executive summary - pam northern...

Malaysian Building Energy Efficiency Rating System (MEERB) – Part 2Proposed Building EnergyIndex (After Industry Dialogue)

CK Tang&Nic Chin

Foreword This document is produced as part of Component 4, Building Sector Energy Efficiency Program (BSEEP) by CK Tang ([email protected]) and Nic Chin ([email protected]) for JKR and UNDP.

The views expressed in this document, which has been produced without formal editing, are those of the authors and do not necessarily reflect the views of neither JKR nor UNDP. Comments and opinions from readers are encouraged and please email it to either [email protected] or [email protected] or comment at our Facebook page: www.facebook.com/bseepc4

CK Tang August3, 2012

Acknowledgements

The development of this document is much inspired by the Australian NABERS (National Australian Built Environment Rating System). The NABERS is well documented and is used as a reference guide during the development of the Malaysian building Energy Efficiency Rating System (MEERS).

In addition, a dialogue session was conducted in 6th September 2012 withMalaysian building industry experts. These experts have contributed important and valuable feedback to the development of MEERS. The followingswere the attendees of dialogues session:

http://www.facebook.com/bseepc4

mailto:[email protected]




Table of Contents1. Executive Summary.......................................................................................................................5

2. Introduction...................................................................................................................................8

3. Default Operating Hours in a Year.................................................................................................9

4. Energy Consumption of Data Center (Server Room)......................................................................9

5. Car Park Energy Consumption.....................................................................................................11

6. BEI Rated Area.............................................................................................................................11

7. Calibration for Occupant Density.................................................................................................14

7.1 Air-Conditioning Energy.............................................................................................................15

7.1.1 Air-Conditioning Energy for Sensible & Latent Heat due to Additional People...................15

7.1.2. Air-Conditioning Energy for Sensible & Latent Heat due to Additional Fresh Air for Additional People........................................................................................................................16

7.1.3 Air-Conditioning Energy for Sensible Heat from Additional Workstation due to Additional People..........................................................................................................................................17

7.1.4 Air-Conditioning Energy for Sensible Heat from Fan (AHU) due to the Additional Heat Load (applicable in VAV system)..........................................................................................................20

7.1.5 Air-Conditioning Energy due to System Coefficient of Performance of Chiller, pumps and cooling towers.............................................................................................................................21

7.2 Direct Energy Consumption.......................................................................................................21

7.2.1 Small Power Energy for additional workstation..................................................................21

7.2.2 Fan (AHU) Energy (applicable for VAV system only) due to Additional Sensible Heat........23

7.3 Simplified Formula for Calibration of BEI based on Occupant Density......................................24

7.4 Default System Coefficient of Performance (SCOP)...................................................................26

7.5 Industry Dialog Feedback...........................................................................................................27

8. Building Operating Hours & Normalization of Rated Hours.........................................................28

8.1 Simulation Results...............................................................................................................29

8.1.1 Low Energy Building.....................................................................................................29

8.1.2 Mid Energy Building.....................................................................................................30

8.1.3 High Energy Scenario...................................................................................................31

8.2 Detailed Analysis..................................................................................................................32

8.2.1 Mid Energy Building 35% Base Load............................................................................32

8.2.2 Mid Energy Building Scenario with 10% Base Load......................................................38

8.2.3 Mid Energy Building Scenario with 50% Base Load......................................................39

8.2.4 Low Energy Building Scenario with 10% Base Load......................................................39



8.2.7 High Energy Building Scenario with 10% Base Load.....................................................41



8.3 BEI Boundary Condition due to Building Rated Hours.........................................................42

8.3.1 Annual Operating Hours Boundaries............................................................................42

8.3.2 Correction Factors........................................................................................................44

8.4 Summary..............................................................................................................................48

8.5 Industry Dialog Feedback.....................................................................................................48

9. Appendix......................................................................................................................................49

Details of Energy Simulation Model for Section 5: BEI Rated Area..................................................49

Details of Energy Simulation Model for Section 7: Building Operating Hours & Normalization......52

1. Executive SummaryAn office building energy index (BEI), was requested to be developed for the Malaysian buildings under the BSEEP project. This BEI computation methodology has to be recognized as much as possible to be transparent, reasonably fair andaccurate to be used as a comparison tool of energy efficiency between buildings in Malaysia. One of the conclusion reached up the completion of this report is that it is not possible to ensure a true apple to apple energy consumption comparison between different buildings because there are too just many variables in each building that will impact the energy performance of a building. It is impractical to create a calibration for all possible building scenarios. However, it was found through this work that it may be beneficial to create a calibration curve for a couple of major issues such as impact on occupancy density and hours of building operation.

The key objective of a BEI is to function as a tool for the industry to enable a fair and equitable comparison of energy consumption between buildings of different sizes and occupancy profiles. The BEI should be a benchmarking tool that industry can understand and use easily and yet is confident that it isproviding a reasonably true and accurate reflection of the energy efficiency of the building measured. In short, the defined BEI should provide enough clarity to avoid confusion in the industry about the actual efficiency of a building.

Five (5) main issues were raised, identified and addressed in this development of the BEI definition for Malaysia.

1. Treatment of Data Center (Server Room) in Building,2. Treatment of car park energy consumption and car park area.3. Quality of reported BEI based on Gross Floor Area (GFA), Air Conditioned Area (ACA) andNet

Lettable Floor (NLA),4. Calibration of BEI for buildings with different occupant density and5. Calibration of BEI for different operating hours of the building.

First, data center (server room) is proposed to be included in the BEI computation because server is an essential part in the support of an office building today. In addition, many small businesses today have a data center (server) on their own even though a room is not allocated for it. It is clear that data center (server) has become a part of an office tenant’s core business and will be difficult to exclude it from the BEI computation for small offices. In addition, there exist many technologies to reduce energy consumption in data center and including it in the BEI will further encourage such practices. However, exclusion of data center energy consumption is proposed to be allowed if the data center (server room) does not entirely serve the building occupants.

Second, it was decided during the industry dialog session that car park energy consumption should be included into the BEI computation because this will spur better efficiency in car park lighting and ventilation energy consumption. However, the car park area should not be used for the computation of BEI due to the reason that it will skew the BEI output significantly if used, while the energy consumption of the car park will not skew the BEI number due to the reason that the energy consumption in car park is insignificant when compared to the rest of the building.

Third, energy simulation studies wereconducted to assess the quality of reported BEI based on Gross Floor Area (GFA),Air-Conditioned Floor Area (ACA) andNet Lettable Floor Area (NLA) area. It was found that computing the BEI using NLA as the “Rated Area” provides the most consistent and accurate comparison between buildings. The BEI computed using GFA is lower for a building with larger common area although the building total energy consumption has increased (i.e. building energy increases but BEI (using GFA) reduces) and the BEI computed using ACA is higher for building employing natural ventilation strategies for common area (i.e. building total energy reduces but BEI (using ACA) increases). However during the industry dialog, it was pointed out that the definition for NLA is not consistently practiced throughout the industry. After discussing this matter at length during the industry dialog, it was agreed by general consensus that the GFA definition used by DBKL (DewanBandaraya Kuala Lumpur, i.e. the Municipal Council of Kuala Lumpur) offers the most consistent definition of GFA that is most suited to the proposed BEI computation need (i.e. it excludes car park areas). Although the study showed that using GFA to compute BEI may have an error up to 17% for a low small power building scenario (showing a lower BEI than using other floor area method), it is still deem the most appropriate floor area to be used by the stakeholders during the consultation process.

Fourth, a methodology to calibrate building with low occupant density was proposed. This calibration method addresses the following issues to calibrate buildings with low occupancy density:

1. Air-Conditioning Energya. Sensible Heat due toAdditional Peopleb. Latent Heat due toAdditional Peoplec. Sensible Heat due to Additional Fresh Air for Additional Peopled. Latent Heat due to Additional Fresh Air for Additional Peoplee. Sensible Heat from Additional Workstation due to Additional Peoplef. Sensible Heat from Fan (AHU)due to the Additional Heat Load (applicable in VAV

system)g. System Coefficient of Performance of Chiller, pumps and cooling towers. h. Air-Conditioning Hours of 2700 hours is used. i. An assumption of infiltration rate of 0.5 ach of outdoor air during night time would

remove sensible heat produced by workstation during night time. 2. Small Power Energy

a. An assumption is made thateach additional person will add to 1 additional workstation.

b. A load of 125.28 watts per workstation is made based on the Ashrae Fundamental (2009) estimate of Medium Load Density of Small Power in offices1.

3. Fan (AHU) Energy (applicable for VAV system)a. In a VAV system, more sensible heat will increase fan energy. b. Additional Sensible Heat are accounted from

i. Peopleii. Small Power (Workstation)

iii. Fan Power (AHU)

1 2009 Ashrae Handbook Fundamentals SI Edition, Load and Energy Calculations, Nonresidential Cooling and Heating Load Calculations, F18.13, Table 11, Recommended Load Factors for Various Types of Offices.

However, during the industry dialog, it was decided by general consensus that such calibration method based on occupancy density should not be introduced at this stage. It was proposed that the calibration method based on occupancy density developed by the BSEEP should be published as atheoretical paper for further research and development by interested parties. It was proposed that when this calibration method is further substantiated by further supporting research papers, it can then be incorporated into use.

