAS is very good at complicated model simulation. The other is that the TAS include the 90.1 model simulation comparison. However, the model may encounter a lot of problem that is main reason I used EPC Tech OPT to finish optimization. 3. Partial simulation for client may need with energy plus Based the information I got from the project design team would like to see the natural ventilation is doable in the building or not these may need energy plus for detail simulation. The other is clear problem after the weather file result. These two are the main focus in the detail simulation. 4. Optimization in EPC Tech OPT and figure out the improvement percentage Tech OPT include different construction cost and labor cost which going to be needed in the LEED v4 Energy performance’s section. 5.Risk analysis, Tornado plot , Monte Carlo method: These three analysis are the method what I going to use to decide the LEED optimization. Since the result have a lot of uncertainty either in cost or point. These analysis is really helpful

Research expectation and problem, I will encounter Expectation: 1.How is the projectâ&#x20AC;&#x2122;s energy performance looks like ? 2.High rise buildingâ&#x20AC;&#x2122;s energy performance and the problem solving for the energy model 3.Ashrae 90.1 modeling bias and some of its trade off 4.Figure out wall and window humidity micro clime based 5.Realize the which causing the building energy condition 6.Optimize the building energy performance with ASHRAE 90.1 and LEED gold criteria 7.Creating LEED criteria sheet for comparison in the project or in the future project 8.Managing cost and labor for other section of LEED V4 9.Figure out the sweeten part for the project that is efficient for energy performance improve 10.Condut the result to the client whether they should spend their money in performance or not 11.Combine energy optimization and LEED Optimization Problem: 1.High rise building energy modeling 2.Proposed model lack of knowledge have to have lots of assumptions 3.Complicated diagram in geometry may not be easy to build up in simulation software 4.Residential zone schedule for each type of living space 5.90.1 regulation and energy code for the baseline model and proposed model 6.LEED regulation and ASHRAE 90.1. 7. Figure out the cost for energy optimization . 8. Figure out the cost for other section in LEED V4 .

Project Introduction The project introduction include project information and project site information. In first part I introduce projectâ&#x20AC;&#x2122;s condition and climate condition and how potential strategies I will be using in the future. Then goes to zone information which is the logic I model in energy simulation software. This section is like small warm up for the next sectionâ&#x20AC;&#x2122;s simulation.

Building Information

Location: Filinvest City, Alabang, Philippines Climate: Tropical, Winter warm, summer hot Building type: Residential, High rise Buildng1 42 floors Building 2 36 floors Total Units: 340 Floor Area: 34865 m2 Faรงade Area :149296.1143 m2

Building Use: 1B: North , East , West 2B: South 3B: South Penthouse: North East West East

Site Information 25F

17F

Site Condition: The site is in Philippines. The climate zone based on ASHRAE 90.1’s definition is 1A. The climate is going to be hot and humid. The simulation I am going to deal with is only tower 1 since tower 1 is higher than tower they all share the same massing and floor height the result can be referenced by tower 2. The surrounding building all are about 20 to 30 floor height (60m to 90m) and for South and East side is the main façade that the project is focusing on. The focusing façade is facing river and it do not covered by any nature or artificial obstacle

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)

Vertical Wind Roses

Wind Roses(Yearly)

Constant wind in South East : Based on the result of the weather, the constant wind is going to appear in East side. This may have point that the building during construction need to be careful about. The main thing is the Building air leakage. Since the South side has lots of window the Envelope of these area have very big chance to get air leakage problem during the careless construction process. The other things is the ventilation problem or window open in the East and South side of the envelope. According to the humid air, these side window open may cause constant humid air blow into the indoor area for the whole year.

Radiation analysis

High Solar Gain with Large Window Open ? Another thing I discover during the simulation, is the solar radiation. The solar radiation is very high in the Philippines clime zone. During the whole year, the South faรงade can even get 938 kwh/m2. This can almost run 5400 laptop for 6 hours at the same time. The other potential problem is that the Visible Transmittance is going to be very important during the simulation or in future design. Since the solar radiance maybe going to be the major problem that causing the high cooling load in the year.

Climate Data Radiation analysis

Comfort zone

Psychrometric Chart

Relative humidity chart

Direct Solar Radiation

17 Total Clime Chart (Yearly)

Site possible risk and general strategy Comfort hour

Comfort hour for Ventilation

Comfort hour for add shading

Comfort hour for dehumification

Quick and general strategies for the project: In order to investigate the project carefully, I plug the data into grasshopper to generate some general idea of how to improve the comfort hour. In the original one it is very clear that the comfort hour doesnâ&#x20AC;&#x2122;t even exist in the whole year. The main reason can be traced back in previous pages. The comfort hour have highly connection with temperature and humidity. According to the tropical climate this is one of the main issue that caused the problem. The other is that high solar radiation during the whole year. In average US city the solar peak hour is 4-5hour, however in Philippines the peak solar hour can gain to 7-9 hours. These high intense solar can make operative temperature higher than normal. Based on these conclusion, I plug in basic strategies. It is very clear that after adding more options about the dehumidification the comfort hour begin to raise up. These can also be followed up in the previous psychrometric chart. Design team can either solve the humidity problem or reduce the operative temperature to get to general comfort zone. The other interesting to see is the ventilation and solar gain. The result shows that the both ventilation and add solar shading can not improve the comfort hours. The main reason might be a little bit clear but how can we prove it ? For more detail I will simulate and discuss more in the later of page.

Building Innovation possible Result

Wave massing envelope: The main characteristic of the project is the wave massing in the South side of the building . According to previous solar simulation result, the solar radiation in South side also the biggest side of the building. These bring up another problem of this project. The window of the faรงade. The South facade is originally designed to give people who live in the unit enjoy river side view so most of the envelope will have lots of curtain wall. The wave massing also have some potential problem. In some cases some massing do not cover by any other massing is going to exposed in the high radiation condition during the whole year. Since the massing changing is 4 floor per times, some of the faรงade might not have chance to be fully covered by overhang massing or it will only be partial covered. On the other hand, the one covered by 4m cantilever might have chance to get enough sun light during the whole year. It is clear that window selection for each massing is going to be important simulation detail in the later ch

Simulation parameter Zone Space Name Gross Floor Area (m2) Occupancy (m2/person) Metabolic rate (W/person) Appliance (W/m2) Lighting (W/m2) Outdoor Air (liter/s/person) DHW (liter/m2/month)

Zone1 1B 10,857 12.50 70 7.72 11.84 7.80 3.33

Zone2 2B 4,002 9.40 70 7.17 11.84 7.80 3.97

Zone3 3B 3,090 7.06 70 7.17 11.84 7.80 3.97

0M CANTILIVER

2M CANTILIVER

4M CANTILIVER

PENTHOUSE

Zone4 Penthouse 976 8.72 70 7.17 11.84 7.80 3.97

Zone5 Corridor 18,940 101.00 180 2.16 5.20 7.80 0.10

Zone input: According to the plan from designer group, I can aggregate the plan into 4different massing floor. From 0m cantilever to 4m cantilever and a penthouse level. The way I separate the building zone is based on direction each units and different units in the floor plan. Since solar radiation is the dominate in the area, each units in different direction should calculate separately to make sure the solar radiation got calculated. For the zone input in Lighting and Appliance and any other stuff, I referenced the US DOE Building America House Simulation Protocols data. Outdoor air infiltration I referenced from ASHRAE Standard 62.1-2010 and DHW number from NEP Inputs. All data comes from different residential regulation. The main reason is that client do not have any preferred input for each. What I did is to chose a basic regulation number to make the whole simulation reasonable. In the future or optimization these number can be substitute in smaller number .

Simulation –Proposed Model This part is beginning the first step’s energy simulation. Chose zone and material make sure HVAC system. Conduct schedule during the whole year. Each part will have detail how I set up these parameter. The section also used as proposed model for LEED v4 ENERGY OPTIMIZE proposed model. Then in the end I set up simulation and adding some uncertainty analysis just to make sure my previous climate data do have impact on the outcome. In this stage is all proposed model which means will be applying to all TAS , EPC’s result in the next few simulations.

Zone Schedule: Zone for Housing

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

Zone for Corridor

Occ_WD 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 0.25 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ 0.25 0.75

Occ_WE App_WD App_WE Light_WD Light_WE 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 0.25 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ 0.25 0.75

0.07 0.07 0.07 0.07 0.07 0.07 0.07 0.54 1.00 0.54 0.07 0.07 0.07 0.07 0.07 0.07 0.07 0.30 0.54

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

Occ_WD ‐ ‐ ‐ ‐ 0.50 1.00 0.50 ‐ ‐ ‐ ‐ ‐ ‐ ‐ 0.25 0.50 0.75 1.00 1.00

Occ_WE ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

App_WD 0.05 0.05 0.05 0.05 0.05 0.05 0.05 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

App_WE Light_WD Light_WE 0.05 0.05 0.05 0.05 0.05 0.05 0.05 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

‐ ‐ ‐ ‐ ‐ ‐ ‐ 1.00 1.00 1.00 ‐ ‐ ‐ ‐ ‐ ‐ ‐ 1.00 1.00

‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

0.07 0.07 0.07 0.07 0.07 0.07 0.07 0.54 1.00 0.54 0.07 0.07 0.07 0.07 0.07 0.07 0.07 0.30 0.54

‐ ‐ ‐ ‐ ‐ ‐ ‐ 1.00 1.00 1.00 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐

0.77

0.20

19‐20

0.75

1.00

1.00 1.00 0.77 0.30

0.20 0.20 0.20 ‐

20‐21 21‐22 22‐23 23‐24

0.25 ‐ ‐ ‐

1.00 ‐ ‐ ‐

1.00 1.00 1.00 0.33

1.00 1.00 1.00 1.00

1.00 ‐ ‐ ‐

With and without cooling energy difference is not very oblivious in July (All distribution simulation period is only July) Schedule in Multi family apartment: For schedule in multi family housing, I used ASHRAE 90.1 and ISO 13790:2008(E) Annex G, Table G.12 and Building America House Simulation Protocols, 2010-B10 Benchmark schedule data as my referenced. The strategies for separate different schedule is using public and private in the whole building. The private area is each units I assume every units share the same schedule to make the simulation easier to launch. The public area is going to be the corridor in the building. This also include the elevator and any other public area. Here I also reference the little study I did during Georgia Tech to show that the uncertainty of the occupancy do not have a very big change on other result. However, in this stage it might need more detail simulation in the future to make sure the occupancy arrangement do not make huge difference in the result since the multi family building is usually very unpredictable. Each units might have different lifestyle and different activity level but in this project, I will not go too deep into that level.

Building system assumption HVAC System 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

35. Room units including single duct units 1. Mechanical system only; no provision for natural ventilation 75 0.00 No heat recovery No exhaust air recirculation 1.6 1.80 1.00

HVAC System assumption: Room units including single duct units (PTHP)

Packaged Terminal Heat Pumps (PTHP) : According to the design team and there drawing, they might propose the single separate units in each household. The main issue for that is the unclear for HVAC type. In this case I will assume basic room HVAC units during simulation . According to ASHRAE 90.1 2010 , The multi residential in climate 1A is using Packaged Terminal Heat Pumps (PTHP). I will start my proposed model from here using PTHP units to simulate. The difference is I will be changing different COP for cooling and heating just to separate the difference between ASHRAE baseline model, and the design team proposed model. The COP I will be using is based on local HVAC unit's website product detail. It is said that in difference climate area the COP of PTHP is going to customize for its own unique climate conditions. In here the usual COP number is 3.9 for cooling and 1.2 for heating. Here I also have suggestion for the design team. Since the building is high rise residential, in some cases it is no harm to us VAV system for each floor. This not only make the performance better but also clear up the balcony space for design purpose.. In this report I will not get into system too much but focus more on the architecture stage

Building shading condition assumption Envelope Oqaque1 Orientation

Area [m2]

Oqaque2 Area [m2]

Window 1 Window1 Window1 Window1 Horizon Overhang Angle Fin Angle Angle [degree] [degree] [degree] 2,705.0 ‐ ‐ ‐ ‐ 1,619.0 ‐ ‐ 1,996.0 ‐ ‐ 1,619.0 ‐ ‐ ‐ Area [m2]

SRF2

S 262.0 ‐ 0.93 SE ‐ ‐ 1 E 2,378.0 ‐ 0.94 NE ‐ ‐ 1 N 1,385.0 ‐ 0.62 NW ‐ ‐ 1 W 2,378.0 ‐ 0.72 SW ‐ ‐ 1 Roof(Hor) 1,018.0 ‐ 1 Below grade Refer to REFERENCE sheet for angle inputs for Overhang, Fin, and Horizon. None: 0. Refer to REFERENCE sheet for shading device Shading Reduction Factor (SRF) from Internal or External Shading Device (Blind or Curtain). No shading device: 1.

Shading or not ? SRF- It is defined as the fraction of incident solar radiation onto a window with shading to the same window without shading. Thus, a high reduction factor represents high solar gains while a low factor means a high influence from shading objects. The SRF in this project is relatively very important. Since the solar radiation is a big impact for the building based on previous result. The black color in the pic means fully shaded and vice and versa. The result shows that the EAST and SOUTH side SRF very closed to 1 which means not even shaded. This problem might show up in the final result which make the solar gain be the main issue to solve in the optimization. This also may lead to reduce window ratio in EAST and SOUTH side

Peak Solar Radiation Massing Study

Peak solar data from Lady bug (Grasshopper) What benefit for ? This result shows how to evaluate peak solar radiation hitting a building massing on the summer design day. The output allows one to estimate which of a set of massing might require a larger, more expensive HVAC system to produce. It also can be used to quantify the relative impact of shade on the size/cost of the HVAC system. Lastly, the reduction of peak solar (and corresponding cooling load) is often necessary to enable the use of certain lowenergy HVAC types, like radiant slabs and chilled beams. Based on the result the North Side in the cooling design day may need to use larger HVAC system for cooling. The main reason that cause difference with South is because the simulation time step is different the cooling deign day look for smaller period than the previous simulation. The other reason is that in Philippines the peak solar time is on May. During this time step the sun is going to be very close to the Tropic of Cancer nut the time is not the fully summer so the sun at that time will be more in the North Side.

Material parameter Material Uvalue [W/m2/K]

Type Roof1 Roof2 Opaque1 Opaque2 Window1 Window2

Absorption coefficient

Emissivity

0.23

0.70

0.90

0.60

0.70

0.90

3.38

0.84

Solar Transmittance

0.23

DOE climate zone chart

ASHRAE 90.1 2019 Appendix G Material assumption: According to the ASHRAE 90.1 appendix G standard, the climate 1A and 1B have their own regulation for envelope in U value for wall and roof. I will assume some parameters from the data based. In walls above grade, I chose steel framed as construction since steel framed is commonly used in Philippines high rise construction. However, the structure also include the mass so based on that the parameter I will be using is going to be about U-0.011 and the roof I chose is Metal Building since it is not common to have attic in the house units and the number is going to be U-0.041

Material number Material Uvalue [W/m2/K]

Type Roof1 Roof2 Opaque1 Opaque2 Window1 Window2

Absorption coefficient

Emissivity

0.23

0.70

0.90

0.60

0.70

0.90

3.38

0.84

Solar Transmittance

0.23

ASHRAE 90.1 2010 Appendix G

California Title 24 and IECC Code 2012-2018 Visible Transmittance: Visible transmittance is the amount of light in the visible portion of the spectrum that passes through a glazing material. A higher VT means there is more daylight in a space which, if designed properly, can offset electric lighting and its associated cooling loads. Since the project is in tropical hot and humid climate the VT is going to be very important during the simulations. The tricky things for the parameters is that the VT in ASHRAE 90.1 2019 have regulation for each climate zone but in LEED v4 coordinate ASHRAE 90.1 2010 there will not be any regulation for VT. According to that I will use the parameter from California Title 24 as my VT number and the rest of the number I will be using is based on ASHRAE 90.1 2010.

Energy consume and Cooling Load

Heating and Cooling Need 12.00 10.00 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 14.00 12.00 10.00 8.00 6.00

Hourly Method Energy Delivered [kWh/m2]

4.00 2.00 ‐ Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec First glance in result: Based on the previous result I assumed during the simulation, I get the result from EPC. The result shows that cooling load is going to based solar radiation since the peak solar month is the same time period in the result with high cooling load. This condition can also be proved in previous climate page which shows the cloud cover in March to May is the smallest during the whole year. The other reason that caused March to May high cooling load is the average wind speed. In previous page the climate data shows the average wind speed in March to May is also the highest in the whole year. Each units and zone there will be some infiltration in each zone and during the whole year building can easily get a lot of latent cooling load in a high wind speed and high humidity climate. For the deliver energy which LEED v4 care the most, it is very clear to see that the energy graph share the same trend as cooling load . These may come to conclusion that most of the deliver energy come from cooling load. Fortunately, this make the optimization easier to solve since project do not have to care about heating.

Causing Distribution analysis

Limited distribution in parameter: All result I assumed in previous page come to one uncertain, none of the number is confirm. These will always be the main issue caused the result doubtable. Based on these concern, it is worth to do an uncertainty analysis. For starting and uncertainty analysis I need to make some assumption before the simulation. The parameter I chose for distribution is the parameter that is hardly to change in the future design process. For example show as the chart above, I set the South window (and any other direction ) and the Units area as my uncertain distribution. The main reason is that these parameter can be hardly changed in the future. On the other hand the window or HVAC system these parameter can be changed easily but will not have big impact on design. The distribution I chose is normal distribution. The main reason for that is because the project right now is in schematic design process. Most of the form is almost confirm (these will be the mean in the distribution) and the normal distribution is going to be the suitable for high possibility in mean.

Main Causing Analysis

Tornado Plot: After counting the distribution in the previous section, I initiate an uncertainty analysis. The main reason for the uncertainty analysis in this stage is to generate a tornado plot and realize the parameter is going to be the most impact for the result. According to the result above it is very clear that the South side curtain wall window is going to be the biggest impact on the both cooling load and deliver energy. These result seems reasonable since previous section shows that the south side east side got most the direct sun radiation in the whole year and the direct sun radiation is the main reason that caused the cooling load. The other reason that make the result reasonable is the cooling load and deliver share the same form in the result. In both cooling load and deliver energy are affected by South side window area and East side window area. This also make sense since the project and climate is going to be cooling dominated and cooling goanna be the main impact on deliver energy. These two reasons that make the tornado plot reasonable .

Proposed Model Detail Simulation This part is detail simulation for the model. The previous section I look at the general model simulation result but how it perform signally in each units? And how caused the general final result in previous section? All these question could be answer in this section. This section also include each typologyâ&#x20AC;&#x2122;s daylight simulation result. In case the design team need this additional result. All the result will be list in this section.

Detail Analysis Per Units (1B WEST) Delivered Energy

Heating and Cooling Need 16.00

9.00 8.00

14.00

7.00

12.00

6.00

10.00

5.00

8.00

4.00 6.00 3.00 Monthly Method Energy Delivered [kWh/m2]

2.00 1.00 ‐ Jan Mar May Jul Sep Nov

4.00 2.00

Heating Need [kWh/m2]

‐ Jan Mar May Jul Sep Nov

1B WEST UNITS: In this stage in order to look into more detail what happened for each units I will start with the 1-bedroom west side units. Most 1-bedroom units only have one opening in their facing side. The glazing not only very small but also facing into one side but most of all the wall is going to be the most envelope in the simulation . According to the result, the opaque is going to be causing the units to have high cooling load during the large direct solar month . The second will be the solar transmittance for the window. These two conclude the main reason that causing the high cooling need in peak solar month. Foe looking into the deliver energy the cooling COP is going to be the biggest impact. The main reason is that the cooling energy load is going to be the dominate reason for the whole year. This also correspondence the previous result for deliver energy.

Detail Analysis Per Units (1B EAST) Delivered Energy

Heating and Cooling Need 12.00

9.00 8.00

10.00

7.00 8.00

6.00 5.00

6.00

4.00 3.00

Monthly Method Energy Delivered [kWh/m2]

2.00 1.00

4.00

2.00

‐

‐ Jan Mar May Jul Sep Nov

Jan Mar May Jul Sep Nov

Heating Need [kWh/m2]

Direct solar: The difference between the East units and West units is the direct solar. For the East side based on the previous result the solar in East side larger than the West side and it also have less shading cover. These two reasons causing the difference with West side result. The result of the tornado plot show the same thing too. Based on tornado plot’s result, the solar transmittance is going to be the main impact. The main reason that make the difference between West 1B and East 1B is the big direct sunlight in the East side. These make the transmittance rank going to be higher than opaque even though its window area is as small as the West side. The plot show as above is obvious to show these phenomenon.

Detail Analysis Per Units (2B West) Heating and Cooling Need

Delivered Energy 18.00

12.00

16.00 10.00

14.00 12.00

8.00

10.00 6.00

8.00 6.00

4.00 Monthly Method Energy Delivered [kWh/m2]

2.00 ‐ Jan Mar May Jul Sep Nov

4.00 2.00 ‐ Jan Mar May Jul Sep Nov

Heating Need [kWh/m2]

More Window from the South: In previous simulation for the 1 bedroom in West side and East side the West side cooling load is affected by opaque’s U value is based on the low solar radiation in West side. In this part for 2 bedroom in West side the result is difference. The result shows the South side window area and window transmittance is going to be the big impact for the result. This is because the South side which get a lot of direct sunlight have more opening than 1 bedroom (1bedroom have no South side opens). For the deliver the cooling still going to be the main reason.

Detail Analysis Per Units (2B East) Delivered Energy

Heating and Cooling Need 18.00

12.00

16.00 10.00

14.00 12.00

8.00

10.00 6.00

8.00 6.00

4.00 Monthly Method Energy Delivered [kWh/m2]

2.00 ‐ Jan Mar May Jul Sep Nov

4.00 Heating Need [kWh/m2]

2.00 ‐ Jan Mar May Jul Sep Nov

Same thing: The result for the East side 2 bedroom is not very surprising. The first rank window is even more away from the baseline. This is also because the direct solar and South side opening these two main reason that make the window lead the simulation result for causing high cooling load from March to May. It also very interesting that the West side and East side difference is very little on deliver energy but have a very clear difference in cooling load. The main reason is that even though the main impact on deliver energy is cooling but deliver energy cooling is based on HVAC. The system COP is going to lower it and not make as dramatic as cooling load did in the result.

Detail Analysis Per Units (3B West) Heating and Cooling Need

Delivered Energy 16.00

9.00 8.00

14.00

7.00

12.00

6.00

10.00

5.00

8.00

4.00 6.00 3.00 4.00 2.00

Monthly Method Energy Delivered [kWh/m2]

1.00 ‐ Jan Mar May Jul Sep Nov

2.00 ‐ Jan Mar May Jul Sep Nov

Heating Need [kWh/m2]

More wall no difference: Go through the final type units. The three-bedroom units is the smallest amount of the total units. The specialist of these units is there big partial of wall area and big partial of window area. I would say the result shows the same things like I showed in previous pages. The West don’t have high direct sunlight number, so the opaque impact is going to be main second impact. The window is still the dominate reason for the uncertainty analysis.

Detail Analysis Per Units (3B East) Delivered Energy

Heating and Cooling Need 16.00

9.00 8.00

14.00

7.00

12.00

6.00

10.00

5.00

8.00

4.00 6.00 3.00 Monthly Method Energy Delivered [kWh/m2]

2.00 1.00 ‐

4.00 Heating Need [kWh/m2]

2.00

Jan Mar May Jul Sep Nov

‐ Jan Mar May Jul Sep Nov

Same story: The main reason is like the previous result this is very clear.

Result calibration

Calibration In the final stage of the detail unit's simulation. I would like to make a calibration of the previous result. As most of the result the May is going to be highest cooling load in the whole year. To make sure the previous simulation for uncertainty and its tornado plot is correct I compare the May result with the final total result. The result shows that the final result of the total cooling load in the building is affected by South side window open area. The result of Mayâ&#x20AC;&#x2122;s tornado plot shows the same thing. These can prove that the opening of the window in South side causing the high cooling load and the design team need to reconsider the open ratio is going to be that high or not?

Solar ,Daylighting analysis â&#x20AC;&#x201C;ďź&#x201D;F

Solar radiation detail analysis for 5f: In this section I will start to do the detail solar analysis for each typology floor. The first typology is the first floor to five floor. The main reason I chose the fifth floor is that the fifth floor is covered by the floor above. It would be good to start with the floor has some trade off in solar radiation. Based on the result, it is oblivious that the South side units have very serious glare problem. The normal light level in residential housing is usually up to 500 LUX but the South side of the building get 3000 LUX. The East side just like previous result said the lighting level also reach 2500 LUX. The main reason is that the fifth floor typology do not have enough shading for normal living units. These two faces can not only conclude the previous cooling load result but also give design team a basic view of glare problem in particular floor.

Solar ,Daylighting analysis-8F

For the next typology. The 2 meter cantilever â&#x20AC;&#x2DC;s radiation number has dramatic change than the fifth floor. As the result above most of the unitâ&#x20AC;&#x2122;s living and sleeping units got almost 2000 LUX for the whole year. These result is not a good choice for people who stay in the house during the day in the morning or afternoon. The sleeping area also is not comfortable for very serious glare problem The main reason that caused this phenomenon is because first the South side do not have any cover and second the floor is way from the ground floor. The floor will not have any other tree cover or other building shading . In this cases the floor should have make their typologies visible transmittance to be smaller in order to control the glare in the building units.

Solar ,Daylighting analysis-14F

Constant and Long Shading Above: The result for 14 floor is the floor which in some cases it did not get enough daylighting but normally it still comfortable for living. The main reason that causing the difference between the 14 floor and the 8 floor is the massing shadingâ&#x20AC;&#x2122;s difference. For 14 floor even though the shading above it is 2-meter cantilever but the next typologies also helping them gain a lot of improvement on shading. Another issue to talk about is the room arrangement problem. According to the plan view, the balcony do help the indoor units to lower the glare problem, but it also make the main view area which there will not be any living units do not get enough daylighting. To solve these problem I would suggest the public spacesâ&#x20AC;&#x2122; balcony rearrange to private spaces. It can not only fix the glare problem in living units but also help the living room have more sunlight during people occupant day

Solar ,Daylighting analysis-18F

2m Massing Shading: Even though the typology of 18 floor is 2 meter cantilever, the shading is still going to be 2 meter. Since the total floor massing did not get enough cover as 15 floor does. The front of the South side of the units based on the much higher part of the building and the less shading the daylighting performance is not in a very good condition. The good things is that the South West unit's bedroom arranged in a very good position. It does not get glare problem from like some previous typologies. The other things to talk about is the West side 1 bedroom units. Since the surrounding buildings are not as tall as the projectâ&#x20AC;&#x2122;s building. The West side can easily get a lot of daylighting. In previous result the West side daylighting performance do not have glare problem it usually get about 750LUX to 500LUX these parameter is acceptable but in this typologies the bedroom units in West get over 2500LUX which will cause glare problem.

Solar ,Daylighting analysis-22F

Protruding the most: Based on the graph above, it is very clear that as the floor height get higher the glare problem start to get more serious. The bedroom units in South side got 70% of its area are over 3000 LUX during the whole year. The West side units get 10% higher of their area reach to 2500 LUX . The trade off is the South Units living room. Since the balcony make the indoor area have less chance to have nice daylighting during the whole year. It is also said that the higher of the floor the higher efficiency of the shading will get.

Solar ,Daylighting analysis-26F

26F: Then goes to 26 floor, in this floor all the result remains the same but the South face become drastically higher than the other previous South face. In this time the North West faceâ&#x20AC;&#x2122;s units get lot more glare problem than the previous ones. The main reason for that is the North West face in 26 floor height do not have any environment shading. This happened to the North East faceâ&#x20AC;&#x2122;s units. Last but not least the East units in previous load analysis the face is going to be the worst just like South. However, the East this time is covered by Tower2 this make units do not have glare problem but probably have lighting problem since it does not have enough day lighting.

Solar ,Daylighting analysis-30F

Cover gets better: For 30F the one covered by the penthouse, the daylight perform is really good. Even though it is located in a very top floor, it covered by penthouse and this condition make it have small solar gain and less glare problem than normal top floor.

Solar ,Daylighting analysis-32F

High price high glare: I would say based o the result I got above, the performance of the daylighting on 32 floor looks terrible. Each units got almost 70% of chance to over glare and got 3000LUX . The over glare phenomenon make these high-rise units have very serious problem on cooling load and most of the activity in the South side of the buildings is not acceptable since most of their time have glare problem. On North and East side the performance is not very good too. The East side does not get enough shading since surrounding buildings is shorter than the tower. The other things that make the high price floor even worst. The floor plan arrangement is making the bedroom units get a lots of glare since it start to mange more dense units (3 bedroom). These make each room dimension become shallow and the total floor area get glare problem.

Solar ,Daylighting analysis - PENTHOUSE

Penthouse still worth it: Finally the penthouse. I would say the penthouse looks great. Even though most of its room got 2500 LUX for the whole year, its plan still arrange pretty good . The main reason is that the penthouse units have very average floor area. Four units share the whole floor. These make each units got deep and wide floor plan area. In other words these give design team can do some trick on arranging the suggestion furniture in each units. For example, some place do not have glare problem it can be set a bed or even a sofa to avoid the glare problem. On the other hand, the glare area can be arranging some working area or just leave it as an open space. Based on the all result for these section, I would suggest the floor above 26 floor should gain more big room units or just make the 3 bedroom to a 2 bedroom units to make living units livable and reduce glare impact but do not change drastically on the design at the same time.

Common Question Test and Solve This part is general question for the model. In previous simulation the design team might have some general solution for there design. For example is the project suitable for ventilation ? Or how is the daylight simulation condition for each floor ? Based on my design background, I come up with some question that designer always want to know, or I should say that general design like to draw their pretty line work. This section will simulate all of them and come up with pacific solution for the whole building and it is worth to do it or not. If designer really want to do , how can they prevent the problem that caused by their decision.

TAS Simulation Result TAS Monthly Building Load Break Down 16.00 14.00 12.00 10.00 8.00 6.00 4.00 2.00 0.00 1

Heating

Cooling

Humidify

Dehumidify

Lighting

Occupancy

Equipment

Internal (L,O,E)

Solar

Annual Load Break Down 1400.00 1200.00 1000.00 800.00 600.00 400.00 200.00 1F 1B E1 1FBAL 2F CORRIDOR 3F 2B S3 4F 2B S2 5F 3B S1 6F 3B S1 7F 3B S1 8F 3B S1 9F 2B S1 10F 2B S1 11F 2B S1 12F 2B S2 13F 3B S1 14F 3B S1 15F 3B S1 16F 3B S1 17F 2B S1 18F 1B W2 19F 1B W1 20F 1B N3 21F 1B N2 22F 1B N2 23F 1B N2 24F 1B N2 25F 1B N2 26F 1B N2 27F 1B N2 28F 1B N2 29F 1B N2 30F 1B N2 31F 1B N2 32F 1B N2 33F 1B N1 34F CORRIDOR

0.00

Heating

Cooling

Humidify

Dehumidify

Solar

Lighting

Occupancy

Equipment

Internal (L,O,E)

Simulation from EDSL TAS: After the detail simulation from EPC and detail solar simulation for daylighting, I start to use EDSL TAS for detail simulation for the whole building. Based on the result from TAS the cooling load still going to be the main sources for deliver energy. Another things which must be break down into detail is the cooling load. Is it the same as previous assumption? I would say the answer is positive. The result above shows that the whenever the cooling load increase the solar gain also increase. The solar gain’s yearly load distribution’s graph is almost the same as the cooling load graph. Another things to double check is the zone load break down chart. Based on the result the zone break down chart above, the results shows the up and down. Load number which respond the different typologies in the solar detail analysis in the previous section. The main reason that caused the up and down load is the massing shading which means the 0m cantilever to 4m cantilever.

TAS simulation load result and EPC simulation load result (with HVAC) TAS load simulation result

Comparison result 12.00 Cooling Need [kWh/m2]

10.00 8.00 6.00 4.00

TAS Cooling Need [kWh/m2] (Proposed)

2.00 ‐ Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Proposed design data calibration with EPC: According to the previous result, the result seems very persuasive. However, I am not very sure how the data is trustable enough. That’s the reason why I tried to list out EPC’s result and compare with TAS’s result. The result shows that EPC ‘s result is very close to the TAS result. This make the TAS result thrustable in this case. Based on the trustable result, I can start to break down the TAS load above. As the above graph shows ,the LATENT COOLING is bigger than usual month. This can respond the previous result (The climate data section). The high deliver energy during March to June is not only caused by solar gain but also caused by humidity. The high humidity during March to June make HVAC system in the building need more energy to remove the indoor humidity. This also make the latent cooling during March to June bigger than other month.

High solar gain Strategy (Current Condition)

0M U-value: 3.23 SHGC: 0.45 TR: 0.55

2M U-value: 3.23 SHGC: 0.45 TR: 0.55

Ashare 90.1 standard 2016

14.00 12.00

KWH/M2

10.00 8.00 6.00

Total cooling load 2m

4.00 2.00 0.00

Total uncover cooling load before mod

Same glazing condition in Typologies connection floor: According to pervious high solar gain condition, I must produce some result to solve the problems. However, before going to optimization part , it is also a good idea to just investigate only the place where the two typologies connect. The main reason for investigating partially is because the place where connecting happened encounter High solar gain ( 4m cantilever with 2m or 4m to 0m) and High shading area (0m to 4m or 2m to 4m) at the same time. This is part where I going to used E+ to simulate. I build up the model in E+ and set the ceiling and floor going to be adiabatic. This make the massing is in the total building condition do not get any impact from others. The result shows the massing which cover by 2m massing shading get less cooling load than the one without shading . These result also support the previous section’s result.