The fifth and final issue that was raised during the industry dialogwas the impact on BEI based on the operating hours of abuilding. Office buildings that operate at longer hours will have higher energy consumption than a building operating at shorter hours. The existing calibration of BEI being practiced by the industry is based on the assumption of a linear relationship of BEI and operating hours. There has been no known previous study to verify the margin of error of this calibration method used for a climate such as Malaysia. A request was made during the industry dialog session to conduct a study on the impact of building operating hours on BEI.

The study on the impact of the building operating hours on BEI was made andis documented in this report. The result showed that the building operating hours has a significant impact on the building BEI although all the equipment efficiencies remains the same. The longer the building operates; the current BEI computation method (linear calibration) will yield a significantly lower BEI. Further analysis also showed that the calibration of BEI due to building operating hours is highly dependent on the building “base” or “phantom” load. Due to the reason that the building “base” or “phantom” load is not easily available from the utility bill, it would not be practical to propose a calibration method for it at this point of time. It wasproposed to limit the linear calibration of BEI between the operating hours of 2,000 to 3,200 hours/year. The proposed limit will have a potential error up to 12% between the proposed extreme limit of building operating hours of 2,000 and 3,200 hours/year. It is not a perfect solution; however, it does help to keep the BEI formula simple and easy for the building industry to use.

2. IntroductionJKR (Malaysia Public Works Department) has practiced computing BEI based on air conditioned area for the past 5 years or more. In addition, existing reports of BEI computationprovided by external consultant to JKR, the BEI was computed inclusive of energy consumption of data center (server room).2Although not specifically specified, the BEI computation in JKR has consistently excluded car park energy consumption.

Meanwhile, the Malaysian Green Building Index (GBI) has a different definition forthe BEI. The GBI’s BEI was based on gross floor area (GFA). In addition, the GBI specifically excluded data center (server room) and car park energy consumption from its BEI computation.

The consistent parts between the two approaches described above are the followings:1. Almost all energy consumption of the building is taken into account. This is inclusive of

lighting and small-power energy used in non-conditioned spaces such as lighting for façade, toilet, janitor room, air handling-unit room, and etc.

2. Both JKR and GBI approach have excluded the car park lighting and ventilation from the BEI computation because it is generally recognized that car park energy consumption is highly dependenton how and where the car park is constructed. I.e. basement car park requires both lighting and ventilation, multi-story above ground car park requires lighting only and car park in open spaces neither requires lighting (daytime) nor ventilation.

The inconsistencies between the two approaches are the followings: Energy Consumption of Data Center (Server Room) is included in BEI computation by JKR but

specifically excluded by GBI. The Rated Area used for computation of BEI. JKR uses Air-Conditioned Area while the GBI

uses Gross Floor Area.

In addition,the influence of occupant densityon BEI computation was often raised by the building industry and therefore need to be addressed as well.

2 Low Energy Office Building by Danida (2002-2005) & Energy Audit Report of JKR, Block F by CofrethSdnBhd (2006)

3. Default Operating Hours in a YearThe default operating hours of office building is required be specified in order for office building with different operating hours to be compared against one another. The methodology to derive the default working hours in a year is described below.

Weekends and public holidays should be accounted to compute the default working hours in a year to be used by the BEI.

There are 52 weekends in 1 year. 52 weeks x 2 off day per week = 104 non-working days Typical Public Holidays in Malaysia

Descriptions of Public HolidaysNo of Days

1st January 1Prophet Birthday 1Thaipusam 1Federal Territory Day/Other States day 1Chinese New Year 2Labour Day 1Agong's Birthday 1HariRaya 2Merdeka 1Malaysia's Day 1Hari Raya Haji (Korban) 1Deepavali 1Awal Muharram 1Christmas 1Gross Total Public Holidays 16Assumed no of Public Holidays falling on Saturday per year. 2Net Total Public Holidays 14

Total Working Days in a Year: 365 – 104 (weekends) – 14 (public holidays) = 247 days a year.

Assumed average operating hours per working day in offices: 7am to 6pm = 11 hours/day.

Total Operating Hours in a year = 247 days x 11 hours/day = 2717 hours/year.

It is also possible that there may be more than 2 public holidays falling on a Saturday in a typical year. Therefore, it is proposed to round down the Total Operating Hours in a year to 2700 hours/year to simplify the BEI. The exact value of the default operating hours is not important because this is just a reference point where all buildings are compared against.

4. Energy Consumption of Data Center (Server Room)Data center or server room is proposed to be included in the BEI computation because server is an essential part in the support of an office building today. In addition, many small businesses today have a data center (server) on their own even though a room is not allocated for it. It is clear that

data center (server) has become a part of an office tenant’s core business and will be difficult to exclude it from the BEI computation for small offices.

In addition, there exist many technologies to reduce energy consumption in data center and including it in the BEI will further encourage such practices. However, exclusion of data center energy consumption is proposed to be allowed if the data center (server room) does not entirely serve the building occupants.

It is proposed that energy from Computer Servers is added to the BEI computation based on the following rules:

1. All Energy by Computer Server where: The total energy consumption of the server room is not sub-metered, or The server is used entirely by internal users of the rated building.

2. Partial Energy by Computer Server where: The server room has a mix of internal and external users, and The external used IT equipment and/or facility services are separately sub-metered. The floor area that may be excluded is determined by measuring the area covered

by the externally used IT equipment. The Assessor must obtain written documentation from the tenant that confirms that

the IT equipment in the excluded area is either used entirely for external users or as a disaster recovery site for another external data center.

3. Proportional Energy by Computer Server where: The server room has a mix of internal and external users, and The total energy consumption of the server room is sub-metered, and The external used IT equipment and/or facility services are not separately sub-

metered, and It is possible to determine the numbers of internal and external users of the IT

equipment. 4. Totally excluded, where:

The total energy consumption of the server room is sub-metered, and The server room is used entirely for external users, or as a disaster recovery site for

another external data center, or It is too difficult to determine the number of external users.

5. Car Park Energy ConsumptionThis issue was raised during the industry dialog session and a clear decision was made by everyone at the dialog session to include the energy consumption of car park (both lighting and ventilation), while excluding the car park area from the BEI computation.

The basis to include the energy consumption of car park is to encourage energy efficiency to be practiced in car park as well, especially on the lighting energy consumption and in the case of basement car park, mechanical ventilation energy consumption as well. It was pointed out that it is not reasonable to keep the car park energy consumption out of the BEI computation when the intention of the BEI is to promote energy efficiency.

The car park area was proposed to be excluded because the car park area can be a very significant number that will skew the BEI significantly. Meanwhile, the energy consumed by thecar park will be insignificant when it is compared to the rest of the building. Therefore, adding the car park energy consumed into the BEI will not skew it significantly, while at the same time it will help to encourage buildings to be efficient in the car park as well.

However, it was also pointed out during the dialog session that this decision made may not be consistent because the car park’s energy is included in the BEI computation but the car park’s area is not included and it may lead to confusion in the market place. The consensus obtained from the industry dialog session is that this will not be a problem for the industry as long as the rules are clearly specified.

6. BEI Rated AreaEnergy simulation studies were conducted to study the impact of BEI computation using Gross Floor Area (GFA), Air-Conditioned Area (ACA) and Net Lettable Area (NLA). These are terms are defined as follows:

Gross Floor Area (GFA)o All spaces in the building but the lift shaft. o It includes office spaces, lift lobbies/walkways, pantries, toilet, AHU rooms, utilities

rooms and etc. Air-Conditioned Area (ACA)

o Any spaces that is air-conditioned. o May or may not include lift lobbies/walkway, pantries and toilet depending on the

air-conditioning strategy employed. Net Lettable Area (NLA)

o Any spaces that is functional as an office space. o NLA excludes lift lobbies/walkway, pantries, toilet, AHU rooms, utilities rooms and

etc.

A Malaysian base case building of 17 floors was modeled with different floor efficiencies, air-conditioned area, equipment power in offices and lighting power in common area. The building

orientation and area of the Net Lettable Floor (offices) are maintained the same for all buildings simulated. The following cases were then simulated:

Case 1– Largercommon area such as toilet, lift lobby/walkway and pantry, reducing the floor efficiency from 78.8% to 74.8%, while increasing the Gross Floor Area (GFA). This may be applicable for buildings located in area where land cost is low or in more prestigious building where common area spaces are made larger to provide a “luxurious” feel to the building.

Case 2 –Base Case with the lift lobby/walkway naturally ventilated (NV), reducing building total energy consumption and reducing Air-Conditioned Area (ACA).

Case 3 –Case 1 with the lift lobby/walkway naturally ventilated (NV), reducing building total energy consumption and reducing Air-Conditioned Area (ACA) at lower floor efficiency (higher GFA).

Case 4 – Base Case with the Small Power in Office spaces reduced by 30%. Case 5 – Base Case with the Lighting Power in Common Area increased by 30%.

A summary of the energy simulation result is tabulated in the table below:

Descriptions Base

Case 1 - Larger Common Area

Case 2 – Base, NV* of Lift Lobby

Case 3 - Case 1, NV* of Lift Lobby

C4 - Base, Low Office Small Power

C5 - Base, High Lighting in common area

GFA (m2) 35,598 37,477 35,598 37,477 35,598 35,598Air-Conditioned Area (ACA) (m2) 32,640 33,917 29,750 29,750 32,640 32,640

NLA (m2) 28,050 28,050 28,050 28,050 28,050 28,050Floor Efficiency (%) 78.8% 74.8% 78.8% 74.8% 78.8% 78.8%

Total Building Energy Consumption (MWh/Year)

5,940.66 6,046.00 5,846.96 5,923.14 4,922.85 6,054.50

Total Building Energy Consumption (% Change)

0.0% 1.8% -1.6% -0.3% -17.1% 1.9%

BEI (based on GFA) (kWh/m2-year)

166.88 161.32 164.25 158.05 138.29 170.08

BEI (based on GFA) % Change 0.0% -3.3% -1.6% -5.3% -17.1% 1.9%

BEI (based on ACA) (kWh/m2-year)

182.01 178.26 196.54 199.10 150.82 185.49

BEI (based on ACA) % Change 0.0% -2.1% 8.0% 9.4% -17.1% 1.9%

BEI (based on NLA) (kWh/m2-year)

211.79 215.54 208.45 211.16 175.50 215.85

BEI (based on 0.0% 1.8% -1.6% -0.3% -17.1% 1.9%

NLA) % Change* NV = Naturally Ventilated.

Computing BEI using GFA as the “Rated Area” showed a significant different in change between the reported BEI and the building total energy consumption for Case 1 and 3. The cause of these differences is due to the larger common area for toilets, lift lobbies and pantries area (increasing the GFA) as compared to the base case. The reported BEI using the GFA as the “Rated Area” showed a reductionwhen the building total energy consumptionwasincreased due to the larger common area provided. The reason for this occurrence is because the common area uses a small amount of energy, while providing a larger area for the computation of BEI, therefore, reducing the reported BEI figure.

Computing BEI using ACA (air-conditioned area) as the “Rated Area” showed a significant different in change between the reported BEI and the building total energy consumption for Case 2 and 3, where the lift lobby is naturally ventilated. Due to the reason that the lift lobbies were not air-conditioned, the “Rated Area” using ACA was reduced, increasing the reported BEI figure significantly when the building total energy consumption wasreduced. In addition, it was also shown that using the ACA method also produced differences in Case 1, where the total building energy consumption increased by 1.8% (due to the larger air-conditioned common area), while the reported BEI using ACA showed a reduction of 2.1%. In Case 1, the common area uses a small amount of energy, while providing a larger area for the computation of BEI, therefore, reducing the reported BEI figure.

Computing the BEI using NLA as the “Rated Area” showed the most consistent results for all the cases studied as compared to the building total energy consumption. It should also be noted that the BEI reported using NLA is approximately 25% to 35% higher than the BEI reported using GFA as the “Rated Area”. Fundamentally, the lower the floor efficiencies, thelarger the differencesbetween thereported BEI based on NLA as compared to the reported BEI based on GFA.

The disadvantages of all 3 methods to compute BEI is summarized below: GFA as the “Rated Area” promotes lower floor efficiencies to provide lower BEI rating. ACA as the “Rated Area” promotes air-conditioning in area that may be possible to be

naturally ventilated to provide lower BEI rating. NLA as the “Rated Area” reported the highest BEI (up to 35% higher) among all the methods

considered.

The advantages of all 3 methods to compute BEI is summarized below: GFA as the “Rated Area” is the easiest method to be practiced by the building industry as

this number is often quoted in many official documents. There is no clear advantage of using ACA as the “Rated Area”. NLA as the “Rated Area” provides the most consistent and accurate comparison between

buildings. In addition, it is also a fairly common to quote the NLA within the building industry.

Based on the result above, it was initially proposed that BEI should be computed using the NLA as the “Rated Area” because it yields the most consistent and accurate picture of the building total energy consumption for comparison between buildings and yet it is a fairly common number used by the building industry.

Unfortunately, during the industry dialog session, a clear definition of NLA was found to be impossible in Malaysia at this point of time. It was stated during the industry dialog session that the industry does not practice a standard formula to compute the NLA and it changes from project to project. It was pointed out that it will take significant effort and time to develop a clear definition of NLA in Malaysia and it may not be worth the effort by BSEEP project to undertake at this point of time. It was agreed by general consensus during the industry dialog session that the DBKL (Kuala Lumpur Municipal Council) definition of GFA is used instead because it suited our need perfectly by providing a clear computation methodology of GFA computation while excluding the car parking area.

The potential inaccuracies of the computed BEI up to 5% of the actual building energy consumption was deem an acceptable trade-off to have a clear and fixed definition of GFA as the BEI rated area as opposed to a unclear and potentially easy to manipulate NLA definition by the building industry.

7. Calibration for Occupant DensityThe calibration of the BEI for low occupant density building is proposed to provide confident to the building industry that all buildings are evaluated in a fair manner. However the energy contribution of added occupancy to the building has to be made carefully to ensure a level of fairness is provided via the calibration process.

It is proposed to calibrate the BEI of all building with occupancy density less than 10 m²/person to a building with an occupancy density of 10 m²/person. In short, people are added hypothetically into thebuilding to increase the occupant density to 10 m²/person. In addition, all possible energy increase due to the added occupants in the building has to be accounted for as well.

The additional energy consumptioncaused by an increased in occupant density is related to the following items:

1. Air-Conditioning Energy for Sensible& Latent Heat due to Additional People2. Air-Conditioning Energy for Sensible & Latent Heat due to Additional Fresh Air for Additional

People3. Air-Conditioning Energy for Sensible Heat from Additional Workstation due to Additional

People4. Air-Conditioning Energy for Sensible Heat from Fan (AHU) due to the Additional Heat Load

(applicable in VAV system)5. Air-Conditioning Energy due to System Coefficient of Performance of Chiller, pumps and

cooling towers. 6. Small Power Energy foradditional workstation. 7. Fan (AHU) Energy (applicable for VAV system only) due to Additional Sensible Heat from

a. Peopleb. Fresh Airc. Small Power (Workstation)d. Fan Power (AHU)

The advantage of the climate in Malaysia is that it is fairly consistent daily for the entire year. 3 It is therefore, possible to develop a scenario of a typical average working day and apply it for the entire year without compromising the accuracy of the result. Based on this fundamental approach, the description of the methodology to compute the energy gain for each item is provided below:

7.1 Air-Conditioning Energy

7.1.1 Air-Conditioning Energy for Sensible & Latent Heat due to Additional PeopleThe sensible and latent heat load per person is taken from the 2009 ASHRAE Handbook – Fundamentals (SI) for a “Moderately active office work”. 4

Sensible Heat from People: 75 W per person Latent Heat from People: 55 W per person

Additional persons to be added into a low occupancy building, to calibrate it to 14 m²/person, can be computed using this equation below:

P=Rated Area x ( 110

− 1Dm

)

Or,

P=Rated Area x (0.1− 1Dm

)

Where,

3 CK Tang, Chapter 2 – Malaysia’s Weather Data, Building Energy Efficiency Technical Guideline for Passive Design, 2012. 4 2009 ASHRAE Handbook – Fundamentals (SI), 18.4, Table 1, Representative Rates at Which Heat and Moisture Are Given Off by Human Beings in Different States of Activity.

Rated Area = Total Rated Area (m²)Dm = Measured Occupant Density (m²/person) in the Rated Area

The default working hours of 2700 hours/year is used to compute the total people heat load contribution to the building in a year. The air-conditioning energy for the year due to people is then computed by dividing the heat load with the System Coefficient of Performance (SCOP) of the chill water system.

7.1.2. Air-Conditioning Energy for Sensible & Latent Heat due to Additional Fresh Air for Additional PeopleThe additional fresh air requirement per person is taken from the ANSI/ASHRAE Standard 62.1-2007, Table 6-1.5

Office Space: 2.5 l/s per person.

The additional fresh air requirement in Ashrea 62.1 for “Area Outdoor Air Rate” is not taken into considerationbecause is assumed to be provided for by the base building BEI measurement (people are added into the building for the calibration, not area). Therefore, only the “People Outdoor Air Rate” is used to account for the additional fresh air requirement.

The sensible heat due to additional fresh air requirement is computed using the equation below with the assumption that the building indoor air temperature is maintained at 23°C, while the outdoor air temperature is taken to be the average air temperature of Malaysia’s Test Reference Year weather data for the hours of 9am to 5pm, of 29.9°C.6

Qs=Cp ρq∆T3600

Where,Qs = sensible heat flow (kW)Cp = specific heat of air (kJ/kg K) (1.0)ρ = air density at standard conditions (kg/m3) (1.2)q = air flow (m3/hr) (2.5 l/s per person x no of added persons)

5 ANSI/ASHRAE Standard 62.1-2007, Table 6-1, Minimum Ventilation Rates in Breathing Zone. 6CK Tang, 2012, Chapter 2 – Malaysia’s Weather Data, Building Energy Efficiency Technical Guideline for Passive Design, p9-10.

Δt = temperature (°C) (29.9°C – 23°C = 6.9°C)

The latent heat due to additional fresh air requirement is computed using the equation below with the assumption that the building indoor air relative humidity is maintained at 60%, (at 23°C, providing a moisture content of 10.6 g/kg), while the outdoor air moisture content is taken to be the average of Malaysia’s Test Reference Year weather data for the hours of 9am to 5pm, to be 18.1 g/kg.7

Ql=hwe ρq ∆ x3600

Where,Ql = latent heat flow (kW)hwe = 2465.56 - latent heat of vaporization of water (kJ/kg)ρ = 1.2- air density at standard conditions (kg/m3)q = air flow (m3/hr)Δx = humidity ratio difference (kg water/kg dry air)

The default working hours of 2700 hours/year is then used to compute the total heat load contribution of additional fresh air to the building in a year. The air-conditioning energy for the year due to this additional fresh air intake is then computed by dividing the heat load with the System Coefficient of Performance (SCOP) of the chill water system.