High solar gain Strategy(High Performance W, Uvalue and SHGC)

0M(MOD) U-value: 1.13 SHGC: 0.25 TR: 0.45

2M U-value: 3.23 SHGC: 0.45 TR: 0.55

Ashare 90.1 standard 2016

12.00 10.00

KWH/M2

8.00 6.00 4.00

Total cooling load 2m

2.00 0.00

Total uncover cooling load after mod

First step (changing U value): The first step for changing window I fist start with changing window’s U value. The strategies I used is to use very low U value window. I chose my product based on National Fenestration Rating Council . Even though the rating are all from U.S, I think the parameter is still trustable enough. The result shows that after lowing the U value the load do go down, but the range is still not big enough to be even lower than the cover one. According to the result in previous section, the main reason that causing the high cooling load is the solar that go into the building and to solve these main issue will not only rely on changing U value but also managing the light go through building’s window. For that the best way to accomplish the goal might be using low visible transmittance and adding shading.

High solar gain Strategy(Add Shading)

0M(Add Shading) U-value: 3.23 SHGC: 0.45 TR: 0.55

2M U-value: 3.23 SHGC: 0.45 TR: 0.55

Ashare 90.1 standard 2016

12.00 10.00

KWH/M2

8.00 6.00

Total cooling load 2m

4.00 2.00 0.00

Total uncover cooling load add shading

Adding shading: The other strategies I will try is adding shading for the South side of the building. As the previous page I mentioned, the best way to lower the load on typologies without massing shading cover is to make the sun light transmit less than the original one. Here I start to try add Fin angle shading next to the window. The shading include the vertical shading which can help building block the East side sun light and the horizontal shading which can block the South side of the sunlight. All shading dimension is 15 cm to 30 cm. This number comes from Philippines government sustainable page. The range goes smallest 15cm to biggest 30cm. The result shows the shading do make some difference, but it is still not enough to make the uncover building load close to cover building or even smaller. Based on that I will try changing Solar Transmittance to see if it will work out.

High solar gain Strategy(W, focus on Visible Transmittance)

0M(MOD) U-value: 1.13 SHGC: 0.25 TR: 0.13

2M U-value: 3.23 SHGC: 0.45 TR: 0.55

Ashare 90.1 standard 2016

12.00 10.00

KWH/M2

8.00 6.00 4.00

TotalÂ coolingÂ load 2m

2.00 0.00

ChangingÂ Visisble Transmittance

Solar Transmittance: The last strategies is changing solar transmittance. This means most of the glazing parameter stays the same but only changing its visible transmittance. The original visible transmittance is 0.55 the number is also from National Fenestration Rating Council . Normal window in US climate zone usually goes to 0.5 to 0.7 but in cooling dominating area usually will let the number goes down to 0.12 or even 0.07 to make sure the cooling load do not get affected by solar gain. Based on this I used the number from ASHRAE Fundamentals (SI) 2009 F15 Table 4: U-Factor and Table 10: Solar Energy Transmittance. The number for single glazing constructions. After changing the Visible Transmittance the cooling load not surprisingly goes down almost 20% and the strategy do work out in the end.

Total Strategy Iteration and Trade off 14.00 Total cooling load 2m

12.00

KWH/M2

10.00

Total uncover cooling load before mod

8.00 6.00

Total uncover cooling load after mod

4.00

Changing Visisble Transmittance

2.00

4m cover total cooling load

0.00 Adding Shading

VT meter step VT: 0.7

VT: 0.32

VT: 0.55

VT: 0.13

Sometimes light is not enough: According to the previous result for the final strategies, changing solar transmittance number might be the best solution for solving the solar gain big impact on building. The graph above also shows the same things. I combine all other parameter in the same graph, it also shows changing visible transmittance is more efficient in during the whole year. The other things might be the trade off for changing windows visible transmittance is the daylighting performance. Changing windows visible transmittance will make the units get lower daylighting. According to the graph above the changing high visible transmittance do improve the glare problem but in VT 0.13 graph it also make units have less daylight. However, I think this might not be a very big problem. Since the low daylighting performance area is only partial of the room not all over the units. Design can use these information to rearrange their interior design to design which place is good for reading and which place is good for sleeping.

Ventilation ? In previous result I talked about Ventilation in this project is not a very good choice since the high humidity in projectâ&#x20AC;&#x2122;s climate zone. Based on the assumption, I would like to do some simulation to make sure my previous assume is correct. Ventilation have lots off different way to reach the final goal. In designer part there are nature ventilation by opening window or even more complex ventilation well, etc. However, in simulation point of view , these different strategies donâ&#x20AC;&#x2122;t have any difference. The main reason is that these strategies all use nature ventilation basedâ&#x20AC;&#x2122; s nature source. In the condition without HVAC turned on and other artificial ventilation, every cooling load in the zone will be fulfilled by the outside temperature and nature source. This assumptions make the simulation doable and easier. Below is the way I set for nature ventilationâ&#x20AC;&#x2122;s logic. The whole process is going to be cross ventilation and the logic is control by indoor temperature and indoor humidity.

Window open ratio control DetermineÂ NVÂ windowÂ openingÂ ratio:Â đ?&#x2018;&#x2030;đ?&#x2018;&#x;đ?&#x2018;&#x17D;đ?&#x2018;Ąđ?&#x2018;&#x2013;đ?&#x2018;&#x153; Â (betweenÂ 0Â andÂ 1)Â asÂ followsÂ IFÂ RHambientÂ <Â RHthresholdÂ AND đ?&#x2018;&#x2021;đ?&#x2018;&#x2013;đ?&#x2018;&#x203A;đ?&#x2018;Ąđ?&#x2018;&#x2019;đ?&#x2018;&#x;đ?&#x2018;&#x2013;đ?&#x2018;&#x153;đ?&#x2018;&#x; AND đ?&#x2018;&#x2021;đ?&#x2018;&#x2013;đ?&#x2018;&#x203A;đ?&#x2018;Ąđ?&#x2018;&#x2019;đ?&#x2018;&#x;đ?&#x2018;&#x2013;đ?&#x2018;&#x153;đ?&#x2018;&#x;

đ?&#x2018;&#x2021;đ?&#x2018;&#x17D;đ?&#x2018;&#x161;đ?&#x2018;?đ?&#x2018;&#x2013;đ?&#x2018;&#x2019;đ?&#x2018;&#x203A;đ?&#x2018;Ą Â đ?&#x2018;&#x2021;đ?&#x2018; đ?&#x2018;&#x2019;đ?&#x2018;Ąđ?&#x2018;&#x161;đ?&#x2018;&#x2013;đ?&#x2018;&#x203A; Â

THENÂ đ?&#x2018;&#x2030;đ?&#x2018;&#x;đ?&#x2018;&#x17D;đ?&#x2018;Ąđ?&#x2018;&#x2013;đ?&#x2018;&#x153;

đ??śâ&#x2C6;&#x2014;

đ?&#x2018;&#x2021;đ?&#x2018;&#x2013;đ?&#x2018;&#x203A;đ?&#x2018;Ąđ?&#x2018;&#x2019;đ?&#x2018;&#x;đ?&#x2018;&#x2013;đ?&#x2018;&#x153;đ?&#x2018;&#x; đ?&#x2018;&#x2021;đ?&#x2018;&#x2013;đ?&#x2018;&#x203A;đ?&#x2018;Ąđ?&#x2018;&#x2019;đ?&#x2018;&#x;đ?&#x2018;&#x2013;đ?&#x2018;&#x153;đ?&#x2018;&#x;

đ?&#x2018;&#x2021;đ?&#x2018; đ?&#x2018;&#x2019;đ?&#x2018;Ąđ?&#x2018;&#x161;đ?&#x2018;&#x2013;đ?&#x2018;&#x203A; Â đ?&#x2018;&#x2021;đ?&#x2018;&#x17D;đ?&#x2018;&#x161;đ?&#x2018;?đ?&#x2018;&#x2013;đ?&#x2018;&#x2019;đ?&#x2018;&#x203A;đ?&#x2018;Ą

ELSEÂ đ?&#x2018;&#x2030;đ?&#x2018;&#x;đ?&#x2018;&#x17D;đ?&#x2018;Ąđ?&#x2018;&#x2013;đ?&#x2018;&#x153;

0Â

ApplyÂ limitÂ onÂ openingÂ ratio:Â Â đ??źđ??š đ?&#x2018;&#x2030;đ?&#x2018;&#x;đ?&#x2018;&#x17D;đ?&#x2018;Ąđ?&#x2018;&#x2013;đ?&#x2018;&#x153;

1 đ?&#x2018;&#x2021;đ??ťđ??¸đ?&#x2018; đ?&#x2018;&#x2030;đ?&#x2018;&#x;đ?&#x2018;&#x17D;đ?&#x2018;Ąđ?&#x2018;&#x2013;đ?&#x2018;&#x153;

1Â

Explanation:Â â&#x20AC;?

â&#x20AC;? â&#x20AC;?

CÂ isÂ aÂ factorÂ thatÂ determinesÂ theÂ speedÂ withÂ whichÂ theÂ openingÂ respondsÂ toÂ changes.Â StartÂ withÂ assumingÂ CÂ =Â 2;Â youÂ shouldÂ experimentÂ withÂ thisÂ number.Â CÂ isÂ obviouslyÂ directlyÂ associatedÂ withÂ theÂ sizeÂ ofÂ theÂ windowÂ opening.Â SmallÂ windowsÂ mayÂ needÂ aÂ largerÂ CÂ toÂ modulateÂ theÂ ventilationÂ flowÂ appropriately.Â CÂ couldÂ alsoÂ beÂ madeÂ aÂ functionÂ ofÂ V windÂ toÂ makeÂ theÂ windowÂ openingÂ inverseÂ proportionalÂ toÂ theÂ windÂ speed;Â tryÂ toÂ seeÂ ifÂ thisÂ givesÂ aÂ stableÂ controlÂ sequenceÂ byÂ plottingÂ V ratioÂ (t)Â TheÂ logicÂ determinesÂ thatÂ (a)Â asÂ weÂ getÂ closerÂ toÂ Tsetmin,Â weÂ startÂ closingÂ theÂ windowÂ more,Â andÂ (b)Â asÂ theÂ differenceÂ betweenÂ insideÂ andÂ outsideÂ temperatureÂ isÂ smaller,Â weÂ startÂ openingÂ theÂ windowÂ moreÂ

đ?&#x2018;&#x2021;đ?&#x2018;&#x2013;đ?&#x2018;&#x203A;đ?&#x2018;Ąđ?&#x2018;&#x2019;đ?&#x2018;&#x;đ?&#x2018;&#x2013;đ?&#x2018;&#x153;đ?&#x2018;&#x; Â Â â&#x20AC;?Â InteriorÂ temperatureÂ (t),Â asÂ computedÂ inÂ theÂ simulationÂ toolÂ đ?&#x2018;&#x2021;đ?&#x2018; đ?&#x2018;&#x2019;đ?&#x2018;Ąđ?&#x2018;&#x161;đ?&#x2018;&#x2013;đ?&#x2018;&#x203A; Â â&#x20AC;&#x201C;Â minimumÂ allowedÂ temperatureÂ insideÂ Â (toÂ avoidÂ overcooling),Â typicallyÂ constant,Â e.g.Â 20Â CÂ RHambientÂ =Â outsideÂ RHÂ RHthresholdÂ limitÂ onÂ outsideÂ RHÂ Â NoteÂ thatÂ đ?&#x2018;&#x2021;đ?&#x2018; đ?&#x2018;&#x2019;đ?&#x2018;Ąđ?&#x2018;? Â Â =Â SetpointÂ temperatureÂ forÂ coolingÂ (variesÂ withÂ timeÂ ofÂ daysÂ andÂ week/weekendÂ day)Â isÂ notÂ usedÂ inÂ theÂ controlÂ logic.Â IndeedÂ theÂ coolingÂ controlÂ isÂ handledÂ byÂ EnergyPlusÂ inÂ theÂ normalÂ way,Â andÂ hasÂ noÂ relationshipÂ withÂ theÂ windowÂ openingÂ logic.Â Â ItÂ meansÂ thatÂ theÂ windowÂ canÂ beÂ openedÂ whenÂ theÂ coolingÂ isÂ on.Â ThisÂ willÂ thenÂ diminishÂ theÂ coolingÂ loadÂ andÂ inÂ someÂ casesÂ driveÂ theÂ temperatureÂ belowÂ the coolingÂ setpointÂ soÂ thatÂ coolingÂ isÂ turnedÂ off.Â NoteÂ alsoÂ thatÂ thisÂ logicÂ assumesÂ thatÂ theÂ windowÂ controlÂ isÂ actuatedÂ inÂ anÂ automatedÂ wayÂ andÂ thereÂ isÂ noÂ limitationÂ onÂ whenÂ thisÂ controlÂ isÂ activeÂ (i.e.Â 7*24Â active).Â IfÂ weÂ wouldÂ assumeÂ occupantÂ activatedÂ windowÂ openingÂ weÂ wouldÂ haveÂ toÂ addÂ timeÂ constraintsÂ onÂ theÂ logic.Â

Open Ratio in ATL To test the open ratio result in Philippines, first I have to make sure how it work in US and test the Open logic is going to effect the window. The condition I assume here is a very simple single stack open assumption. The place I chose is in Atlanta Midtown which is climate zone 3A the climate include heating need and cooling need. Main reason I chose Atlanta is that the Dry Bulb temperature is floating more drastic than the climate zone in 1A. The less drastic dry bulb climate zone is easier to see the difference and its ratio also clearer than the constant temperature one.

WINDOW VENTILATIONSCH: Schedule Value [Ratio](Hourly) 1.2 1

Ratio

0.8 0.6 0.4 0.2

07/21 01:00:00 01/04 17:00:00 01/15 09:00:00 01/26 01:00:00 02/05 17:00:00 02/16 09:00:00 02/27 01:00:00 03/09 17:00:00 03/20 09:00:00 03/31 01:00:00 04/10 17:00:00 04/21 09:00:00 05/02 01:00:00 05/12 17:00:00 05/23 09:00:00 06/03 01:00:00 06/13 17:00:00 06/24 09:00:00 07/05 01:00:00 07/15 17:00:00 07/26 09:00:00 08/06 01:00:00 08/16 17:00:00 08/27 09:00:00 09/07 01:00:00 09/17 17:00:00 09/28 09:00:00 10/09 01:00:00 10/19 17:00:00 10/30 09:00:00 11/10 01:00:00 11/20 17:00:00 12/01 09:00:00 12/12 01:00:00 12/22 17:00:00

Zone Cooling load difference(ATL) 4.00E+08 3.50E+08 3.00E+08 2.50E+08

[J]

2.00E+08 1.50E+08 1.00E+08 5.00E+07 December

November

October

September

July

August

May

June

April

March

February

0.00E+00 January

40 35 30 25 20 15 10 5 0 ‐5 ‐10 ‐15

01/01 01:00:00 01/23 21:00:00 02/15 17:00:00 03/10 13:00:00 04/02 09:00:00 04/25 05:00:00 05/18 01:00:00 06/09 21:00:00 07/02 17:00:00 07/25 13:00:00 08/17 09:00:00 09/09 05:00:00 10/02 01:00:00 10/24 21:00:00 11/16 17:00:00 12/09 13:00:00

Temperature [c]

Environment: Site Outdoor Air Dry bulb 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 suggesting that most of the time should open the window. The opening ratio is also making sense since the outdoor dry bulb temperature in most of the time is very high than normal city. It can also show that the open ratio’s form is approximate the dry bulb 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 nighttime 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 Ratio(Load Comparison in PHP) 32F Thermal Load Comparison 3.00E+09 2.50E+09

[J]

2.00E+09 1.50E+09 1.00E+09 5.00E+08 1 252 503 754 1005 1256 1507 1758 2009 2260 2511 2762 3013 3264 3515 3766 4017 4268 4519 4770 5021 5272 5523 5774 6025 6276 6527 6778 7029 7280 7531 7782 8033 8284 8535

0.00E+00

Hours THERMAL ZONE 14 IDEAL LOADS AIR SYSTEM:Zone Ideal Loads Zone Total Cooling Energy [J](After Open Logic) THERMAL ZONE 14 IDEAL LOADS AIR SYSTEM:Zone Ideal Loads Zone Total Cooling Energy [J](Before Open Logic)

3F Thermal Load Comparison 3.00E+09 2.50E+09

[J]

0.00E+00

Hours THERMAL ZONE 5 IDEAL LOADS AIR SYSTEM:Zone Ideal Loads Zone Total Cooling Energy [J](After Open Logic) THERMAL ZONE 5 IDEAL LOADS AIR SYSTEM:Zone Ideal Loads Zone Total Cooling Energy [J](Before Open Logic)

Load break down After the window opened, I start to output the load comparison to make sure how the load difference effect the model. Since the dry bulb temperature difference always appear in the logic. Every time system knows that the outside temperature is bigger than indoor temperature it will close the window. According to Zeroth law of thermodynamics the load have the highly connection with the temperature. The temperature always have difference between indoor and outdoor. This make the load difference have a very big difference even in hot and humid climate like Philippines. According to the graph above, both zone in high floor and in low floor have load decrease during the whole year. The result shows that the result during March to May have clearly decrease. Since during these time period the solar gain is the worst in the whole year. Indoor temperature is always larger than outdoor temperature and during this time open window is efficient for decrease the cooling load. However ,the graph above is sensible load and according to the psychrometric chart the humidity will cause high latent cooling load. I will talk more detail in next page with humidity comparison.