It should be noted that,it can also be argued that the base (measured) building fresh air ventilation rate is already more than adequate to cater for the additional people to be added to the building to calibrate it to 10 m²/person, therefore, it is not necessary to add this load into the building. However,this argument will not hold true for building installed with CO 2 controlled fresh air damper, where fresh air provided is controlled by the measured CO2in the building. In buildings where the fresh air intake and/or infiltration rate is not controlled, the addition of building occupant will most likely not increase fresh air intake.

A decision is made to add the fresh air contribution to the BEI calibration because buildings with measured BEI would likely have taken measures to reduce energy consumption in the building itself and is assumed to have reduced the fresh air intake to the minimum while maintaining air quality. Therefore, an added occupancy will require more fresh air to maintain air quality in the building and has to be accounted in the calibration of the BEI for a low occupant density building.

7.1.3 Air-Conditioning Energy for Sensible Heat from Additional Workstation due to Additional PeopleA key assumption is made that for each additional person added to the building, it will increase one (1)additional workstation in the building. Therefore, there will be additional heat gain added from the use ofworkstation (small power in building) due to the increased occupant density.

A workstation load was taken from 2009 ASHRAE Handbook – Fundamentals (SI) for a “Medium Load Density of Office” in Table 11 to be 10.8 W/m².8This figure was computed from an assumption of

7CK Tang, 2012, Chapter 2 – Malaysia’s Weather Data, Building Energy Efficiency Technical Guideline for Passive Design, p12-14.

11.6 m²/workstation. Combining these two numbers will yield an average load per workstation to be 125.28 W/workstation.

The working hour sensible heat gain from workstation is computed using the default working hours of 2700 hours/year and the number of occupant to be added to the building.

The non-working hour (base load) sensible heat gain from workstation is then computed taking into account of the followings:

A. A possibility that different building may have different base load for small power.B. An infiltration rate of 0.5 air-changes per hour (ach) during off-peak hours taking out the

heat generated during night time.

A base load, BL (%) is defined as,

BL= Average Small Power Load duringUnoccu pied Hours (kW )Average Daily Peak Small Power Load(kW )

A default base load (BL) of 22% is proposed for building where the base building small power or base load is not measured. The 22% base load is computed from 2009 Ashrae Fundamental Handbook, F18, Table 12, Cooling Load Estimates for Various Office Load Densities for a Medium Load Density Case with the following assumptions:

Computer and monitor have a standby power loss up to 10% during unoccupied hours. Shared printers and fax machine are not switched off during unoccupied hours.

8 2009 Ashrae Handbook Fundamentals SI Edition, Load and Energy Calculations, Nonresidential Cooling and Heating Load Calculations, F18.13, Table 11, Recommended Load Factors for Various Types of Offices.

The base load at night will cause higher heat gain in the morning when the air-conditioning system is switched on. However, this heat gain during night time will also be reduced due to conduction out of the building fabric and infiltration of outside (cooler) air into the building. The heat lost due to conduction part is quite small due to the small temperature differences between indoor and outdoor temperature during night time and is disregarded. However, the infiltration of outdoor air into the building during night time will take a significant heat out of the building and has to be addressed.

In 2003 – 2005, through the Danida project, it was measuredthat the Low Energy Office (LEO) building has a night time infiltration rate of 0.5 ach by the drop of measured CO 2density in the building.9This night time infiltration rate is used to compute the cooling provided by the infiltration of outdoor air into the building during night time.

The average outdoor air temperature from 7pm to 7am of 24.8°C from the Malaysia’s Test Reference Year weather data is used as the basis to compute the sensible heat removed from the building due to infiltration during night time.10

An assumption is made for the average indoor air temperature from the hours of 7am to 7pm, allowing the computation of heat removal due to infiltration of outdoor air during night time. The balance of the night time heat gain by the building is computed by the total heat generated by this workstation during unoccupied hours minus the heat removed due to infiltration during unoccupied hours. This balance of the night heat gain is then used to compute the indoor air temperature using the heat capacity of air. Iteration is made until the assumed indoor air temperature is matched with the computed indoor air temperature.

The balance of the night heat gain is then added to the working hour heat gain to provide the total heat load due to workstation for the year. The air-conditioning energy due to this additional workstation is then computed by dividing the heat load with the System Coefficient of Performance (SCOP) of the chill water system.

9 2003-2005, Danida project for LEO building. 10CK Tang, 2012, Chapter 2 – Malaysia’s Weather Data, Building Energy Efficiency Technical Guideline for Passive Design, p9-10.

7.1.4 Air-Conditioning Energy for Sensible Heat from Fan (AHU) due to the Additional Heat Load (applicable in VAV system)For a Constant Air Volume (CAV) system, the fan speed is not varied and is assumed to be designed for the peak load capable of supplying adequate cooling to a building with an occupancy density of 10 m²/person. However, for a Variable Air Volume (VAV) system, the fan speed is dependent on the sensible heat in the building. The additional sensible heat from people, workstation and fan itself has to be accounted to compute the additional heat generated by the fan.

The sensible heat from people and workstation is available from items 1 and 3 above. An assumption of additional sensible heat from the fan is made at the beginning and an iteration process is made to ensure that the assumed heat gain from the fan is matched with the computed power requirement of the fan at the end (for an energy balance to be made).

The fan power can be calculated using the fan power limit from the MS1525 (2007), of 0.45 watt/cmh. A typical VAV fan power curve from the measure LEO building in 2004was used to provide an approximation of the average fan power of a VAV system for a typical day is show below.

Measured typical VAV AHU performance in LEO in 2004.

The measured LEO building in 2004, showed that a typical VAV system operates 3/4 hour at 100%, 1 hour at 60%, 1 hour at 45%, 8 hours at 40%. The weighted average fan power of a day is computed from these numbers to be 47% of the peak load. With the fan power limit from the MS1525 (2007), of 0.45 Watt/cmh, 47% will yield 0.21 Watt/cmh on average for a VAV system.

The additional air-flow rate was then computed from the total sensible heat and the temperature difference between the supply air and return air temperature. An assumption is made that supply air temperature (off-coil) is 12°C and the return air temperature is 23°C, therefore, allowing the air-flow rate to be computed and the fan energy estimated. An iteration process is carried out until the fan sensible heat is equal to the fan power used (energy balance is achieved).

The default working hours of 2700 hours/year is then used to compute the total heat load contribution of a VAV fan to the building in a year. The air-conditioning energy due to this additional air flow rate is then computed by dividing the total fan heat load with the System Coefficient of Performance (SCOP) of the chill water system.

7.1.5 Air-Conditioning Energy due to System Coefficient of Performance of Chiller, pumps and cooling towers.The System Coefficient of Performance (SCOP) is defined herewith as:

SCOP= kWh (coolingdelivered )kWhe (chiller )+kWhe (water pumps )+kWhe(cooling tower)

Where, kWh (cooling delivered) = cooling load delivered to the building (kWh)kWhe(chiller) = electricity of the chiller (kWh)kWhe(water pumps) = electricity of chilled water pump and condenser water pump (kWh)kWhe(cooling tower) = electricity of cooling toweror condenser fan if air cooled (kWh)

At minimum ofone (1) full week measurement of energy in kWh by the chiller, pumps and fans is proposed to be used because it will provide the “average” System Coefficient of Performance that can be used to estimate the Total Air-Conditioning Energy for the building with the equation below.

Total Additional Air Conditioning Energy=¿ tal Additional Heat LoadSCOP

Where,Total Additional Air Conditioning Energy = kWh/yearTotal Additional Heat Load = Total sensible & latent heat from people, fresh air, workstation and fan (kWh/year)

7.2 Direct Energy Consumption

7.2.1 Small Power Energy foradditional workstation.A key assumption is made that for each additional person added to the building, it will increase one (1) additional workstation in the building. Therefore, there will be additional energy added from the use ofworkstation (small power in building) due to the increased occupant density for the calibrated building.

The workstation power consumption is taken from 2009 ASHRAE Handbook – Fundamentals (SI) for a “Medium Load Density of Office” in Table 11.

Ashrae recommendation for Medium Load Density of an Office is 10.8 W/m² with an assumption of 11.6 m²/workstation. This will provide a load per workstation to be 125.28 W/workstation.

The working hour energy consumption from workstation is computed using the default working hours of 2700 hours/year and the occupant to be added to the building.

The non-working hour (base load) energy consumption from workstation is then computed taking the base load multiply by 6060 hours/year. Where base load (BL) is defined as:

BL= Average Small Power Load duringUnoccupied Hours(kW )Average Daily Peak Small Power Load (kW )

A default base load (BL) of 22% is proposed for building where the base building small power or base load is not measured. The 22% base load is computed from 2009 Ashrae Fundamental Handbook, F18, Table 12, Cooling Load Estimates for Various Office Load Densities for a Medium Load Density Case with the following assumptions:

Computer and monitor have a standby power loss up to 10%. Shared printers and fax machine are not switched off during unoccupied hours.

7.2.2 Fan (AHU) Energy (applicable for VAV system only) due to Additional Sensible HeatFor a Constant Air Volume (CAV) system, the fan speed is not varied and is assumed to be designed for the peak load capable of supply adequate cooling to a building with an occupancy density of 10 m²/person. However, for a Variable Air Volume (VAV) system, the fan speed is dependent on the sensible heat in the building. The additional sensible heat from people, workstation and fan itself has to be accounted to compute the additional heat generated by the fan.

The sensible heat from people and workstation is available from items 1 and 3 above. An assumption of additional sensible heat from the fan is made at the beginning and an iteration process is made to ensure that the assumed heat gain from the fan is matched with the computed power requirement of the fan at the end (for an energy balance to be made).

The fan power can be calculated using the fan power limit from the MS1525 (2007), of 0.45 watt/cmh. A typical VAV Fan power curve from the measure LEO building in 2004 was used to provide an approximation of the average fan power of a VAV system for a typical day is show below.

Measured typical VAV AHU performance in LEO in 2004.

The measured LEO building in 2004, showed that a typical VAV system operates 3/4 hour at 100%, 1 hour at 60%, 1 hour at 45%, 8 hours at 40%. The weighted average fan power of a day is computed from these numbers to be 47% of the peak load. With the fan power limit from the MS1525 (2007), of 0.45 Watt/cmh, 47% will yield 0.21 Watt/cmh on average for a VAV system.

The additional air-flow rate was computed from the total sensible heat and the temperature difference between the supply air and return air temperature. An assumption is made that supply air temperature (off-coil) is 12°C and the return air temperature is 23°C, therefore, allowing the air-flow rate to be computed and the fan energy estimated. An iteration process is carried out until the fan sensible heat is equal to the fan power used (energy balance is achieved).

The default working hours of 2700 hours/year is then used to compute the total energy contribution of a VAV fan to the building in a year due to higher occupant density.

7.3 Simplified Formula for Calibration of BEI based on Occupant DensityBased on the assumptions and computation methods described above, the calibration for BEI of low density building was made and a simplified formula is provided below.

Where occupancy density of a building is low, i.e. more than 10 m²/person, the BEImcan be calibrated to a building with occupant density of 10 m²/person. The BEIc (calibrated) is defined as:

BEI c=BEI mx Rated Area+AC p+SPp+FPvav

Rated Area

Where,BEIc = Calibrated Building Energy Index (kWh/m²-year)BEIm= Measured Building Energy Index (kWh/m²-year)ACp = Additional cooling energy to the building (kWh/year)SPp = Additional Small Power Energy (kWh/year)FPvav = Additional Fan Energy (kWh/year for VAV system only)Rated Area = Total Rated Area (m²)

For a VAV system (where Base Load is not measured),

BEIc=BEI mx Rated Area+( 963

SCOP )P+505.3 P+34.6 P

Rated Area

Where,BEIm = Measured Building Energy Index (kWh/m²-year)Rated Area = Total Rated Area (m²)SCOP = System Coefficient of Performance (unit-less) P = No of People Added to calibrate building to 10 m²/person occupant density.

The number of people to be added (P), to calibrate building to 10 m²/person is defined below:

P=Rated Area x ( 110

− 1Dm

)

Where,Rated Area = Total Rated Area (m²)Dm = Measured Occupant Density (m²/person) in the Rated Area

Where Base Load (BL) is measured,

BEIc=(BEI ¿¿mx Rated Area)+(AC p x P)+(SE¿¿ p x P)+ (FE¿¿ p x P)Rated Area

¿¿¿

Where,

SEp=338.3+759.2 BL

AC p=557.4+SPc+FPc

SCOP

SPc=348.4+86.1BL

FPc=FE p=12.30+0.06 SPc

Where,BEIm = Measured Building Energy Index (kWh/m²-year)Rated Area = Total Rated Area (m²)SCOP = System Coefficient of Performance (unit-less) P = No of People Added to calibrate building to 14 m²/person occupant density. FEp = Fan Energy (kWh/year-person)SEp = Small Power Energy (kWh/year-person)FPc = Fan Power Cooling Load (kWh/year-person)SPc = Small Power Cooling Load (kWh/year-person)ACp = Air-Conditioning Energy (kWh/year-person)BL= Small Power Base Load (percentage)

BL= Average Small Power Load duringUnoccupied Hours(kW )Average Daily Peak Small Power Load (kW )

A minimum measurement of 1 full week of cooling load delivered and electricity consumption of chillers, chill water & condenser water pumps and cooling towers is required to derive a meaningful SCOP.

For a CAV system, (where Base Load is not measured),

BEIc=BEI mx Rated Area+( 925

SCOP)P+505.3 P

Rated Ar ea

Where,BEIm = kWh/m²-yearRated Area = m²SCOP = System Coefficient of PerformanceP = No of People Added to calibrate building to 14 m²/person occupant density.

Where Base Load (BL) is measured,

BEIc=BEI mx Rated Area+AC p x P+SEp x P

Rated Area

SEp=338.3+759.2 BL

AC p=557.4+SPcSCOP

SPc=348.4+86.1BL

Where,BEIm = Measured Building Energy Index (kWh/m²-year)Rated Area = Total Rated Area (m²)SCOP = System Coefficient of Performance (unit-less) P = No of People Added to calibrate building to 14 m²/person occupant density. SEp = Small Power Energy (kWh/year-person)SPc = Small Power Cooling Load (kWh/year-person)ACp = Air-Conditioning Energy (kWh/year-person)BL= Small Power Base Load (percentage)

7.4 Default System Coefficient of Performance (SCOP)For buildings where the system coefficient of performance (SCOP) is not measured, a default SCOP is provided for different types of chiller system used.

For air cooled split unit, the default SCOP is based on a reasonably efficient split units system available in the market today.

For chilled water system, the default SCOP was computed based on the minimum chiller COP of the MS1525 (2007) and the requirement of Ashrae 90.1 (2009), Appendix G for chilled water pump power, condenser water pump power and cooling tower fan power.

Ashrae 90.1 (2009) specified a chilled water pump power limit of 349 kW/1000 l/s at a chilled water supply temperature of 44°F and return 57°F, condenser water pump power limit of 310 kW/1000 l/s at condenser ΔT of 10°F and a cooling tower fan power limit of 0.0105 kWe/kW rejected heat.

For district cooling system, the SCOP was agreed at 3.8 during the industry dialogue session if data is not provided by the district cooling plant.

Equipment Size Minimum Chiller COP (MS1525)

Default System COP

Air Cooled Split Unit

(non-inverter)

<10 kWr - 3.0

Air Cooled Split Unit

(inverter)

<10 kWr - 3.8

Air cooled, with condenser

(no condenser pump)

< 105 kWr (30RT) 2.6 2.32

105 kWr and

< 530 kWr (150RT)

2.7 2.40

530 kWr and

< 1060 kWr (300RT)

2.8 2.49

1060 kWr (300RT) 2.9 2.57

Water cooled, positive displacement

(Reciprocating and Scroll)

All capacities 4.0 3.24

Water cooled, positive displacement (Rotary

Screw)

< 530 kWr (150RT) 4.0 3.24

530 kWr and

< 1060 kWr (300RT)

4.4 3.51

1060 kWr (300RT) 5.4 4.14

Water cooled, centrifugal < 1060 kWr (300RT) 5.2 4.02

1060 kWr (300RT) 5.7 4.32

District Cooling All Capacities - 3.5

7.5 Industry Dialog FeedbackAlthough the above proposed calibration method was well received by the participants in the industry dialog session, they were reluctant to implement this calibration method immediately. It was proposed during the industry dialog session to go ahead and publish the proposed calibration methodology and thenwaits for further supporting evident from other academicians or industry that the methodology proposed is indeed a fair method to calibrate buildings with different occupancy density.

8. Building Operating Hours & Normalization of Rated HoursThe proposed office BEI computation normalizes different operating hours of a building based on the equation below:

BEIo=Total Building EnergyConsumptionTotal Rated Areas x RatedHours

x 2700hours

Where, BEIo = Office Building Energy Index as measured [kWh/(m²-year)]Rated Hours = Default operating hours of the building.

It was requested during the BSEEP MEERB dialogue session, that a study on the operating hours of building on the impact of BEI computation should be carried out.

A quick initial study was made based on 2 extreme building operating scenarios of 8 hours a day, 5 days week (a total of 2080 hours/year) and 24 hours a day, 7 days a week (a total of 8760 hours/year). Although the building occupancy densities, mechanical and electrical equipment remain the same in these two scenarios, the results showed that normalized BEI computation to be significantly different. A differential of 55% was found.

This result states that if someone purchase a building with a reported BEI of 127 kWh/m²/year (based on the previous owner operating the building 24 hours, 7 days a week), and only operates the building 8 hours day and 5 days a week, he/she will get a BEI of 196 kWh/m²/year, with the same occupancy and small power density. In summary, the current version of BEI may misrepresent the actual situation due to differences in building operating hours.

Further investigation into the cause of the differences in the reported BEI due to different operating hours yields the following two (2) major factors:

1. Building Base Load. Base load in a building is defined as energy consumption in the building during non-operating hours of the building. Although the base load occurs during non-operating hours of the building, its energy consumption is added to the operating hours. Where the building operating hours is short, the base load has a larger influence because of the longer non-operating hours.

2. Longer air-conditioning hours dampen the peak cooling load of the building. This helps to reduce building energy consumption per operating hour basis. The longer air-conditioning operating hours kept the building structure cooler, when the air-conditioning system is switched on again after a break, the peak cooling load is lowered. In a building designed with variable speed system, the efficiency gained is significant due to the lower peak cooling load.

This results point to a need to establish a kind of boundary conditions (or correction factor) that can be applied to building to ensure a more representative picture is provided by the reported BEI. The following case studies were established to study the possibility of establishing such a boundary condition:

A. Three (3) building scenarios were created to model the influence of operating hours on the BEI computation. These three (3) building scenarios represents the followings:

1. Low Energy Building: This is a model of a building that is reasonably well optimized for energy efficiency. It has good building fabric, low lighting power density, low small power density and efficient air-conditioning equipment. This building is modeled with variable air volume system and variable chill water flow.