100

Open Ratio(Latent Load Comparison in PHP) Latent cooling load after window open

Latent cooling load before window open

Latent Load Latent cooling load is a measure of the amount of energy that is necessary to dehumidify the air in a building, for example, regardless of the outdoor humidity. Cooling load needs to be considered when a cooling system is being dimensioned. Latent cooling load refers to the wet bulb temperature. It specifies the cooling capacity a cooling system needs to be able to dehumidify a building to a desired humidity, even when external factors that create humidity are calculated in. Factors that influence humidity include: People, Different forms for equipment, Outside air entering through doors, windows, etc. Based on the result I got from the graph above, latent load before window open ventilation maximum goes to 11kw/m2. However, after making ventilation window operate the latent load up to 13kw/m2. The latent load comes from relative humidity from outside to inside. The result I showed above is Latent remove load which means the possibility buildingâ&#x20AC;&#x2122;s latent load building have to remove. Before open window the latent load comes from windowâ&#x20AC;&#x2122;s infiltration and air leakage gap between opaque and window. The one after open is based on outside humidity.

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Nature Ventilation trade off for humidity Average RH [%] Before Ventilation 90 80 70 60

50 40 30 20 10 1 245 489 733 977 1221 1465 1709 1953 2197 2441 2685 2929 3173 3417 3661 3905 4149 4393 4637 4881 5125 5369 5613 5857 6101 6345 6589 6833 7077 7321 7565 7809 8053 8297 8541

Hour

After Ventilation Humidity [%] 120 100

80 60 40 20

1 252 503 754 1005 1256 1507 1758 2009 2260 2511 2762 3013 3264 3515 3766 4017 4268 4519 4770 5021 5272 5523 5774 6025 6276 6527 6778 7029 7280 7531 7782 8033 8284 8535

Hour 1F 1B N1 Relative Humidity (%)

35F NP1 Relative Humidity (%)

Humidity According to previous pages result from latent cooling load, I do notice that the main reason that caused the latent cooling load raise up is humidity. Since the window open do not make any people’s occupancy change or diffuser change . I know the humidity is going to change but how big is the humidity goanna be during window opened? Here is the result. The graph above shows the humidity’s difference after the window is open as an open logic nature ventilation strategies. The top graph shows the average RH change during the whole year after window opened. The graph below top graph is the comparison between 1f with 35f during the whole year. In the second graph it is said that the 35f’s humidity is lower than 1f that is because the temperature for 35f is lower than 1f. This can reference from previous Psychrometric Chart. Although both floor RH are very high, I would suggest the top floor is the better place to start ventilation if architects really want to do that.

102

Risk for opening windows and ventilation strategy After Ventilation Humidity [%] 120 100

80 60 40 20

1 252 503 754 1005 1256 1507 1758 2009 2260 2511 2762 3013 3264 3515 3766 4017 4268 4519 4770 5021 5272 5523 5774 6025 6276 6527 6778 7029 7280 7531 7782 8033 8284 8535

Hour 1F 1B N1 Relative Humidity (%)

35F NP1 Relative Humidity (%)

Harmful in different aspect: In the previous page I noticed that the indoor RH is very high during the whole year but how will it happen when the team insist to ventilation during the whole year ? The graph above top one shows the total RH when open the window. The minimum for 1F RH is 65% maximum of RH is 100% and for 35F minimum is 55% maximum is 100%. It is said that even in the tall floor the RH is still from 65% to 100% and the chance is high during the whole year. Here is the question how will happen when we open the window for nature ventilation? Based on Indirect health effects of relative humidity in indoor environments by A V Arundel, E M Sterling, J H Biggin, and T D Sterling paper, the graph shows the best range for RH is 40% -60%. When over that range the RH will cause not only people’s health problem and construction mold problem. In here, I would suggest just stay away from ventilation in the project. The not project not only need stay away from Ventilation but also need to have some strategies against RH in construction. The next page I will talk more about that.

103

Wall humidity strategy suggestion

Vapor barrier inside insulation layer limits condensation on the interior side, and the frame wall cavity is not insulated, providing a high drying potential inwards.

Summary: 1. The material near interior is very important for costing mold problem. Some wall maybe efficient near exterior surface but the interior part may cause a lot of problem. 2.Some material insulation may not be well built. This will make the cavity outside have water go into the insulation and cause condensation or mold problem. 3. Gypsum board and polystyrene and coating is good at preventing humidity. The polystyrene is not sensitive to humidity and the gypsum board coating can absorb water and make sure the interior can use AC to get rid of humidity. 4. Before concrete cavity had been simulate the polystyrene prevent the interior material metal or OSB etc. from humidity. After adding another air layer with water and heat source the wall is still success in each climate area which means the polystyrene insulation plays an important role in the wall. 5. I changing the near interior material into wood material. It is not a surprised that the wall does not success in humid area. It is saying that the wall is not a very simple construction all materials have to concern carefully. Humidity sensitive must combine with insulation to make sure interior do not get any humidity problem.

104

Wall WUFI mold test

105

Window thermal testing and suggestion

Insulated Insulated window glazing refers to windows with two or more panes of glass. To insulate the window, the glass panes are spaced apart and hermetically sealed, leaving an insulating air space. Insulated window glazing primarily lowers the U-factor, but it also lowers the SHGC. Low-Emissivity Coatings Low-emissivity (low-e) coatings on glazing or glass control heat transfer through windows with insulated glazing. Windows manufactured with low-e coatings typically cost about 10% to 15% more than regular windows, but they reduce energy loss by as much as 30% to 50%.A low-e coating is a microscopically thin, virtually invisible, metal or metallic oxide layer deposited directly on the surface of one or more of the panes of glass. The low-e coating lowers the U-factor of the window, and different types of low-e coatings have been designed to allow for high solar gain, moderate solar gain, or low solar gain. A low-e coating can also reduce a window's VT unless you use one that's spectrally selective. Although low-e coatings are usually applied during manufacturing, some are available for do-ityourselfers. These films are inexpensive compared to total window replacements, last 10 to 15 years without peeling, save energy, reduce fabric fading, and increase comfort. Spectrally Selective Coatings A special type of low-e coating is spectrally selective, filtering out 40% to 70% of the heat normally transmitted through insulated window glass or glazing while allowing the full amount of light transmission. Spectrally selective coatings are optically designed to reflect particular wavelengths but remain transparent to others. Such coatings are commonly used to reflect the infrared (heat) portion of the solar spectrum while admitting more visible light. They help create a window with a low U-factor and SHGC but a high VT. Computer simulations have shown that advanced window glazing with spectrally selective coatings can reduce the electric space cooling requirements of new homes in hot climates by more than 40%.

106

LEED Gold and Baseline Model This part is about the LEED Gold criteria and the baseline model which based on Ashrae 90.1 2010 appendix g model regulation. These model is going to prepare to compare with proposed model based on LEED v4 regulation. The result came across from EPC to TAS so the section also include the calibration for the model from TAS to EPC. So the result can be used in next sectionâ&#x20AC;&#x2122;s optimization in EPC TECH OPT.

107

LEED GOLD criteria and energy improvement points (V4)

Energy improvement ? After knowing the detail simulation problems and figure out how to solve these problems. It is time to back on track to the main objective. The LEED Gold for the project. The criteria I used here is LEED Gold V4 since the project is going to be build in 2020. V4 is the better version to apply. For the LEED Gold the regulation will be 60 -79 points (Aggregate ). In this part I will mainly focusing on Energy performance and Renewal energy percentage since these two section in ENERGY AND ATMOSPHERE is easier to quantify and it can also correspond the previous result and strategies. Based on LEED V4 the prerequisite in energy performance rating method regulation, the criteria I am going to use is going to be Ashrae 90.1 2010 Appendix G which I have to create a baseline model and compare it with my proposed model. For the next part I will talk about the projectâ&#x20AC;&#x2122;s baseline model.

108

Baseline Model from ASHRAE 90.1 2010 Heating and Cooling Plants Heating System Coefficient of Performance (COP) [KW/KW] Cooling System Full Load COP [KW/KW] Relative COP100: for Relative Load 100% Partial Load COP75 Relative Load 75% Partial Load COP50 Relative Load 50% Partial Load COP25 Relative Load 25% Weighting of 100% Load Weighting of 75% Load Weighting of 50% Load Weighting of 25% Load HVAC System 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

0.91 3.60 1.00 0.90 0.82 0.50 0.01 0.42 0.45 0.12

IPLV: 0.82, Seasonal COP: 2.94 Refer to REF sheet Refer to REF sheet Refer to REF sheet Refer to REF sheet From ARI 550/590 Standard From ARI 550/590 Standard From ARI 550/590 Standard From ARI 550/590 Standard

35. Room units including single duct units 1. Mechanical system only; no provision for natural ventilation 75 0.00

(Only used for extra fan energy consumption)

No heat recovery No exhaust air recirculation

Building air leakage level (Air flow m3/h per floor area at Q4Pa)

1.1

Specific fan power [W/(l/s)]

1.80

Fan flow control factor

1.00

Pump control for cooling

No pump for cooling

Pump control for heating

No pump for heating

Refer to REF sheet (Infiltration ACH: 0.22) Average electromotor efficiency: Refer to REF sheet Average control reduction factor: Refer to REF sheet

PTHP in Baseline: The previous section I set PTHP as mine proposed model HVAC. Here in baseline I would still prefer using the same system since the design team are in schematic design step. Another reason for choosing the same system in baseline model and proposed model is to make the software compare possible. The next step I would going to use TECH OPT to do the optimization choosing the same system can make the result in TAS and EPC comparable For COP in here is the only things that is different from proposed model in HVAC section. The number I used in HVAC PTHP COP is based on ASHRAE 90.1 2010 appendix G. The number is going to be 3.6 for cooling and 0.91 for heating.

109

Ashrae 90.1 Baseline model – Zone Input Zone Space Name Gross Floor Area (m2) Occupancy (m2/person) Metabolic rate (W/person) Appliance (W/m2) Lighting (W/m2) Outdoor Air (liter/s/person) DHW (liter/m2/month)

Zone1

Zone2

1B 10,857 12.50 70 7.17 11.84 7.80 3.33

2B 4,002 9.40 70 7.17 11.84 7.80 3.97

Zone3

Zone4

3B 3,090 7.06 70 8.10 11.84 7.80 3.97

Penthouse 976 8.72 70 8.10 11.84 7.80 3.97

Zone5 Corridor 18,940 101.00 180 2.16 5.20 7.80 0.10

<Source: ISO 13790:2008(E) Annex G, Table G.12, NEP Input data, and Building America House Simulation Protocols, 2010‐Occupant Schedule> Single‐family houses Apartment blocks Domitory Retail Office Occupancy (m2/person) 60 40 10 50 14.29 Metabolic rate (W/person) 70 70 100 250 120 Appliance (W/m2) 13.11 12.87 5 50 10 <Source: ASHRAE Standard 90.1‐2007, Table 9.5.1 LPD using the Building Area Method and NEP Input> Multi‐family 4 stories or more Domitory Retail Office Lighting (W/m2) 11.84 8 50 10.76 <Source: ISO 13790:2008(E) Annex G, Table G.12, and NEP Inputs> * Example of conventional input data related to occupancy Single‐family houses Apartment blocks Domitory Outdoor Air (liter/s/person) 11.7 7.8

Retail 10

<Source: ASHRAE Standard 62.1‐2010> * Minimum requirements Residential Dwelling unit Common corridors Retail Outdoor Air (liter/s/person) 2.5‐ Outdoor Air (liter/s/m2) 0.3 0.3

Office 3.8 2.5 0.6 0.3

Office 10

<Source: NEP Inputs> Domitory DHW (liter/m2/month)

Office 6.55

0.1

Zone input schedule <Source: E+ default data set> Multi family BedRoom Multi family OtherRoom Hour Occ‐WD Occ‐WE App‐WD App‐WE Light‐WD Light‐WE Hour Occ‐WD Occ‐WE App‐WD App‐WE Light‐WD Light‐WE 0‐1 0.67 0.67 0.03 0.03 0.00 0.00 0‐1 0.00 0.00 0.19 0.19 0.00 0.00 1‐2 0.67 0.67 0.03 0.03 0.00 0.00 1‐2 0.00 0.00 0.19 0.19 0.00 0.00 2‐3 0.67 0.67 0.03 0.03 0.00 0.00 2‐3 0.00 0.00 0.19 0.19 0.00 0.00 3‐4 0.67 0.67 0.03 0.03 0.00 0.00 3‐4 0.00 0.00 0.19 0.19 0.00 0.00 4‐5 0.67 0.67 0.03 0.03 0.00 0.00 4‐5 0.00 0.00 0.19 0.19 0.00 0.00 5‐6 0.67 0.67 0.03 0.03 0.00 0.00 5‐6 0.00 0.00 0.19 0.19 0.00 0.00 6‐7 0.45 0.45 0.06 0.06 0.66 0.66 6‐7 0.21 0.21 0.30 0.30 0.29 0.29 7‐8 0.27 0.27 0.06 0.06 0.23 0.23 7‐8 0.21 0.21 0.70 0.70 0.59 0.59 8‐9 0.00 0.00 0.03 0.03 0.00 0.00 8‐9 0.21 0.21 0.34 0.34 0.00 0.00 9‐10 0.00 0.00 0.03 0.03 0.00 0.00 9‐10 0.21 0.21 0.34 0.34 0.00 0.00 10‐11 0.00 0.00 0.03 0.03 0.00 0.00 10‐11 0.21 0.21 0.34 0.34 0.00 0.00 0.21 0.21 0.61 0.61 0.00 0.00 11‐12 0.00 0.00 0.03 0.03 0.00 0.00 11‐12 12‐13 0.00 0.00 0.03 0.03 0.00 0.00 12‐13 0.21 0.21 0.61 0.61 0.00 0.00 13‐14 0.00 0.00 0.03 0.03 0.00 0.00 13‐14 0.21 0.21 0.34 0.34 0.00 0.00 14‐15 0.00 0.00 0.03 0.03 0.00 0.00 14‐15 0.21 0.21 0.34 0.34 0.00 0.00 15‐16 0.00 0.00 0.03 0.03 0.00 0.00 15‐16 0.21 0.21 0.34 0.34 0.00 0.00 16‐17 0.00 0.00 0.03 0.03 0.00 0.00 16‐17 0.21 0.21 0.34 0.34 0.00 0.00 17‐18 0.00 0.00 0.03 0.03 0.00 0.00 17‐18 0.67 0.67 0.84 0.84 0.00 0.00 18‐19 0.00 0.00 0.03 0.03 0.00 0.00 18‐19 0.67 0.67 0.94 0.94 0.00 0.00 19‐20 0.21 0.21 0.09 0.09 0.31 0.31 19‐20 0.45 0.45 0.34 0.34 0.63 0.63 20‐21 0.21 0.21 0.09 0.09 0.31 0.31 20‐21 0.45 0.45 0.34 0.34 0.63 0.63 21‐22 0.33 0.33 0.20 0.20 0.47 0.47 21‐22 0.33 0.33 0.23 0.23 0.47 0.47 22‐23 0.67 0.67 0.12 0.12 0.63 0.63 22‐23 0.00 0.00 0.19 0.19 0.31 0.31 23‐24 0.67 0.67 0.12 0.12 0.63 0.63 23‐24 0.00 0.00 0.19 0.19 0.31 0.31

Zone input: The input I set is little different from proposed model. Most of the proposed model’s parameter is based on ISO 13790 and the baseline model is based on ASHRAE 90.1 2010 and ASHRAE 90.1 2007. For the schedule, in order to make the model most closed to the proposed and also based on the Appendix G’s regulation I set the same schedule as the proposed model does.

110

Ashrae 90.1 Baseline model – Envelope Material Uvalue [W/m2/K]

Type

Roof1 Roof2 Opaque1 Opaque2 Window1 Window2

Absorption coefficient

Emissivity

0.11

0.70

0.90

0.21

0.70

0.90

2.11

0.84

Solar Transmittance

0.28

Envelope for baseline model: The final part in baseline model is the envelope. The envelope is pretty closed to the proposed model but in here the only difference I made is setting the difference Visible Transmittance. Based on the Ashrae 90.1 2010 there is no regulation on the glazing’s visible transmittance but the Ashrae 90.1 2019 have regulation on VT. I set the visible transmittance for baseline is based on Ashrae 90.1 2019’s visible transmittance. The number is 0.28 for normal glazing. The main reason I used 2019 regulation is to make sure the building is goanna stay more resilience in the future. The previous detail simulation shows that the VT is very important during simulation. I would like to be stricter on this section just to make sure the optimization can change this section that can really help the building to improve its performance.

111

Ashrae 90.1 Baseline model – Result Heating and Cooling Need 9.00 8.00 7.00 6.00 Heating Need [kWh/m2]

5.00

Cooling Need [kWh/m2]

4.00 3.00 2.00 1.00 ‐ Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

TAS Baseline Cooling Need and EPC Cooling Need Comparison 9 8 7 6

TAS Baseline Cooling Need [kWh/m2]

Cooling Need [kWh/m2]

4 3 2 1 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

EPC result and TAS result : After got the result from EPC baseline model for the project. I would like to compare with TAS’s result. For TAS’s result it also used the same parameter from EPC. The only difference is that the TAS result is ready for Ashrae 90.1 2010 simulation. Based on Ashrae 90.1 2010 regulation requirement, the model has to simulate in different direction : 90, 180 , 270, 0. The TAS result I showed above is the average result from the four direction . The previous detail simulation the solar gain is the huge impact on the building so the different direction for baseline building’s result goanna be little bigger than only one direction model. The EPC model here is only one direction so in high solar gain month the cooling load is going to be bigger than the EPC result. For the other result, it is only 10% difference between EPC and TAS. This make the EPC result trustable and ready to be used for TECH OPT optimization model in the later section

112

Cooling load calibration (TAS & EPC)

EPC

From Hourly Calculation

Baseline

Difference(%)

TAS

From Hourly Calculation

Baseline

Difference(%)

Edesign,del [kWh/m2/yr]

‐24.16%

Edesign,del [kWh/m2/yr]

99.8

75.57

‐24.43%

Baseline

Proposed

Calibrate cooling load: The next step for the result is to do the calibration. The mina reason is that I need to make EPC result ready to do the optimization in the excel. So first is the cooling load. According to the result show above, the difference between EPC’s baseline model and proposed model is (-24.16%) and the difference between TAS’s proposed model and baseline model is -24.43%. The main different is very clear to see is in the HVAC system. The main idea for the HVAC system is too solve the main cooling load that caused from the solar gain this make the proposed model HVAC energy bigger than the baseline model. The other is the cooling load of the building which stand for Solar and Humidity. According to the chart cooling load in May which the highest month in the whole year.

113

ASRAE 90.1 rating system

PI Edesign,del [kWh/m2/yr]

From Hourly Baseline Calculation 126

Difference(%) ‐26.78%

Main Category for LEED : The energy performance optimization in the section is goanna used the price to do the comparison. Based on the Ashrae 90.1 2010 appendix g, the rating system include the energy and it electricity price to count the percentage between proposed model and baseline model. Thanks to TAS help the result already calculated the price in the 90.1 wizard. However for the comparison, I still need to compare with EPC’s result. The method I used is to reference the formula from Ashrae and count the difference percentages. Instead of using average direction's difference percentages. I only used one direction in EPC. The result in TAS is about -29.19% and the result I got from EPC is -26.78%. The main reason that EPC’s number is smaller is that the HVAC calculation is difference than TAS but the range is still acceptable enough. Based on these result, I would say that the project still had a long way to go . The LEED qualification need 5% percent improvement. Right now project still need to improve 34% from baseline. To improve that much is the cost doable ? Or I would say where is place to stop the optimization ? For these trade off question I will answer in the next section about the optimization. .

114

Energy Performance Optimization This section is an introduce to my optimization system with EPC TECH OPT. The most important for the section is I introduce the cost of each optimization options and how I improve the model from general requirement to credit points in LEED v4 (From baseline 5% improvement to 50% improvement which going to be the maximum percentage in LEED energy optimize point in the criteria). The process from 5% to 50% I will not include in this section for more detail of the process please contact me personally. Last the chapter also include the next step optimization and the most effective options during the optimizations.

115

LEED GOLD Optimization and option scaling factors After knowing the situation the project, how can I notice the actual point that design team should peruse during the optimization process? Is it possible that the optimization all fall into energy improvement ?Is it efficient ? To answer these question I got the idea from the paper Article Credit Optimization Algorithm for Calculating LEED Costs If a client can easily employ a program by utilizing only the limited information available during initial construction planning, accessibility can also be improved for users aiming to achieve LEED certification. Therefore, the paper presents an estimation program based on the target certification level and basic building specifications. The overall algorithm is divided into primary and secondary calculation processes. In the primary calculation, basic building information is used to calculate relevant credits and scores. In the secondary calculation, if the scores calculated in the primary calculation do not satisfy the desired credit level, priority credits that can compensate for deficiencies are recommended. The information required for calculation concerns the architectural scheme, including gross area, building area, roof area, mandatory energy reduction rate, and the number of floors. Equal scale ratio from US to PHP

50% to below 50%

Scaling the cost for the construction: After knowing the target, I need to figure out how to scale the construction cost from US domain to Philippines domain. The main reason to do that is to make sure the cost information I got from US can be scale to Philippines and can also used to other site. The other main reason is I need the scaling factor to generate the LEED optimization curve. I start with looking into salary reference between Philippines architecture salary and construction salary and compare the rank position with US. The result surprisingly close. These means the construction cost and other optimization cost can be scale down from US to Philippines

116

Optimization option Labor cost Philippines Top End Construction Worker Earnings($/day) $38.93

Philippines Architect Fees (per project)

Philippines Experienced Construction Worker Earnings($/day)

Philippines HVAC worker Earnings($/day)

$34.30 Philippines Starting Construction Worker Earnings($/day) $24.59

Philippines PV worker Earnings($/day)

$9,587.52 $18.55 $16.79

Labor cost: According to the information I found on Glassdoor, I used the US average number in 2018. The normal workers working is 8 hours per day. I multiply the hour and the average money workers earn in PHP. Each construction will cost 1 or half day. I assumed that 1 day’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 material’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 must 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.

117

Optimization parameter: Optimization 1: Lighting daylighting factor Technology levels

Index

Starting Construction Worker

Cost $

Par.1

Total Cost(Without worker fee)

C22

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 produced 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 its 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 smaller 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 C23

B 1 ‐ Baseline (NULL)

0.00

B 2 ‐ Partial sensor (25%)

0.00

0.9

B 3 ‐ Partial sensor (50%)

0.00

0.6

B 4 ‐ Partial sensor (75%)

0.00

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 number will affect each other.

118

Optimization 2: Heating and Cooling Plants efficiencies (COPs) Technology levels Index 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 $ 0.00 1974500.0 0 2530740.0 0 3173680.0 0

2530740.0 0

Par.1 C28 0.91

Par.2 C29 3.6

Par.3

Min‐index 1

2.28

3.7

HVAC Reinstallation Fee(Total)

4.28

4.75

$2,500.00

6.28

5.8

4.28

4.75

Max‐index 4

Variable 3

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 project HVAC I assumed does not have any floor unit's central system 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

Total Cost(Without worker fee)

C43

No heat recovery

0.00

Heat exchange plates or pipes (0.65)

6250.00

No heat recovery Heat exchange plates or pipes (0.65)

Two‐elements‐system (0.6)

5800.00

Two‐elements‐system (0.6)

Loading cold with air‐ conditioning (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. Finally, the cost also must include the workers’ construction fee, since it was a big construction on the site.

119

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, HR‐ 3 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 Home depot to check each different type the DHW system. The DHW in residential is very important and might be a big part in during the simulation . It has a big connection between this one and solar hot water system. The things I did was connect them together. When TECH OPT chose normal system the solar hot water system’s cost will be eliminated.

120

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 software’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 Minimum # PV modules Maximum # PV modules

Value

Cost $

Par.1 C58

Par.2

Par.3

Min‐value 0

Max‐value 865.19

Variable 0

0 865.19 PV module area: PV module cost:

0.00

2.6 388.11

0.00

PV system: I used the module that Sol offer on his PV design excel file. The one I chose is the one based on NREL’s SAM 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.

121

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

Index

Cost $ Total Cost(Without worker fee)

Par.1 G13

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

14 5.10 2.21 2.07 2.27 2.67 14

Cost $ Total Cost(Without worker fee)

Par.1 G14

0.00

LED and CFL combo

3780.00

LED

4200.00

Fluorescent lamp t5

3480.00

Fluorescent lamp t8

3600.00

Fluorescent lamp t12

3840.00

100% CFL

0.00

12 2.05 2.10 1.97 2.16 2.54 12

Lighting for Zone1 and 2 : This section I go through Amazon, Home depot, 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 affect the use if the lighting.

122

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 (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

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.

123

Optimization 10: Window1 Technology levels

Index

Window Baseline 1

3.39

0.84

358500

2.11

0.84

0.25

165

442500

3.28

0.078

0.31

205

474000

2.678

0.137

0.22

220

495000

1.77

0.313

0.17

230

705000

1.046

0.417

0.15

330

852000

0.68

0.418

0.12

400

358500.00

2.11

0.84

0.25

Ashrae Baseline model Double glazing (SCO) 10‐16‐6 uncoated, air‐filled 4‐12‐4 low‐e, air filled 4‐12‐4‐12‐4 triple glazing, low‐e 4‐12‐4‐12‐4 triple glazing, argon‐filled, low‐e Ashrae Baseline model South window ratio Technology levels Starting Construction Worker Minimize Maximum Ratio

Index

Cost $

Par.1 G68

Cost $ Total Cost(Without worker fee)

Par.2 I68

Par.1

Par.2

Par.3 J68

Min‐index 1 WINDOW BUYING 0.36 COST(PER WINDOW)

Par.3

Max‐index 7

Variable 2

Min‐index

Max‐index

Variable

0.6

0.8

S50

0.6 0.9

Average Window Tare down window Area NUMBER(per window)

Total Glazing Area

0 1.29 Average Window Average Window Area Area install cost Put up window install cost (Tare or (Tare PLUS intall) NUMBER(per window) intall) PER WINDOW PER WINDOW $120.00 $195.00 0 Type Window Window Use Type($) Cost(Total) 0 0

2,704.80

0.00 West window ratio Technology levels

Index

Starting Construction Worker Minimize Maximum Ratio

Cost $ Total Cost(Without worker fee)

0.8

Par.1

Par.2

S56

Par.3

Min‐index

Max‐index

Variable

0.2

0.8

0.4

0.2 0.8

Tare down window Average Window Area NUMBER(per window)

Total Glazing Area

1,602.40 0.76 Average Window Area install Average Window Area Put up window NUMBER(per cost (Tare or intall) PER install cost (Tare PLUS window) WINDOW intall) PER WINDOW $120.00 Window Use Type($) 0.00

0.4

$195.00 Type Window Cost(Total) 0

Building Window Optimization: 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. Here is the graph shows how to overlay shading masks representing different shading strategies for the 4 cardinal directions onto a stereographic sun path that has suns colored according to the outdoor temperature. The result shows the portion of the sky dome that is masked by context geometry around a given point.

124

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

0.00 6600.00 7600.00 8120.00

0 30 45 60

0.00

Cost $ Total Cost(Without worker fee)

Par.1 Fin Angle

1 2 3 4

0.00 13200.00 15200.00 16240.00

0 30 45 60

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

0 10 20 30 40 50 60 70 80 0

Shading Change: Based on previous result for detail simulation, the solar gain is the main reason that caused the high cooling load. The other result also shows adding shading can help the whole building lower the cooling load. However, I don’t have any clue for how deep is the shading going to add and which direction is better to add shading. These difference make the shading for each side is very important. According to the reason , I separate each face’s shading condition. The main reason is to let tech opt to help me chose the best shading angle for each side. Finally the different shading can build simultaneously this also make the assumption reasonable.

125

Optimization 13: Appliance for smallUnits (W/m2) Technology levels 100%normal appliance 75%normal appliance 50%normal appliance 25%normal appliance 10%normal appliance 0%normal appliance 100%normal appliance Appliance for big Units (W/m2) Technology levels 100%normal appliance 75%normal appliance 50%normal appliance 25%normal appliance 10%normal appliance 0%normal appliance 100%normal appliance

Index

Cost $

1 2 3 4 5 6 1

Index 1 2 3 4 5 6 1

Par.1 G13 0.00 2500.00 5000.00 7500.00 9000.00 10000.00 0.00

Cost $

Par.2 7.17 5.92 4.66 3.41 2.65 2.15 7.17

Par.1 G14 0.00 2500.00 5000.00 7500.00 9000.00 10000.00 0.00

Par.3

Par.2 8.1 6.68 5.27 3.85 3.00 2.43 8.1

Par.3

Energy Star appliance: On average, home appliances – including clothes washers, dryers, dishwashers, refrigerators, freezers, air purifiers and humidifiers – will account for 20 percent of your home’s total electric bill. ENERGY STAR appliances, which are certified by the U.S. Department of Energy, can reduce that share. The average home appliance lasts for 10 to 20 years, and an ENERGY STAR-certified appliance will use anywhere from 10 to 50 percent less energy each year than a non-energy efficient equivalent. By replacing the appliances in your home with ENERGY STAR certified appliances, it is making an investment that will reduce your energy bill for years to come, which is especially important when user recognize that electricity rates are increasing every year. Some appliances use more energy than others. The amount project save is also dependent on the age of users’ current appliances and the electricity rates that users’ pay

126

Energy improvement point [ Certificate Level / 0pt] : PI Difference (%)

From Hourly Calculation 5%

Improvement for certificated level 5%: Qdesign,heat,nd [kWh/m2/yr]

1.7256614193272

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

72.0698929036860

Edesign,del [kWh/m2/yr]

94.42219708037

Edesign,p [kWh/m2/yr]

313.680936890791

Improvement Before: Qdesign,heat,nd [kWh/m2/yr] Qdesign,cool,nd [kWh/m2/yr] Edesign,del [kWh/m2/yr] Edesign,p [kWh/m2/yr] Improvement(%) 5%

0 75 99 371 Cost($)

$ 3,580,246

Renew Energy Points 0.00

Get to certificate level: The first stage of optimization is to make the model reach the certificate level. The original proposed model is -26.5% from baseline. The model has a lot of place to improve its performance. Based on the option I put in the EPC TECH OPT, the final result is listing above. The first stage in improve the proposed model cost about 3580246$ and it does not include. Although I do know the total cost and the options that TECH OPT chose, I still don’t know which one is the main option that system used in improving 31% in energy. Here is another RISK analysis with uncertainty simulation. The main reason using RISK analysis in this part is because there are many ways to make model improve to 5% but which one is the most common in the sample. After setting different kind of distribution in optimization options, the result shows BEM is the main optimization system have chosen. The BEM system control is based on prEN 15232:2006 5.3 and 8 the system set simple cut off control of the building this might be the fast and easiest way reach certificate and it also fulfill the energy metering part in other LEED v4 section.