2. Mid Energy Building: This is a model of a building that has standard efficiency. It has moderate building fabric, medium level of lighting power density, medium level of small power density and average efficiency air-conditioning equipment. This building is modeled with variable air volume system and variable chill water flow.

3. High Energy Building: This is a model of a building that has poor energy efficiency. It has poor building fabric, high lighting power density, high small power density and poor efficiency air-conditioning equipment. This building is modeled with constant air volume system and constant chilled water flow.

The lighting and air-conditioning equipment in these three (3) buildings remain exactly the same for all the simulation cases based on the building scenario. The objective of this study is to model the same building with same equipment and occupant density but with the only differences made to the operating hour.

B. Three (3) different base loads were simulated for each building scenario. These three (3) base loads were made to study the influence of different base load on BEI and operational hours of the building. The following base loads were made:

1. Small Power base load of 10%2. Small Power base load of 35%3. Small Power base load of 50% (65% for High Energy Building).

C. Eight (8) cases of different operating hours of a building were made. These cases modeled building with operating hours of 2080 to 8760 per year. The details of the operating hours is shown in the table below:

Cases Operating hours (Mon-Fri)

Operating Hours (Sat)

Operating Hours (Sun)

Yearly Operating Hours

Base Case 9am to 5pm Off off 2080Case 1 9am to 6pm Off off 2340Case 2 8am to 6pm Off off 2600Case 3 8am to 6pm 8am to 1pm off 2860Case 4 9am to 9pm Off off 3120Case 5 9am to 9pm 9am to 9pm 9am to 9pm 4380Case 6 9am to 12 midnight 9am to 12 midnight 9am to 12 midnight 5475Case 7 24 hours 24 hours 24 hours 8760Table 8.1: Simulation Cases of Different Building Operating Hours

A total of 72 cases were simulated. Details of simulation cases can be found in the appendix.

8.1 Simulation ResultsThe results of 72 simulation cases showed that regardless of the exact operating hours and days of a building, the BEI result can be tabulated in a relatively smooth curve based on the number of building operational hours per year as shown in Charts 8.1.1.1 to 8.1.3.1 below for the 3 difference building scenarios:

8.1.1 Low Energy Building

DescriptionsHours/year

BEI of 10% BL

BEI of 35% BL

BEI of 50% BL

Base, 9to5 mon-fri 2080 113.1 133.8 146.2C1, 9to6 mon-fri 2340 109.4 127.1 137.7C2, 8to6 mon-fri 2600 104.8 120.1 129.2Interpolated Point 2700 104.0 118.5 127.3C3, 8to6 mon-fri, 8to1 sat 2860 102.7 116.1 124.2C4, 9to9 mon-fri 3120 101.3 113.0 120.0C5, 9to9 mon-sun 4380 95.1 101.8 105.7C6, 9to12 mon-sun 5475 92.1 96.2 98.6C7, 24 hours 8760 85.5 85.5 85.5

Table 8.1.1.1: Computed BEI for different hours of building operation based on existing methodology for a low energy building.

1500 2500 3500 4500 5500 6500 7500 85000

20406080

100120140160

Normalized BEI to 2700 HoursLow Energy Scenario

BEI 10% Base Load BEI 35% Base Load BEI 50% Base Load

Operating Hours a Year

Norm

alize

d BE

I (kW

h/m

2/ye

ar)

Chart 8.1.1.1: BEI Curve for different hours of building operation based on existing methodology for a low energy building

8.1.2 Mid Energy Building


BEI of 10% BL

BEI of 35% BL

BEI of 50% BL


Table 8.1.2.1: Computed BEI for different hours of building operation based on existing methodology for a mid energy building.

1500 2500 3500 4500 5500 6500 7500 85000

50

100

150

200

250

Normalized BEI to 2700 HoursMid Energy Scenario


Operating Hours a YearNorm

alize

d BE

I (kW

h/m

2/ye

ar)

Chart 8.1.2.1: BEI Curve for different hours of building operation based on existing methodology for a mid energy building

8.1.3 High Energy Scenario

Descriptions Hours/yearBEI of 10% BL

BEI of 35% BL

BEI of 65% BL


Table 7.1.3.1: Computed BEI for different hours of building operation based on existing methodology for a high energy building.

1500 2500 3500 4500 5500 6500 7500 85000

50100150200250300350

Normalized BEI to 2700 HoursHigh Energy Scenario


Operating Hours a Year

Norm

alize

d BE

I (kW

h/m

2/ye

ar)

Chart 8.1.3.1: BEI Curve for different hours of building operation based on existing methodology for a high energy building

8.2 Detailed AnalysisDetailed analysis was conducted on all the cases and it was found that the results shares similar characteristic between the different building energy scenarios. The Mid Energy Building scenario with 35% base load was selected to describe these common characteristics.

8.2.1 Mid Energy Building 35% Base LoadAnalysis of the Mid Energy Building with 35% Base Load in Chart 8.2.1.1 showed that with the exception of lighting energy index, all other energy index breakdown displayed relatively smooth curve based on the number of building operational hours per year. There were two (2) minor ‘defects’ detected that is not a perfectly smooth curve in the breakdown of energy index. These are for the building lighting and chiller system. These defects werefound to be caused by 2 factors:

1. Different operating hours of pre-cooling modeled for these buildings and2. Extended operating hours during night time (late nights Monday to Friday) versus extended

operating hours during daytime (on Saturday and Sunday).

1000 2000 3000 4000 5000 6000 7000 8000 90000

10

20

30

40

50

60

70

Normalized Energy Index to 2700 HoursMid Scn 35% Base Equip Load

EI Chiller EI AHU Fan EI Chill Water PumpEI Heat Rejection EI Lights EI Equip

Operating Hours in a Year

kWh/

m2/

year

Chart 8.2.1.1: Breakdown of various Energy Index (EI) normalized to 2700 hours/year. Mid Energy Building, 35% Base Load.

However, these minor ‘defects’ does not cause any major variation to the smooth curves found in the overall BEI computed for all 3 building scenarios as shown in Chart 8.1.1.1, 8.1.2.1 and 8.1.3.1 in the previous section.

An analysis of the impact significant of these energy breakdowns were made by deducting the Energy Index of the 24 hours scenario with the base scenario to provide Chart 8.2.1.2 below. This chart provides the reduction of Energy Index of equipment (small power), chiller, AHU fan, lighting,

heat rejection (condenser water pump and cooling tower) and chill water pump between the two (2) extreme building operating hours simulated.

Equipment Chiller AHU Fan Lighting Heat Rej Chill Water Pump

0

5

10

15

20

25

30

35

40

Energy Index Reduction (Base Case minus 24 Hours Case)

kWh/

m2/

year

Chart 8.2.1.2: Breakdown of Reduction of Energy Index between Base Case and Case 7 (24 hours)

From Chart 8.2.1.2 above, the following energy consuming machineriesare ranked according to its significant on the BEI due to the differences of operating hours of a building:

1. Equipment Energy Index (Small Power)2. Chiller Energy Index3. AHU Fan Energy Index4. Lighting Energy Index5. Chilled Water Pump Energy Index6. Heat Rejection (condenser water pump and cooling tower) Energy Index

Equipment Energy Index

1000 2000 3000 4000 5000 6000 7000 8000 900030

40

50

60

70


EI Equip


kWh/

m2/

year

Chart 8.2.1.3: Equipment (small power) Energy Index of Mid Energy Building Scenario with 35% Base Equipment Load.

Mon–Fri 8-6

Mon-Fri 8-6, Sat 8-1

Mon-Fri 9-9

Mon-Sun 9-9

Mon-Sun 9-12

Mon-Fri 9-5

Mon-Fri 9-6

24 hours

A relatively smooth curve is obtained from the equipment (small power) normalized energy index. This is expected because the normalized energy index of equipment is directly linked to the hours of base load of the building.

Comparing to the base case, the equipment energy index of the 24 hours scenario is 53% lower. It should be noted here that the equipment energy index is highly influence by its base load. The higher the base load and shorter operating hours, the computed BEI is higher. While, lower base load and longer operating hours, reduces the BEI. In these simulation case studies the following differences were found:

Descriptions 10% BL 35% BL 50% BL 65% BLLow Energy Scenario 26.2% 53.5% 62.0% NAMid Energy Scenario 24.4% 52.7% 61.4% NAHigh Energy Scenario 26.4% 53.6% NA 67.9%

Table 8.2.1.1: Energy Index Reduction of Equipment (Small Power) between Base Case and 24 Hours Case.

Although the definition of base load is the energy consumption by the building outside building operating hours, the base load energy consumption is a part of the BEI computation with good justification. Due to the reason that this base load energy is incurred during non-operational hours of the building, the computed BEI based on present methodology increases when the non-operational hour increases.

Chiller Energy Index

Chart 8.2.1.4: Chiller Energy Index (EI) normalized to 2700 hours/year. Mid Energy Building Scenario with 35% Base Equipment Load.

The chiller energy index is found to reduce as the building operational hours increases. It was found that the longer air-conditioning operational hours dampen the peak cooling load of the building. Further investigation showed that there were 2 major factors contributing to this behavior:

1. The longer air-conditioning hours kept the building structure cooler. The shorter duration of non-conditioned hours reduces the hours where heat is gained by the building structure itself. For example, if the air-conditioning system is switched off on Saturday and Sunday, the heat built up during the weekend is absorbed by the building structure, where on Monday, when the air-conditioning system is switched on, the peak cooling load of the building is higher as compared to a building where the air-conditioning system is switched on every day.