127

5% improvement iteration: 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

A 2 ‐ Partial sensor (25%)

Cost $ Total Cost(Without worker fee)

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

375.00

0.9

Lighting occupancy factor Technology levels

Index

Cost $

Par.1

Par.2

Par.3

C23 B 1 ‐ Baseline (NULL)

0.00

B 2 ‐ Partial sensor (25%)

0.00

0.9

B 3 ‐ Partial sensor (50%)

0.00

0.6

B 4 ‐ Partial sensor (75%)

0.00

0.3

B 5 ‐ Fully autom. sensor

0.00

B 1 ‐ Baseline (NULL)

0.00

Heating and Cooling Plants efficiencies (COPs) Technology levels

Index

Cost $

Par.1

Par.2

C28

C29

D 1 ‐ Baseline HVAC D 2 ‐ HVAC variation 2

1 2

0.00 1974500.00

0.91 2.28

3.6 3.7

D 3 ‐ HVAC variation 3

2530740.00

4.28

4.75

D 4 ‐ HVAC variation 4

3173680.00

6.28

5.8

D 3 ‐ HVAC variation 3

2530740.00

4.28

4.75

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

No heat recovery

Heat exchange plates or pipes (0.65)

936500.00

Heat exchange plates or pipes (0.65)

Two‐elements‐system (0.6)

783500.00

Two‐elements‐system (0.6)

Loading cold with air‐conditioning (0.4)

613500.00

Loading cold with air‐conditioning (0.4)

Heat‐pipes (0.6)

749500.00

Heat‐pipes (0.6)

Slowly rotating or intermittent heat exchangers (0.7)

1177900.00

Slowly rotating or intermittent heat exchangers (0.7)

Heat‐pipes (0.6)

749500.00

Heat‐pipes (0.6)

128

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

Cost $

Par.1 C45

Minimum infiltration Maximum infiltration

0.05 5

0.00

3.81

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

Index

Cost $

Par.1 C52

Electric (0.75)

0.00

Gas Boiler, HR‐Boiler (0.75)

VR‐Boiler (0.61)

61325.00

VR‐Boiler (0.61)

Gas Boiler, HR‐Boiler (0.75)

82675.00

Electric (0.75)

Co‐Generation (0.9)

350110.00

Co‐Generation (0.9)

District Heating (0.9)

24260.00

District Heating (0.9)

Heat Pump (1.4)

65875.00

Heat Pump (1.4)

Steam (0.61)

42075.00

Steam (0.61)

Electric (0.75)

0.00

Gas Boiler, HR‐Boiler (0.75)

Type of BEM system installed Technology levels

Index

Cost $

Par.1 C54

1: Class D

0.00

2: Class C

937422.67

3: Class B

2282420.41

4: Class A

3056813.05

4: Class A

3056813.05

PV module Surface Area (m2) Technology levels

Value

Cost $

Par.1 C58

Minimum # PV modules Maximum # PV modules

0 865.19

86160.42 Solar Collector Surface Area (m2) Technology levels Minimum # Solar Col. Maximum # Solar Col.

Value

Cost $

577.20

Par.1 C64

0 865.19

90944.00

146.16

129

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 t12

Cost $

1 2 3 4 5 6 6

Lighting zone5 (W/m2) Technology levels

0.00 535500.00 595000.00 493000.00 510000.00 544000.00 544000.00

Index

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

Par.1 G13 11.84 5.92 2.96 7.10 9.47 10.66 10.656

Cost $

1 2 3 4 5 6 5

Par.1 G14 0.00 107100.00 119000.00 98600.00 102000.00 108800.00 102000.00

5.2 2.60 1.30 3.12 4.16 4.68 4.16

Roof1 Technology levels

Index

Cost $

Par.1

Par.2

G64

H64

Par.3 I64

Roof Baseline 1

0.00

0.345

0.7

0.9

Ashrae Baseline model

122160.00

0.11

0.7

0.9

Metal cladding roof (E&W), residential building

193420.00

0.307

0.7

0.9

Exposed floor (E&W)

223960.00

0.238

0.7

0.9

Roof Improvement 1.2 mm( new insulation EX Membrane)

264680.00

0.157

0.6

0.9

Roof Improvement 1.7 mm( new insulation EX Membrane)

294880.00

0.13

0.6

0.9

Ashrae Baseline model

122160.00

0.11

0.7

0.9

Opaque1 Technology levels

Index

Cost $

Par.1

Par.2

G66

Par.3

H66

I66

Wall Baseline 1

0.00

0.7

Ashrae Baseline model

126183.75

0.21

0.7

0.9 0.9

Wall Improvement 3 (R‐30 insulation)

138474.38

0.515

0.7

0.9

Wall Improvement 3 (R‐21 insulation)

167152.50

0.47

0.7

0.9

Wall Improvement 4 (R‐19 insulation)

200337.19

0.341

0.7

0.9

Wall Improvement 5 (R‐13 insulation)

221640.94

0.285

0.7

0.9

Wall Improvement 6 (R‐11 insulation)

247860.94

0.813

0.7

0.9

Wall Improvement 3 (R‐30 insulation)

138474.38

0.515

0.7

0.9

Window1 Technology levels

Index

Cost $

Par.1

Par.2

Par.3

G68

I68

J68

Window Baseline 1

3.39

0.84

0.36

Ashrae Baseline model

358500

2.11

0.84

0.25

Double glazing (SCO)

442500

3.28

0.078

0.31

10‐16‐6 uncoated, air‐filled

474000

2.678

0.137

0.22

4‐12‐4 low‐e, air filled

495000

1.77

0.313

0.17

4‐12‐4‐12‐4 triple glazing, low‐e

705000

1.046

0.417

0.15

4‐12‐4‐12‐4 triple glazing, argon‐filled, low‐e

852000

0.68

0.418

0.12

Ashrae Baseline model

358500.00

2.11

0.84

0.25

130

North window ratio Technology levels Minimize Maximum Ratio

Index

Cost $

Par.1 S54

0.3 0.8

5135683.23 South window ratio Technology levels Starting Construction Worker Minimize Maximum Ratio

Index

Cost $ Total Cost(Without worker fee)

0.666554827

Par.1 S50

0.6 0.9

2303100.65 West window ratio Technology levels Starting Construction Worker Minimize Maximum Ratio

Index

Cost $ Total Cost(Without worker fee)

Par.1 S56

0.2 0.8

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

Index

Cost $ Total Cost(Without worker fee)

0.321782543

Par.1 S52

0.2 0.8

9114044.22 Appliance for smallUnits (W/m2) Technology levels 100%normal appliance 75%normal appliance 50%normal appliance 25%normal appliance 10%normal appliance 0%normal appliance 75%normal appliance Appliance for big Units (W/m2) Technology levels 100%normal appliance 75%normal appliance 50%normal appliance 25%normal appliance 10%normal appliance 0%normal appliance 10%normal appliance

Index

Cost $

1 2 3 4 5 6 2

Index 1 2 3 4 5 6 5

0.688948413

Par.1 G13 0.00 2500.00 5000.00 7500.00 9000.00 10000.00 2500.00

Cost $

7.17 5.92 4.66 3.41 2.65 2.15 5.915

Par.1 G14 0.00 2500.00 5000.00 7500.00 9000.00 10000.00 9000.00

8.1 6.68 5.27 3.85 3.00 2.43 2.997

131

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 0.00 6600.00 7600.00 8120.00

0 30 45 60

0.00

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 80 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

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 20 Degree

Index 1 2 3 4

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

13200.00

Index

Par.1 Fin Angle 0 30 45 60

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

Par.1 Horizontal Angle

Par.1 Overhang

1 2 3 4

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

6600.00

1 2 3 4 5 6 7 8 9 9

Index

Index 1 2 3 4

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

0.00

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 10 20 30 40 50 60 70 80 80

0 30 45 60

Par.1 Fin Angle 0 30 45 60

Par.1 Horizontal Angle 0 10 20 30 40 50 60 70 80 20

132

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 30 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

60 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 10 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 0 30 45 60

Par.1 Fin Angle 0 30 45 60

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

Par.1 Horizontal Angle

Par.1 Overhang

1 2 3 4

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

6600.00

1 2 3 4 5 6 7 8 9 4

Index

Index 1 2 3 4

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

16240.00

Index 1 2 3 4 5 6 7 8 9 2

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

0 10 20 30 40 50 60 70 80 30

0 30 45 60

Par.1 Fin Angle 0 30 45 60

Par.1 Horizontal Angle 0 10 20 30 40 50 60 70 80 10

133

Result:

Next step process: Based on all iteration in previous pages, I finally get to make the model to certificate level. The previous page also realize which one is the option that it improve the most. For the next step, it is good to know which iteration that system might start to optimize. Based on the RISK analysis for the whole building, the next step system will choose are Building air leakage level. The main reason that tornado plot show can be connected to the next step option is because the tornado plot above do reveal the current analysis main reason that caused the cooling load and deliver energy. The cooling load and deliver energy should have choosing the same option since the project is cooling dominated. The result above do choose the same option to make the model go to the next level. Finally the next step is going to be improve the model to 6 %. The next page will not list other option to 6% -50% but only 50%. For more detail in 6%-48% please contact me for more detail explanation.

134

Energy improvement point [ 50% / 18pt] : PI Optimization Points

From Hourly Calculation 18

Improvement for certificated level 50%: PI

From Hourly Calculation

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

0.2905684944703

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

58.9142966728858

Edesign,del [kWh/m2/yr]

51.88617479408

Edesign,p [kWh/m2/yr]

210.041677251124

Improvement Before: Qdesign,heat,nd [kWh/m2/yr] Qdesign,cool,nd [kWh/m2/yr] Edesign,del [kWh/m2/yr] Edesign,p [kWh/m2/yr] Improvement(%) 50%

0 75 99 371

Cost($) 13,640,831

Renew Energy Points 2.00

Limit goal for LEED V4: Since the largest energy improvement percentages is 50%, I list my report only the lowest and the highest. For more detail in simulation from 6%-48% please let me know. The end of the improvement 50% mainly chose window properties as their main strategies for improving 76% from proposed to current model. The other things I would like to talk about is the corresponding of the Risk analysis and its tornado plot. Based on the tornado plot the main system chose is window property. The property include U vale and the most important Solar Transmittance. This result do respond the previous detail simulation in solar gain part. Changing window property in this project probably the most efficient way to do during optimization.

135

50% improvement iteration: Lighting daylighting factor Technology levels

Index

Cost $

Par.1

Par.2

Par.3

C22 A 1 ‐ Baseline (NULL)

0.00

A 2 ‐ Partial sensor (25%)

102000.00

0.9

A 3 ‐ Partial sensor (50%)

204000.00

0.6

A 4 ‐ Partial sensor (75%)

306000.00

0.3

A 5 ‐ Fully autom. sensor

408000.00

A 3 ‐ Partial sensor (50%)

204000.00

0.6

Lighting occupancy factor Technology levels

Index

Cost $

Par.1 C23

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

1 0.9 0.6 0.3 0

B 3 ‐ Partial sensor (50%)

0.00

0.6

Heating and Cooling Plants efficiencies (COPs) Technology levels

Index

Cost $

Par.1

Par.2

C28

C29

D 1 ‐ Baseline HVAC

0.00

0.91

3.6

D 2 ‐ HVAC variation 2

1974500.00

2.28

3.7

D 3 ‐ HVAC variation 3

2530740.00

4.28

4.75

D 4 ‐ HVAC variation 4

3173680.00

6.28

5.8

D 1 ‐ Baseline HVAC

0.00

0.91

3.6

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

No heat recovery

Heat exchange plates or pipes (0.65)

936500.00

Heat exchange plates or pipes (0.65)

Two‐elements‐system (0.6)

783500.00

Two‐elements‐system (0.6)

Loading cold with air‐conditioning (0.4)

613500.00

Loading cold with air‐conditioning (0.4)

Heat‐pipes (0.6)

749500.00

Heat‐pipes (0.6)

Slowly rotating or intermittent heat exchangers (0.7)

1177900.00

Slowly rotating or intermittent heat exchangers (0.7)

No heat recovery

0.00

No heat recovery

136

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

0.00

3.69

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

Index

Cost $

Par.1 C52

Electric (0.75)

0.00

Gas Boiler, HR‐Boiler (0.75)

VR‐Boiler (0.61)

61325.00

VR‐Boiler (0.61)

Gas Boiler, HR‐Boiler (0.75)

82675.00

Electric (0.75)

Co‐Generation (0.9)

350110.00

Co‐Generation (0.9)

District Heating (0.9)

24260.00

District Heating (0.9)

Heat Pump (1.4)

65875.00

Heat Pump (1.4)

Steam (0.61)

42075.00

Steam (0.61)

VR‐Boiler (0.61)

61325.00

VR‐Boiler (0.61)

Type of BEM system installed Technology levels

Index

Cost $

Par.1 C54

1: Class D

0.00

2: Class C

937422.67

3: Class B

2282420.41

4: Class A

3056813.05

2: Class C

937422.67

PV module Surface Area (m2) Technology levels

Value

Cost $

Par.1 C58

Minimum # PV modules Maximum # PV modules

0 865.19

27167.70 Solar Collector Surface Area (m2) Technology levels Minimum # Solar Col. Maximum # Solar Col.

Value

Cost $

182.00

Par.1 C64

0 865.19

464128.00

745.92

137

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

Cost $

1 2 3 4 5 6 4

Lighting zone5 (W/m2) Technology levels

0.00 535500.00 595000.00 493000.00 510000.00 544000.00 493000.00

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)

Par.1 G13 11.84 5.92 2.96 7.10 9.47 10.66 7.104

Cost $

1 2 3 4 5 6 2

Par.1 G14 0.00 107100.00 119000.00 98600.00 102000.00 108800.00 107100.00

5.2 2.60 1.30 3.12 4.16 4.68 2.6

Roof1 Technology levels

Index

Cost $

Par.1

Par.2

G64

H64

Par.3 I64

Roof Baseline 1

0.00

0.345

0.7

0.9

Ashrae Baseline model

122160.00

0.11

0.7

0.9

Metal cladding roof (E&W), residential building

193420.00

0.307

0.7

0.9

Exposed floor (E&W)

223960.00

0.238

0.7

0.9

Roof Improvement 1.2 mm( new insulation EX Membrane)

264680.00

0.157

0.6

0.9

Roof Improvement 1.7 mm( new insulation EX Membrane)

294880.00

0.13

0.6

0.9

Exposed floor (E&W)

223960.00

0.238

0.7

0.9

Opaque1 Technology levels

Index

Cost $

Par.1

Par.2

G66

Par.3

H66

I66

Wall Baseline 1

0.00

0.7

Ashrae Baseline model

126183.75

0.21

0.7

0.9 0.9

Wall Improvement 3 (R‐30 insulation)

138474.38

0.515

0.7

0.9

Wall Improvement 3 (R‐21 insulation)

167152.50

0.47

0.7

0.9

Wall Improvement 4 (R‐19 insulation)

200337.19

0.341

0.7

0.9

Wall Improvement 5 (R‐13 insulation)

221640.94

0.285

0.7

0.9

Wall Improvement 6 (R‐11 insulation)

247860.94

0.813

0.7

0.9

Wall Improvement 3 (R‐30 insulation)

138474.38

0.515

0.7

0.9

Window1 Technology levels

Index

Cost $

Par.1

Par.2

Par.3

G68

I68

J68

Window Baseline 1

3.39

0.84

0.36

Ashrae Baseline model

358500

2.11

0.84

0.25

Double glazing (SCO)

442500

3.28

0.078

0.31

10‐16‐6 uncoated, air‐filled

474000

2.678

0.137

0.22

4‐12‐4 low‐e, air filled

495000

1.77

0.313

0.17

4‐12‐4‐12‐4 triple glazing, low‐e

705000

1.046

0.417

0.15

4‐12‐4‐12‐4 triple glazing, argon‐filled, low‐e

852000

0.68

0.418

0.12

4‐12‐4‐12‐4 triple glazing, argon‐filled, low‐e

852000.00

0.68

0.418

0.12

138

North window ratio Technology levels Minimize Maximum Ratio

Index

Cost $

Par.1 S54

0.3 0.8

103229.81 South window ratio Technology levels Starting Construction Worker Minimize Maximum Ratio

Index

Cost $ Total Cost(Without worker fee)

0.3

Par.1 S50

0.6 0.9

12167142.86 West window ratio Technology levels Starting Construction Worker Minimize Maximum Ratio

Index

Cost $ Total Cost(Without worker fee)

Par.1 S56

0.2 0.8

49147266.80 East window ratio Technology levels Starting Construction Worker Minimize Maximum Ratio

Index

Cost $ Total Cost(Without worker fee)

0.703233019

Par.1 S52

0.2 0.8

49516087.53 Appliance for smallUnits (W/m2) Technology levels 100%normal appliance 75%normal appliance 50%normal appliance 25%normal appliance 10%normal appliance 0%normal appliance 75%normal appliance Appliance for big Units (W/m2) Technology levels 100%normal appliance 75%normal appliance 50%normal appliance 25%normal appliance 10%normal appliance 0%normal appliance 100%normal appliance

Index

Cost $

1 2 3 4 5 6 2

Index 1 2 3 4 5 6 1

0.708510361

Par.1 G13 0.00 2500.00 5000.00 7500.00 9000.00 10000.00 2500.00

Cost $

7.17 5.92 4.66 3.41 2.65 2.15 5.915

Par.1 G14 0.00 2500.00 5000.00 7500.00 9000.00 10000.00 0.00

8.1 6.68 5.27 3.85 3.00 2.43 8.1

139

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

Baseline 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

Baseline 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 70 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

0.00

Index

Par.1 Overhang 0 30 45 60

Par.1 Fin Angle 0 30 45 60

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

Par.1 Horizontal Angle

Par.1 Overhang

1 2 3 4

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

0.00

1 2 3 4 5 6 7 8 9 6

Index

Index 1 2 3 4

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

0.00

Index 1 2 3 4 5 6 7 8 9 8

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

0 10 20 30 40 50 60 70 80 50

0 30 45 60

Par.1 Fin Angle 0 30 45 60

0 Par.1 Horizontal Angle 0 10 20 30 40 50 60 70 80 70

140

North Shading‐South Overhang Angle Technology levels

Index

Starting Construction Worker

Cost $

Par.1

Total Cost(Without worker fee)

Overhang

Baseline

0.00

30 Degree

6600.00

45 Degree

7600.00

60 Degree

8120.00

60 Degree

8120.00

North Shading‐South Fin Angle Technology levels

Index

Starting Construction Worker

Cost $

Par.1

Total Cost(Without worker fee)

Fin Angle

Baseline

0.00

30 Degree

13200.00

45 Degree

15200.00

60 Degree

16240.00

45 Degree

15200.00

North Shading‐South Horizontal Angle Technology levels

Index

Starting Construction Worker

Cost $

Par.1

Total Cost(Without worker fee)

Horizontal Angle

Baseline

0.00

10 Degree

6600.00

20 Degree

6760.00

30 Degree

6920.00

40 Degree

7080.00

50 Degree

7240.00

60 Degree

7400.00

70 Degree

7560.00

80 Degree

7700.00

20 Degree

6760.00

West Shading‐South Overhang Angle Technology levels

Index

Starting Construction Worker

Cost $

Par.1

Total Cost(Without worker fee)

Overhang

Baseline

0.00

30 Degree

6600.00

45 Degree

7600.00

60 Degree

8120.00

45 Degree

7600.00

West Shading‐South Fin Angle Technology levels

Index

Starting Construction Worker

Cost $

Par.1

Total Cost(Without worker fee)

Fin Angle

Baseline

0.00

30 Degree

13200.00

45 Degree

15200.00

60 Degree

16240.00

45 Degree

15200.00

West Shading‐South Horizontal Angle Technology levels

Index

Starting Construction Worker

Cost $

Par.1

Total Cost(Without worker fee)

Horizontal Angle

Baseline

0.00

10 Degree

6600.00

20 Degree

6760.00

30 Degree

6920.00

40 Degree

7080.00

50 Degree

7240.00

60 Degree

7400.00

70 Degree

7560.00

80 Degree

7700.00

20 Degree

6760.00

141

Result:

Next step ??? The previous simulation in 5% the system the tornado plot still give the result that are possible to solve during the next step. The line work in 5% tornado plot have one to two clear difference. As the time goes through the result of the tornado plot 50% become more equal during the simulations. The main reason is that the improvement in this stage is already up to 76% from proposed to current model. It probably reach the limit. Although it still have some space to make more improvement, its improvement range can not be as big as the one I did 5%. So the final tornado plot the next step for cooling load and deliver energy start to split out and each strategy rank very close this also means these strategies all can work in improving more than 50%. It is also said that the improvement in this stage have even more option than the previous one since it do not have main issue in after optimization model.