2. The longer operational hours of the building also reduces the amount of heat generated by the base load. The base load hours is reduced due to the longer operational hour of the building. Therefore, less heat is generated as well.

0:30 11:30 22:30 9:30 20:30 7:30 18:30 5:30 16:30 3:30 14:30 1:30 12:30 23:30 10:30 21:300

1000

2000

3000

4000

5000

6000

Chiller Load

C7, 24 hours C4, Mon-Fri, 9-9 Base, Mon-Fri, 9-5

kW

Sun Mon Tue Wed Thur Fri Sat

Chart 8.2.1.5: Chiller load of 3 selected cases shows that peak cooling load reduces with extended cooling hours.

The chiller energy index, Chart 8.2.1.4, showed that there is a slight influence of running the building during daytime and night time. Again, this marginal influence of the building being operated during daytime or night time cannot be detected when it is combined together with all the other energy indexes to provide the total BEI of the building as in Chart 8.1.1.1, 8.1.2.1 and 8.1.3.1.

AHU Fan Energy Index

Although the absolute value of the energy index of AHU Fan is lower than Heat Rejection and Lighting energy index, the reduction of energy index from base case to 24 hours case scenario exceed the reduction by both heat rejection and lighting energy index.

Mon–Fri 8-6

Mon-Fri 8-6, Sat 8-1

Mon-Fri 9-9

Mon-Fri 9-5

Mon-Fri 9-6

Mon-Sun 9-9 Mon-Sun 9-1224 Hours

The AHU fan was modeled as a variable air volume (VAV) system that is designed for the peak load of a building that operates 9am to 5pm. As the peak cooling load of the building reduces with the longer operational hours, the AHU fan was running more hours on part load than on full load. Due to the affinity fan law, the energy reduction is significantly high based on the reduction of the air flow rate. Therefore, the AHU Fan energy index is significantly lower per hour of use basis when it is operated for longer hours in the building.

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10111213141516


EI AHU Fan


kWh/

m2/

year

Chart 8.2.1.6: AHU Fan Energy Index (EI) normalized to 2700 hours/year. Mid Energy Building Scenario with 35% Base Equipment Load.

Lighting Energy Index

Chart 8.2.1.7: Lighting Energy Index (EI) normalized to 2700 hours/year. Mid Energy Building, 35% Base Load.

The lighting energy index, Chart 8.2.1.7 above, showed that it is significantly affected by time of day the building is operational. If building extended operational hours are during daytime such as Saturday or Sunday, the lighting energy index is lower than a building where the extended hours are during night time such as working up to 9pm on Monday to Friday. This is because the simulation model was made with daylight harvesting feature in place, where extended operation during daytime would allow some electrical lights to be switched off. However, the influence of lighting energy index is small for this building model when it is considered together total BEI of the building. This model has approximately 26% of the office area benefiting from daylight harvesting.

There is also a small influence of the lighting energy index to the overall BEI due to the base lighting load. There are certain spaces, such as lift lobby, where up to 50% of the lights are switched on during non-occupancy hours for security purpose. This kind of base lighting load is comparatively small for a building and therefore it would only contribute marginally to the building BEI computation due to different operating hours of the building.

Chilled Water Pump Energy Index

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EI Chill Water Pump


kWh/

m2/

year

Chart 8.2.1.8: Chill Water Pump Energy Index (EI) normalized to 2700 hours/year. Mid Energy Building, 35% Base Load.

The chilled water pump was modeled as a variable primary flow system for the low and mid energy building scenarios, while it was modeled as constant flow for the high energy building scenario. Again the reduction of peak cooling load due to the longer operating hours of the building reduces the chill water pump energy by over 60% for this case of mid energy building scenario with 35% equipment (small power) base load. However, since the energy consumed by the chilled water pump is already low for the base case, it does not provide much effect to the overall building BEIcomputation.

Heat Rejection Energy Index

The heat rejection energy index comprise of the condenser water pump and cooling tower. These two (2) machineries were modeled as constant speed and therefore have almost no reduction in energy index. The minor differences displayed in this study were due to the longer hour of pre-cooling, 1 hour, for the base case as opposed to 30 minutes practiced by all other cases. Part of the reason that this small variation of pre-cooling hours was implemented was to test the significant of

such small variation in the operational hours of different equipment in the building due to differences of building operational hours. In short, the heat rejection system should not provide any differences due to these machineries running at constant speed. It is only influence is the hours of operation.

1000 2000 3000 4000 5000 6000 7000 8000 900012

14

16

18


EI Heat Rejection


kWh/

m2/

year

Chart 8.2.1.8: Heat Rejection (Condenser Water Pump and Cooling Tower) Index (EI) normalized to 2700 hours/year. Mid Energy Building, 35% Base Load.

8.2.2 Mid Energy Building Scenario with 10% Base Load

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8.2.3 Mid Energy Building Scenario with 50% Base Load

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8.2.4 Low Energy Building Scenario with 10% Base Load

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Normalized Energy Index to 2700 hoursLow Scn 10% Base Equip Load

EI 10% Base Chiller EI 10% AHU Fan EI 10% Chill Water PumpEI 10% Heat Rejection EI Lights EI Equip


kWh/

m2/

year


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Normalized Energy Index to 2700 hoursLow Scn 35% Base Equip Load

EI 35% Base Chiller EI 35% AHU Fan EI 35% Chill Water PumpEI 35% Heat Rejection EI Lights EI Equip


kWh/

m2/

year


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Normalized Energy Index to 2700 HoursLow Scn 50% Base Equip Load



kWh/

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year

8.2.7 High Energy Building Scenario with 10% Base Load

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Normalized Energy Index to 2700 HoursHigh Scn 10% Base Equip Load



kWh/

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year


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8.3 BEI Boundary Conditiondue to Building Rated HoursAn attempt is made to find a boundary condition that would provide a consistent BEI value that is simple to use. These were the options considered.

1. The reported BEI could be categories into several categories of annual operating hours. I.e.a. Category 1: Annual Operating Hours of 2,000 to 2,600b. Category 2: Annual Operating Hours of 2,600 to 3,120c. Category 3: Annual Operating Hours of 3,120 to 4,380d. Category 4: Annual Operating Hours of 4,380 to 5,500e. Category 5: Annual Operating Hours above 5,500

2. Application of a Correction Factor to compensate thereported BEI to reflect a more accurate picture.

The above two (2) options would limit the error reported due to different operating hours of the building to approximately 10%.

8.3.1 Annual Operating Hours BoundariesInitial analysis from Table 7.3.1.1 to 7.3.1.3 showed that it is possible to report BEI 34% lower (24 hours scenario) or 16% higher (2,080 hours scenario) than the actual case of operating the building at 2700 hours per year.


10% BL 35% BL 50% BL

BEI% diff from 2700 hour BEI

% diff from 2700 hour BEI

% diff from 2700 hour

Base, 9to5 mon-fri 2080 113.1 8.8% 133.8 12.9% 146.2 14.9%

C1, 9to6 mon-fri 2340 109.4 5.2% 127.1 7.2% 137.7 8.1%C2, 8to6 mon-fri 2600 104.8 0.8% 120.1 1.3% 129.2 1.5%Interpolated Point 2700 104.0 0.0% 118.5 0.0% 127.3 0.0%C3, 8to6 mon-fri, 8to1 sat 2860 102.7 -1.2% 116.1 -2.1% 124.2 -2.4%C4, 9to9 mon-fri 3120 101.3 -2.6% 113.0 -4.7% 120.0 -5.7%C5, 9to9 mon-sun 4380 95.1 -8.5% 101.8 -14.1% 105.7 -16.9%C6, 9to12 mon-sun 5475 92.1 -11.4% 96.2 -18.8% 98.6 -22.5%C7, 24 hours 8760 85.5 -17.7% 85.5 -27.8% 85.5 -32.8%

Table 8.3.1.1: Low Energy Building Scenario


10% BL 35% BL 50% BL




Base, 9to5 mon-fri 2080 166.4 10.5% 196.1 14.3% 213.8 16.2%C1, 9to6 mon-fri 2340 156.5 3.9% 181.8 6.0% 197.1 7.1%C2, 8to6 mon-fri 2600 151.6 0.7% 173.4 1.1% 186.6 1.4%Interpolated Point 2700 150.6 0.0% 171.5 0.0% 184.0 0.0%C3, 8to6 mon-fri, 8to1 sat 2860 149.1 -1.0% 168.3 -1.8% 179.8 -2.2%C4, 9to9 mon-fri 3120 147.2 -2.3% 164.0 -4.4% 174.0 -5.4%C5, 9to9 mon-sun 4380 138.4 -8.1% 147.9 -13.7% 153.6 -16.5%C6, 9to12 mon-sun 5475 133.9 -11.1% 139.6 -18.6% 143.1 -22.2%C7, 24 hours 8760 126.9 -15.8% 126.9 -26.0% 126.9 -31.0%

Table 8.3.1.2: Mid Energy Scenario


10% BL 35% BL 65% BL




Base, 9to5 mon-fri 2080 244.5 8.5% 283.9 12.1% 331.0 15.6%C1, 9to6 mon-fri 2340 237.2 5.3% 270.9 7.0% 311.4 8.7%C2, 8to6 mon-fri 2600 226.7 0.6% 255.9 1.1% 290.7 1.5%Interpolated Point 2700 225.3 0.0% 253.2 0.0% 286.4 0.0%C3, 8to6 mon-fri, 8to1 sat 2860 223.1 -1.0% 248.8 -1.7% 279.5 -2.4%C4, 9to9 mon-fri 3120 219.8 -2.4% 242.2 -4.3% 269.0 -6.1%C5, 9to9 mon-sun 4380 209.1 -7.2% 221.8 -12.4% 237.2 -17.2%C6, 9to12 mon-sun 5475 203.1 -9.9% 210.8 -16.7% 220.1 -23.1%C7, 24 hours 8760 188.7 -16.2% 188.7 -25.5% 188.7 -34.1%

Table 8.3.1.3: High Energy Scenario

An attempt was made to create boundaries condition where the reported BEI should not differ approximately more than 10%. Although small power base load of 50% is commonly reported in buildings worldwide, it is proposed herewith to use 35% small power base load to provide the boundary conditions for BEI due to operating hour’s differences. The case to use 35% small power base load is based on the assumption that in Malaysian buildings where BEI is measured, the building owner would have taken appropriate actions to reduce small power base load in the building.