142

LEED Gold Optimization For Bristol 2 : Energy optimize points $18,000,000 $16,000,000 $14,000,000

Cost $

$12,000,000 $10,000,000 $8,000,000 $6,000,000 $4,000,000 $2,000,000 $‐ 0

Energy Performance Points

Renew energy percentage Factors $800,000.00 $700,000.00 $600,000.00

Cost $

$500,000.00 $400,000.00 $300,000.00 $200,000.00 $100,000.00 $‐ 0

Renewal Energy Points LEED Energy Performance Optimization Equation: Based on each step TECH OPT optimization, I can try to come up the project's own equation just like the paper I mentioned in LEED Optimization. All result have energy improvement percentages and the cost of each step percentages. The meaning for the first graph’s equation is to give design team the fully looks their project’s performing in LEED energy improvement each step. The result shows there might be point that the cost will dramatically raise up and after go over that point the cost will cost design team so much to optimize the building. I would suggest the team just need to reach the 4 or 5 points in this project since after this point the cost will jump from 5,000,00$ to 2,000,000,$. This gap is very hard to accept. The other I would like to list it in the optimization is the Renew energy percentage. In this section the point range is smaller than performance, but it still can generate the curve for the design team. Based on the graph for renew energy , I would suggest the team why not go for 2 to 5 points. The gap between these two section only have 250,000$ difference but for 1to 2 have 300,000$ difference.

143

Renewable Energy: Renew energy percentage 12%

Improvement Percentage

10%

0% 0.00E+00

1.00E+05

2.00E+05

3.00E+05

4.00E+05

5.00E+05

6.00E+05

7.00E+05

8.00E+05

Cost $

PV iMPROVEMENT CURVE 1200 1000

Area (m2)

800 600 400 200 0 0%

Renewable Energy Percentage (%) Renew energy percentage: Based on the renew energy percentage result, I detail analyze the renew energy detail information. For the first graph above it list the relationship between the cost and how much renew energy it will produce, or I would say the cost of renew energy. This project is a high rise residential the renew energy will depend on solar grid and solar DHW system since the square footage of the building is very small and it can not have open space to put wind turbine. In real condition not all roof can make the whole area fully PV. It have to based on roof’s condition and the cost of the payback grid so in first graph the renew energy percentage is linearly scaling before 5% but in the second graph I break the limit of the roof condition and make the PV fully install on the roof , the cost and the renew energy percentage both rise up to huge number. This also can say that PV grid for the building is the main source that causing the renew energy percentages.

144

LEED Gold Whole Section Optimization This chapter is all about the cost for the other section in LEED Gold v4 criteria. These fata is going to prepare for the next step LEED Gold optimization and energy optimize pointâ&#x20AC;&#x2122;s efficiency .

145

LEED Gold Optimization High-rise Construction Cost Reference: The next section is going to need each section’s cost to solve the LEED Gold optimization in my own LEED calculator . For each section all need to be count and highly estimate the section cost. To begin estimate the cost for each section. I need to know the total construction cost for Tower2. The main reason is that the cost of each section is combine section optimize might also optimize other section’s very small part. The method I am going to use reference some document and made a bold assumption for each section. Since every single section is bounded together as a construction project. I will use the whole project's construction cost and the reference document’s ratio in each section then produce linear cost equation for each section.

$15751243.26 $24479026.39 Project Cost Detail Floor Area(M2) Total units Site Area(M2) Construction cost(US$) Sustainable Ratio Factor

MEP COST Annual Ele Cost Annual Green offset cost

37865

Philippines Labor cost

340

$2.06

US Labor Cost

$39.03

PH Construction Cost per SQM

$238.56

LEED Premium Cost

$21,513,485.92

74523 $19,475,611 0.05 $4,868,902.64 320725 Construction cost per sqf LEED Certificated cost 0.04 perium

Volume (sqf3) FAÇADE AREA

1630300.294 1607010.29

$47.78 Average US household income

$ 64,430.00

$52.78 Average PHP household income

$ 53,101.21

The Cost of LEED v4: This report was created to demystify the costs associated with pursuing building project certification under the LEED for new construction version 4 rating system. Perceived cost premiums have always been an impediment to wider adoption of green building practices and LEED. That predicament led Building Green to produce the 2010 report “The Cost of LEED 2009,” which evaluated specific sustainable design strategies based on their relative costs. That report clearly highlighted green strategies with no cost premium or cost savings and drew systematic connections between strategies in the context of the LEED for New Construction (LEED-NC) rating system v2009. Since the U.S. Green Building Council (USGBC) released LEED v4 in 2013, the market has again been uncertain about the costs and benefits of LEED certification. Largely due to the uncertainties regarding cost, as well as not knowing how projects would fare under the new system with new requirements, many project teams have been on the fence about whether to upgrade.

146

Assumption disclaimer • These assumption is organized based on the LEED BD+C: New Construction and Major Renovation version 4, or LEED-NC v4. Other LEED rating systems and “adaptations” (to use the LEED v4 term), especially other LEED BD+C adaptations, can use the information on sustainability strategies, but not every credit will be applicable. The more detail information all reference from The Cost of LEED v4 by Building Green, Inc. and USGBC • This analysis utilizes a generic commercial or institutional building as a benchmark, except where otherwise noted. types. • Construction cost premiums are listed in some cases in percentages of construction cost, and in some cases actual dollar costs. Cost data is based on average U.S. construction costs from 2015. Construction costs include materials, installation (labor), and overhead. • This assumption lists cost synergies between credits that are often dependent on local, project-specific factors in here I just assume it as linear equation . I list and organize the places where complying with the requirements of one credit would financially impact, negatively or positively, compliance with other related credits, usually by sharing costs. The cost I didn’t list on the assumption is based on designer in other wards it is an easy job and could be done by designer team with more passion on LEED. These won’t cost any money. • Local regulations often impose project requirements that carry cost premiums that are outside of sustainable design considerations. Compliance with these requirements would not constitute a sustainable design cost “premium” for the project but rather should be considered as base project cost. Intelligent analysis of those requirements may assist the project in achieving other sustainable goals without an added premium. • All cost do not include requirement in LEED’s cost. That is because I assumed to get LEED requirement is mandatory for the project that need to reach LEED Gold.

147

LEED Gold Optimization- Location and Transportation High Priority Site

Bicycle Facilities

Reduced Parking Footprint

Location and Transportation Credit Credit Credit Credit Credit Credit Credit Credit

LEED for Neighborhood Development Location Sensitive Land Protection High Priority Site Surrounding Density and Diverse Uses Access to Quality Transit Bicycle Facilities Reduced Parking Footprint Green Vehicles

Green Vehicles

Cost

Labor Hour

Total Cost

Cost Per Points

$0.00

1 2 5 5 1 1 1

0$ $389,512 0$ 0$ $1,132,289 $1,752,805 $44,737

0$ 50 0$ 0$ 198 199 0

0$ $389,615 0$ 0$ $1,132,697 $1,760,572 $44,737

$0.00 $389,615 $0.00 $0.00 $1,132,697 $92,662 $44,737

LTc: The cost of locating a project within a LEED for Neighborhood Development (LEED-ND) is very projectspecific, and beyond the scope of this study. There is no general reason for a cost premium, unless the development as a whole is being built on a premium basis, but in that case the cost would not be related to the specific building, or to LEED. Achieving this credit does result in immediate cost savings for the individual project, however. This credit is an alternative compliance path for the entire LT category in LEED BD&C, and therefore earning this credit reduces LEED documentation needs. Also, while this is a project-specific factor, a LEED-ND location provides shared green infrastructure that is likely to reduce the cost of green strategies for individual projects. Locating projects in LEED-ND locations also brings overall economic, social, health, and sustainable design benefits associated with the master plan, due to location, access, parking, and land conservation..

148

LEED Gold Optimization- Sustainable Site Site Developmentâ&#x20AC;&#x201D;Protect or Restore Habitat

Rainwater Management

Heat Island Reduction

Light Pollution Reduction

Sustainable Sites

Prereq

Construction Activity Pollution Prevention

Credit

Site Assessment

Credit

Site Development - Protect or Restore Habitat

Credit

Open Space

Credit

Rainwater Management

Credit

Heat Island Reduction

Credit

Light Pollution Reduction

Cost

Labor Hour

Total Cost

Cost Per Points

Required 0$

0$ $29,809

0$ 132

$30,081

200

$243,127

$81,042

200

$110,582

$55,291

$735,988

0$ $242,715 $102,776 $13,983,766

$0.00 $30,081

SSc: The price here for un-cost is the Assessment and Open space. For assessment: Due to strategies identified or explored through the assessment process and cost synergies with other LEED credits, this credit is more likely to produce cost savings than added costs. It requires a site survey or assessment that is intended to provide useful information informing site design, ideally in an integrative process (conducted through IPc1). The site assessment should include topography, hydrology, climate, vegetation, soils, human uses, and human health effects (related to site). For Open space, even though the reference document include the open space cost, but here I will just leave it as no cost. I think in the project it already include even though it might need some additional pavement or grass but like I say it will just be drawing work in the studio it will not be a massive work

149

LEED Gold Optimization- Water Efficiency Outdoor Water Use Reduction

Indoor Water Use Reduction

Building-Level Water Metering and Water Metering

Cooling Tower Water Use

Water Efficiency Prereq Prereq Prereq Credit Credit Credit Credit

Outdoor Water Use Reduction Indoor Water Use Reduction Building-Level Water Metering Outdoor Water Use Reduction Indoor Water Use Reduction Cooling Tower Water Use Water Metering

Cost

Labor Hour

Total Cost

Cost Per Points

Required Required Required 2 6 2 1

$220,635 $82,496 $30,000 $35,789

200 200 550 450

$221,047 $82,908 $31,133 $36,716

$110,523 $13,818 $15,567 $36,716

WE: Reducing water used in irrigation can conserve scarce groundwater resources, and generally reduce demand for potable water that is becoming scarcer in many parts of the world. This part is very hard to estimate the water reduction is going to need each pipe optimization and all comes down to MEP construction. In the other words, in some cases I need to use the total MEP in the construction cost to estimate the cost of this section. I would say this section do need more detail cost but here I will leave it to the MEP guys. Additionally, LEED v4 requires water metering (manual or automated) to cover all potable water uses for the associated grounds on a monthly and annual basis, which represents an added cost. Note that water metering costs can be greatly reduced by being spread over the whole cost of the Building Automation System (BAS).

150

LEED Gold Optimization- Water Efficiency Enhanced Commissioning

Energy Metering

Demand Response

Green Power and Carbon Offsets

Energy optimize points $18,000,000 $16,000,000 $14,000,000

Cost $

$12,000,000 $10,000,000 $8,000,000 $6,000,000 $4,000,000 $2,000,000 $‐ 0

Energy Performance Points

151

Renew energy percentage Factors $800,000.00

Cost $

$600,000.00 $400,000.00 $200,000.00 $‐ 0

Renewal Energy Points Energy and Atmosphere

Cost

Labor Hour

Total Cost

Cost Per Points

Prereq

Fundamental Commissioning and Verification

Required

Prereq

Minimum Energy Performance

Required

Prereq

Building-Level Energy Metering

Required

Prereq

Fundamental Refrigerant Management

Required

Credit

Enhanced Commissioning

$7,500

Credit

Optimize Energy Performance

$35,714

Credit

Advanced Energy Metering

$32,073

Credit

Demand Response

$151,4600$

Credit

Renewable Energy Production

$10,000

Credit

Enhanced Refrigerant Management

Credit

Green Power and Carbon Offsets

$4,302,697.2

$4,310,197.18

$151,460

$718,366

$75,730 $10,000

$0 $6,415

EA: In this section the big two assumption is come my linear line I did in previous page and the only one without any cost is the Enhance Refrigerant Management. There’s no getting around it: adding renewable energy production capacity to a project is likely to be an added cost. However, costs are coming down—for solar photovoltaic (PV), at least—and projects are increasingly finding a variety of benefits to add renewables, including tax advantages, added value, and locked-in pricing.

LEED Gold Optimization- MATERIALS & RESOURCES Building-Level Water Metering and Water Metering

Materials and Resources Prereq Prereq Credit Credit Credit

Credit

Storage and Collection of Recyclables Construction and Demolition Waste Management Planning Building Life-Cycle Impact Reduction Building Product Disclosure and Optimization Environmental Product Declarations Building Product Disclosure and Optimization - Sourcing of Raw Materials Building Product Disclosure and Optimization - Material Ingredients Construction and Demolition Waste Management

Cost

Labor Hour

Cost Per Points

Total Cost

Required Required 5

$205,006

600

$206,242

0 0 $103,121

0 0

MR: This section highly connect with the energy performance section since choosing material of the building include in the TECH OPT system. Based on these assumption, some of the section which may need to use energy efficient material I will leave it as no cost. The only section that is going to have cost is the Disclosure and Optimization. The section need to use Bio material and other High tech material to the building. This process I do not key in to the TECH OPT system. These material need additional cost that is the reason that I count it as cost.

152

LEED Gold Optimization- ENVIRONMENTAL QUALITY Enhanced Indoor Air Quality Strategies

Low-Emitting Materials

Indoor Air Quality Assessment

Acoustic Performance

Daylight

Interior Lighting

Indoor Environme ntal Quality

Credit

Minimum Indoor Air Quality Performance Environmental Tobacco Smoke Control Enhanced Indoor Air Quality Strategies Low-Emitting Materials

Credit

Construction Indoor Air Quality Management Plan

Credit

Indoor Air Quality Assessment Thermal Comfort Interior Lighting Daylight Quality Views Acoustic Performance

2 1 2 3 1 1

Prereq Prereq Credit

Credit Credit Credit Credit Credit

Cost

Required Required 2 3

Labor Hour

$13,421 $1,735,908 0$

Total Cost

700 700 0$

$15,700 0$

700 0$

$510,000 $170,000 0$

$902 0$

468 468 0$

$803,505

$14,863 $91,439

$26,893 $8,998 0$

700

$42,366

Cost Per Points

$7,432 $30,480 $0 $451 $0 $13,446 $2,999 $0 $42,366

EQ: This section include a lot of strategies I used in previous TECH OPT section. The ratio I count the cost is using the cost in TECH OPT result. These cost sometime will have some overlap with the energy performanceâ&#x20AC;&#x2122;s cost. The way I did to solve these problem is taking the reference ratio as additional cost for TECH OPT. The only three section can not quantify are View, Comfort, Management Plan. For view, I say this is consider during design process. For comfort, this include more complicated calculate. The comes with HVAC and Design par. Here I would assumed the result is already consider the comfort requirement and the system is using the high quality one. Finally, the construction management plan. These can be done by choosing the right contractor or manage a plan with contractor. This will not cost any additional money3.

153

LEED Optimizer and Final Result How is the projectâ&#x20AC;&#x2122;s LEED looks? How is its points distribution looks like in average LEED Gold projects ? How can I process the next step of the of the efficient points in energy optimize part? This question will be answered in this section. The chapter I will also introduce my own calculator solver for LEED Gold optimization. The process include RISK optimizer and SOLVER. This chapter will also tell the designer my final decision whether they have to pursue the LEED Gold in this project or not.

154

LEED Gold Optimizer - Solver system

Creation: The next stage’s calculation is all based on my own LEED OPT The optimization will calculate ten project that based on USGBC’s website and then each points will come with price and its own leaner equation. The only thing I will do is setting its final result function how you want the system to optimize Based on my research target the things I have to optimize is the cost and points. However, these criteria can be changed based on user’s define and this calculator can also work on LEED Platinum or Silver etc.

155

LEED Gold Optimization- 10 Project Estimation Location and Transportation $1,200,000

$1,000,000

P2 P3

Cost $

$800,000

P4 $600,000

$400,000

P6 P7

$200,000

P8 $0 LEED for Neighborhood Development Location

Sensitive Land Protection

High Priority Site

Surrounding Density and Diverse Uses

Access to Quality Transit

Bicycle Facilities Reduced Parking Green Vehicles Footprint

P9 P10

Sustainable Sites $300,000 P1 $250,000

P2 P3

Cost $

$200,000

$150,000

$100,000

P6 P7

$50,000

P8 $0 Construction Site Assessment Site Activity Development ‐ Pollution Protect or Prevention Restore Habitat

Open Space

Rainwater Management

Heat Island Reduction

Light Pollution Reduction

P9 P10

Water Efficiency $800,000 $700,000 $600,000 $500,000 $400,000 $300,000 $200,000 $100,000 $0

P1 P2 P3 P4 P5 P6 P7 P8 P9 P10

156

Location and Transportation $1,200,000 P1

$1,000,000 $800,000

$600,000

$400,000

$200,000

P6 P7 P8 P9 P10

Energy and Atmosphere $5,000,000 $4,500,000 $4,000,000 $3,500,000 $3,000,000 $2,500,000 $2,000,000 $1,500,000 $1,000,000 $500,000 $0

P1 P2 P3 P4 P5 P6 P7 P8 P9 P10

Materials and Resources $120,000 $100,000

$80,000

$60,000

$40,000

$20,000

P6 P7 P8 P9 P10

157

Indoor Environmental Quality $100,000 $90,000

$80,000

$70,000

$60,000

$50,000

$40,000

$30,000

$20,000

$10,000 $0

P9 Minimum Environmental Indoor Air Tobacco Smoke Quality Control Performance

Enhanced Indoor Air Quality Strategies

Low‐Emitting Materials

Construction Indoor Air Quality Management Plan

Indoor Air Quality Assessment

Thermal Comfort

Interior Lighting

Daylight

Quality Views

Acoustic Performance

Innovation 6

Points

5 4 3 2 1 0 Innovation

LEED Accredited Professional

P1 P2 P3 P4 P5 P6 P7 P8 P9 P10

Regional Priority

Points

P10

1.2 1 0.8 0.6 0.4 0.2 0

P3 P4 P5 P6 P7 P8 Regional Priority: Specific Credit

Regional Priority: Specific Credit

P9 P10

Average LEED Gold points for v4: In previous pages I manage the LEED v4 each section’s cost and how to quantify the total cost for each detail section. Here is another question : how is the project other section points going ? What is the total point Bristol will get? Last but not least, how match will it cost for the project to reach efficient LEED Gold points? The method I will use is to summarize 10 LEED Gold projects and do the average points for each section. This bold assumption can give me a clue which LEED Gold points distribution. After I get the average points for LEED Gold, I can assume this project also can follow this average point as the first step of its points optimization. The project object is to reach LEED Gold and all data above can also give project a quick look which section is the efficient section which other 10 project reached. After getting the average point off all section and its total points I can use previous energy improvement equation and renew energy equation to count current project LEED Cost and then I separate it into two section 1 is the part I use equation to generate(Energy improvement, Renew Energy percentage) the other is the rest of the section. This will be my optimization baseline model

158

LEED Gold Optimization Price Tag Calculator- Average Project : 10 Average LEED Gold Points Distribution 25

Points 68

Points

20 15

Total Cost Other Section cost

$16,334,741 $5,719,205

Energy OPT cost

$10,615,536

Optimization matrix

4.20576E-06

10 5 0

Average points and its distribution: Based on previous page’s assumption, the average LEED Gold points can be engaged by an uncertainty analysis. Since each section is based on mean number for 10 sample (10 v4 Gold projects), the original assumption is already a distribution. With the help of the RISK’s uncertainty analysis, result can generate into a single tornado plot. The result of the tornado plot shows that the Energy Optimization performance is the main impact on Average Total Points. These outcome seems reasonable since the section maximum can reach almost 19 credit points. For the next step’s optimization, I set up an optimization factor. The factor is Total Points / Total Cost. My goal is to make the ratio as big as it can. This means the Total Points going to be bigger than 59 which accomplish the LEED Gold criteria and for Total cost it going to be as small as possible. For optimization goal is to reach the points that Energy improvement add renew energy points equal to rest of the total cost. These information can tell design team to stop pursue energy optimization and pursue other section’s points

159

Risk analysis with Monte Carol Analysis calibration: The result I set for average analysis is based on 10 LEED Gold projects but I personally not sure about whether the assumptions is reasonable enough or not. Here is what I did for the basic calibration. I set distribution as uniform for each sectionâ&#x20AC;&#x2122;s points and than run the RSIK analysis with 100 sample. After the result I mainly focusing in the average points and Total cost. Then I used Monte Carol analysis to make sure the result I get have highly possibility. The graph above shows that for average points my result is 63 points and in Monte Carol analysis the possibility is about 83%. For total cost, my result is 16 millions it reach about 77.8% possibility. These result shows the basic data calibration, and both are trustable. These result can not only used in calibration but also used in optimization check. If any optimization in the next page can lower the average points and total cost then make sure there possibility are very high. The data is going to be the ultimate for the result.

160

LEED Gold Optimization - First Optimization (Without Risk): First Optimization LEED Gold Points Distribution 25

Points

Points 67

Total Cost Other Section cost Energy OPT cost Optimization matrix

$13,459,307 $6,720,032 $6,739,275 4.98E-06

15 10 5 0

Excel Solver blind zone: Here is the first try I used for optimization. The method I am using in this stage is Excel’s solver. The logic I set is very simple. The main goal is to set the optimization factor as big as it can be. The restriction is total points must be bigger than 59 points but smaller than 79 points which is LEED Gold requirement. The other restriction in this stage is the make sure the other points cost and energy optimization cost be equal together. The second logic is to make sure the system chose the correct point and let designer team to deicide which point they can stop optimize. After the logic the solver chose each section pretty much the same as previous one and the tornado plot criteria stays the same. I assume this simulation is not a best result for reaching our goal. The main reason is that the solver only have to lower 1 or 2 points from the energy performance and let the other section points gain 1 or 2 more it can fill up the blank that caused by energy optimization. This not the case I want.

161

Optimize surface? With plotting optimization result, it is clear that the optimization did not even make the model better. Based on first graph above, the points in final result even get smaller the energy optimization points only lower 1 point. The possibility in graph 1 is 67points to 87.5% the original one is 68 points to 83.3%. These gap did not have very clear difference and improvement. Next is the total cost, this time is even worst. In previous optimize before the cost 143 million to 77% here is 135 million to 50%. Total cost only decrease 8 millions but the chance fall 27%. The possibility drop dramatically. These result is not the best condition for the optimization points result. The main reason is because the distribution in each sectionâ&#x20AC;&#x2122;s points do not have any uncertainty and using solver only change the surface of the model it just complete the restriction, but the process had a lot of uncertainty it not only appear in cost but also in each sectionâ&#x20AC;&#x2122;s points. Without proper assumption the optimization is just fulfil surface phenomenon.

162

LEED Gold Optimization - Final Optimization (Adding Risk): Final Optimization Points Distribution 16

Points 70

14 12

Points

Total Cost Other Section cost

$4,332,069

Energy OPT cost

$3,725,745

Optimization matrix

$8,057,814

8.52589E-06

8 6 4 2 0

Risk optimization: After previous optimization with solver, I produce the other strategies. The RISK optimizer. With RISK optimizer the result is going to be optimized by solver plus uncertainty. The result is list above. According to the result, the final point have dramatically changed in each section. The first big change is the energy optimization section. In previous optimization, the Energy and Atmosphere section only decrease one to two points but this time the RSIK optimizer chose to let the Energy Atmosphere decrease to only 6 points. That is interesting choice. For optimization factor also have a very big change the factor right now is 2 times bigger than the original number and its total score increase to 70 points, Total cost decrease from 13 millions to 8 millions. These phenomenon all shows the optimization function work for the whole model and it does follow the optimization logic. For tornado plot in the final result, since the energy performance points go down the main convert for decision turned into total construction cost. It seems like the system suggest design team to go for more points on the other section. The main impact on the section is the total construction cost and result do reflect that.

163

Final Result: After Risk Optimizer, the result of the total costâ&#x20AC;&#x2122;s Monte Carol analysis shows the cost in current optimize have 72% possibility. The cost is 8.3 millions. The number is way lower than original cost which is 16 millions and its possibility is also 73%. The result make the whole cost lower than original and its possibility is bigger than that. For optimization function, the final optimize parameter is 8.6millions and its possibility is 62%. For solverâ&#x20AC;&#x2122;s optimization function is 4.9 millions and it possibility is 55%. This is very clear that the optimization function in Risk Analysis do make the whole points and cost more efficient.

164

LEED Gold Optimization - Final Iteration Detail Location and Transportation

Sustainable Sites

Prereq

Construction Activity Pollution Prevention

Required

Credit

Site Assessment

Credit

Site Development ‐ Protect or Restore Habitat

Credit

Open Space

Access to Quality Transit

Credit

Rainwater Management

Credit

Bicycle Facilities

Credit

Heat Island Reduction

Credit

Reduced Parking Footprint

Credit

Light Pollution Reduction

Credit

Green Vehicles

1 33

Credit

LEED for Neighborhood Development Location

Credit

Sensitive Land Protection

Credit

High Priority Site

Credit

Surrounding Density and Diverse Uses

Credit

Energy and Atmosphere Water Efficiency Prereq

Outdoor Water Use Reduction Required

Prereq

Indoor Water Use Reduction Required

Prereq

Building‐Level Water Metering Required

Prereq Prereq Prereq

Credit

Outdoor Water Use Reduction

Prereq Credit Credit

Credit

Indoor Water Use Reduction

Credit

Cooling Tower Water Use

Credit

Water Metering

Credit Credit Credit Credit Credit

Materials and Resources

Prereq

Storage and Collection of Recyclables

Prereq

Construction and Demolition Waste Management Planning

Credit

Building Life‐Cycle Impact Reduction Building Product Disclosure and Optimization ‐ Environmental Product Declarations Building Product Disclosure and Optimization ‐ Sourcing of Raw Materials Building Product Disclosure and Optimization ‐ Material Ingredients Construction and Demolition Waste Management

Indoor Environmental Quality Prereq Prereq Credit

Credit Credit

Fundamental Commissioning Required and Verification Minimum Energy Required Performance Building‐Level Energy Required Metering Fundamental Refrigerant Required Management Enhanced Commissioning 6 Optimize Energy Performance 18 Advanced Energy Metering 1 Demand Response 2 Renewable Energy Production 3 Enhanced Refrigerant 1 Management Green Power and Carbon 2 Offsets

Credit Credit Credit Credit

Minimum Indoor Air Quality Required Performance Environmental Tobacco Required Smoke Control Enhanced Indoor Air Quality 2 Strategies Low‐Emitting Materials 3 Construction Indoor Air 1 Quality Management Plan Indoor Air Quality 2 Assessment Thermal Comfort 1 Interior Lighting 2 Daylight 3 Quality Views 1 Acoustic Performance 1

0 0 0 0 0 2 1 2 0 1 0 14 0 0 2 3 1 2 0 2 3 1 0

165

Innovation

Credit

Innovation

Credit

LEED Accredited Professional

4 1

4 3

Regional Priority

Credit

Regional Priority: Specific Credit

Credit

Regional Priority: Specific Credit

Credit

Regional Priority: Specific Credit

Credit

Regional Priority: Specific Credit

LEED Gold Optimizer Wrap Up: Original Average LEED Gold Total Points:

After Final Optimization LEED Gold Points :

166

Original Average LEED Gold Total Cost

After Final Optimization LEED Gold Total Cost Total Cost / PAVERAGE 7.505 1.4

90.0%

5.0%

100.0%

1.2

85.7%

1.0

71.4%

0.8

57.1%

0.6

42.9%

0.4

28.6%

0.2

14.3%

0.0

0.0%

Minimum Maximum Mean Std Dev Values

$7,197,080.65 $9,042,584.13 $8,062,304.32 $343,741.88 100

9.20

9.00

8.80

8.60

8.40

8.20

8.00

7.80

7.60

7.40

7.20

Total Cost / PAVERAGE

7.00

Values x 10^-6

8.546

5.0%

Values in Millions ($)

Final Decision: Based on all simulation I did in previous pages and section here is my result: 1.The final RISK optimization is trustable since all calibration is correct. 2. The final result do make the it better in Cost part, the possibility is less cost in after optimization one is even higher than the original one.(Original 16million, 71.4% After, 8.34million, 72.3%) 3.In total point part, the original one still worst than optimize one its total score is smaller, and its possibility is lesser than optimize one.( Original 68 points, 90%, After 70 points, 100%) 4. The final optimization chose only pursue energy optimization points for 2 points and total energy and atmosphere for 6 points. 5. The main suggestion for optimizer is investigate more on Location and Transportation since the cost is not very and the points scale is very big, Invest more can easily get payback very fast.

167

Final Result- Pursue Energy Improvement ?

The whole thing is a lot of works. Here is the wrap it up section. I will sum up my suggestion and how design team should focus on in the future. 1.Not pursue more than 2 points on advance energy optimization points, since the other sectionâ&#x20AC;&#x2122;s is more efficient to help the project get to LEED Gold on v4

2.If only look at the energy optimization improvement design team should pursue 6 points because after that the improvement cost going to pass the half of the cost of average high rise multi family cost in Philippines.

3.For every building improvement project get extra LEED energy points, but every additional point cost relatively more. This equation can also help the project realize which points is going to have a positive payback. In this case it is going to be 5 points. After 5 points, the energy part cost will more expensive than other section total cost.

4.This logic and optimize function can not only be used in this project it also can be used in different project to discuss the investment in LEED Gold cost and its trade off.

For project itself, here are some points for future design strategies: 1.Solar gain is the main reason that causing the project high cooling load. During design stage should consider more on choosing the right glazing.

2.The way to chose the right glazing for this project is using low visible transmittance glazing and low U value.

3.The solar gain going to be very high for South side and East side of the building, design should rearrange its floor plan on these two side to make sure the indoor over glare hour do not be a big impact on living area.

5.In current stage, I will not suggest pursuing nature ventilation. Since the humidity is a very big trade off for the project. The other part may need to be focusing on is the Glazing ratio or Shading percentage in each side. Glazing ration and Shading percentage really do make a very big difference based on my detail simulation. Wrap up: I do learn a lot during these cap stone practice. The things is LEED Gold is not actually a strict energy performance rating method. If project really wants make the real building be a net zero energy building. Please focusing only on how to lower the final energy load but not use any rating method on the building. Another things for LEEDâ&#x20AC;&#x2122;s blind zone is that the performance is based on improvement. Sometimes this criteria may be too easy to reach. Although the project got the points, but it does not actually an well perform energy performance building. .

168

Reference: •

Impact of the Implementation of the 2000/2001 IECC on Residential Energy Use in Texas: Preliminary Verification of Residential Energy Savings - J. C. BaltazarJeff S. HaberlJeff S. HaberlC. CulpC. CulpBahman YazdaniBahman Yazdani

•

Energy Savings Analysis: ANSI/ASHRAE/IES Standard 90.1-2016 – DOE

•

The Cost of LEED v4 - BuildingGreen, Inc.

•

National Cost-effectiveness of ANSI/ASHRAE/IES Standard 90.1-2013 - R Hart SA Loper EE Richman RA Athalye MI Rosenberg MA Halverson Y Xie

•

Developing Performance Cost Index Targets for ASHRAE Standard 90.1 Appendix G – Performance Rating Method - M Rosenberg R Hart

•

Technical Support Document: 50% Energy Savings for Small Office Buildings - Brian A. ThorntonWeimin WangWeimin WangYunzhi HuangBing LiuBing Liu

•

Credit Optimization Algorithm for Calculating LEED Costs - Jae-Yong Park 1, Sul-Geon Choi 2 ID , Da-Kyung Kim 3, Min-Chul Jeong 4 and Jung-Sik Kong

•

LEED Credit Review System and Optimization Model for Pursuing LEED Certification - Jin Ouk Choi 1,*, Ankit Bhatla 2, Christopher M. Stoppel 2 and Jennifer S. Shane

•

A STUDY ON THE USE OF DOUBLE SKIN FAÇADE SYSTEMS IN THE PHILIPPINES BASED ON ITS PROPERTIES, NATURE AND GENERAL USE - April Mae Dalangin