Low 35%

Mid 35%

High 35%

Low 35%Diff

Mid 35% Diff

High 35% Diff

Ave. Diff Notes

Base, 9to5 mon-fri 2080 133.8 196.1 283.9 0.0% 0.0% 0.0% 0.0% C1, 9to6 mon-fri 2340 127.1 181.8 270.9 5.0% 7.3% 4.6% 5.6% C2, 8to6 mon-fri 2600 120.1 173.4 255.9 10.3% 11.5% 9.9% 10.6% limit 1Interpolated Point 2700 118.5 171.5 253.2 1% 1% 1% 1.2% C3, 8to6 mon-fri, 8to1 sat 2860 116.1 168.3 248.8 3% 3% 3% 3.0% C4, 9to9 mon-fri 3120 113.0 164.0 242.2 6% 5% 5% 5.6% limit 2C5, 9to9 mon-sun 4380 101.8 147.9 221.8 10% 10% 8% 9.4% limit 3C6, 9to12 mon-sun 5475 96.2 139.6 210.8 5.5% 5.6% 5.0% 5.4% limit 4C7, 24 hours 8760 85.5 126.9 188.7 11% 9% 10% 10.2% limit 5

Table 8.3.1.4: Boundaries of approximate 10% difference.*Shaded becomes base case again to compute % differences.

Base on the analysis on Table 8.3.1.4, the following boundaries can be proposed:

Boundaries Proposed Limits of Operating Hours

Category 1 2,000 to 2,600Category 2 2,600 to 3,120 Category 3 3,210 to 4,380Category 4 4,380 to 5,500Category 5 5,500 to 8,760Table 8.3.1.5: Proposed Operating Hours Boundaries to limit BEI potential errors to approximately 10%.

This method of annual operating hours as boundaries condition will requires buildings to be categories into 5 sets of boundary conditions as shown in Table 7.3.1.5 above. These boundaries conditions will limit the reported BEI errors to a maximum of 10.6%, where longer operating hours will benefit from a lower BEI being reported.

Using this method, higher small power base load will increase the margin of error for the BEI reported. While a lower small power base load will reduce the margin of error for the BEI reported.

8.3.2 Correction FactorsA correction factor (CF) is computed as a multiplier to calibrate the BEI at different operating hours of a building to match the BEI at 2700 hours was made and is presented in Tables 8.3.2.1, 8.3.2.2 and8.3.2.3 below.


10% BL 35% BL 50% BLBEI CF BEI CF BEI CF

Base, 9to5 mon-fri 2080113.

1 0.92 133.8 0.89 146.2 0.87

C1, 9to6 mon-fri 2340109.

4 0.95 127.1 0.93 137.7 0.92C2, 8to6 mon-fri 2600 104. 0.99 120.1 0.99 129.2 0.99

8

Interpolated Point 2700104.

0 1.00 118.5 1.00 127.3 1.00C3, 8to6 mon-fri, 8to1 sat 2860

102.7 1.01 116.1 1.02 124.2 1.02

C4, 9to9 mon-fri 3120101.

3 1.03 113.0 1.05 120.0 1.06C5, 9to9 mon-sun 4380 95.1 1.09 101.8 1.16 105.7 1.20C6, 9to12 mon-sun 5475 92.1 1.13 96.2 1.23 98.6 1.29C7, 24 hours 8760 85.5 1.22 85.5 1.39 85.5 1.49

Table 8.3.2.1: Low Energy Building Scenario with Correction Factor (CF)




4 0.91 196.1 0.87 213.8 0.86

C1, 9to6 mon-fri 2340156.

5 0.96 181.8 0.94 197.1 0.93

C2, 8to6 mon-fri 2600151.

6 0.99 173.4 0.99 186.6 0.99


6 1.00 171.5 1.00 184.0 1.00C3, 8to6 mon-fri, 8to1 sat 2860

149.1 1.01 168.3 1.02 179.8 1.02

C4, 9to9 mon-fri 3120147.

2 1.02 164.0 1.05 174.0 1.06

C5, 9to9 mon-sun 4380138.

4 1.09 147.9 1.16 153.6 1.20

C6, 9to12 mon-sun 5475133.

9 1.13 139.6 1.23 143.1 1.29

C7, 24 hours 8760126.

9 1.19 126.9 1.35 126.9 1.45Table 8.3.2.2: Mid Energy Building Scenario with Correction Factor (CF)




5 0.92 283.9 0.89 331.0 0.87

C1, 9to6 mon-fri 2340237.

2 0.95 270.9 0.93 311.4 0.92

C2, 8to6 mon-fri 2600226.

7 0.99 255.9 0.99 290.7 0.99


3 1.00 253.2 1.00 286.4 1.00C3, 8to6 mon-fri, 8to1 sat 2860

223.1 1.01 248.8 1.02 279.5 1.02

C4, 9to9 mon-fri 3120219.

8 1.02 242.2 1.05 269.0 1.06

C5, 9to9 mon-sun 4380209.

1 1.08 221.8 1.14 237.2 1.21

C6, 9to12 mon-sun 5475203.

1 1.11 210.8 1.20 220.1 1.30

C7, 24 hours 8760188.

7 1.19 188.7 1.34 188.7 1.52Table 8.3.2.3: High Energy Building Scenario with Correction Factor (CF)

It was observed that the Correction Factors has a higher dependent on the base load of the building rather than the overall efficiency of the building. This observation is in line with the simulation results in Section 8.2 that showed significant influence of the equipment (small power) base load.

If a building equipment (small power) base load is measured, it is more accurate to provide Correction Factor in building based on the percentage of base load in the building. Table 8.3.2.4 to 8.3.2.6 provides the average Correction Factor depending on the building base load with very low standard deviation. In fact the highest standard deviation of 3 times (covering 99% of the statistical data) has a potential margin of error of 8.3%. In fact the margin of error, based on these correction factors provided in Table 8.3.7, 8.3.8 and 8.3.9 is less than 3% for more than 80% of the cases with a confident level of 99%.


10% BL 10% BL 10% BLLow Energy Bld CF

MidEnergy Bld CF

High EnergyBld CF Average StdDev

3 StdDev

Base, 9to5 mon-fri 2080 0.92 0.91 0.92 0.92 0.7% 2.1%C1, 9to6 mon-fri 2340 0.95 0.96 0.95 0.95 0.6% 1.7%C2, 8to6 mon-fri 2600 0.99 0.99 0.99 0.99 0.1% 0.2%Interpolated Point 2700 1.00 1.00 1.00 1.00 0.0% 0.0%C3, 8to6 mon-fri, 8to1 sat 2860 1.01 1.01 1.01 1.01 0.1% 0.4%

C4, 9to9 mon-fri 3120 1.03 1.02 1.02 1.02 0.1% 0.4%C5, 9to9 mon-sun 4380 1.09 1.09 1.08 1.09 0.6% 1.9%C6, 9to12 mon-sun 5475 1.13 1.13 1.11 1.12 0.8% 2.5%C7, 24 hours 8760 1.22 1.19 1.19 1.20 1.2% 3.6%

Table 8.3.2.4: Correction Factor (CF) of a Building with 10% Equipment Base Load



Mid Energy Bld CF

High Energy Bld CF Average StdDev

3 StdDev



Table 8.3.2.5: Correction Factor (CF) of a Building with 35% Equipment Base Load



Mid Energy Bld CF

High Energy Bld CF Average StdDev

3 StdDev



Table 8.3.2.6: Correction Factor (CF) of a Building with 50% & 65% Equipment Base Load

Unfortunately, equipment (small power) base load of a building is not easily available. Moreover, in cases where the building is running 24 hours, it is not possible to know the building base load at all. Therefore, it may not be practical to offer correction factors based on the building equipment base load.

An average of all correction factors based on the building operating hours was made and is provided in Table 7.3.10 with its standard deviation provided.

DescriptionsHours/

yearCF Average of all Cases

StdDev (68%)

2 StdDev (95%)

3 StdDev (99%)

Base, 9to5 mon-fri 2080 0.89 2.3% 4.6% 6.8%C1, 9to6 mon-fri 2340 0.94 1.4% 2.7% 4.1%C2, 8to6 mon-fri 2600 0.99 0.3% 0.7% 1.0%Interpolated Point 2700 1.00 0.0% 0.0% 0.0%C3, 8to6 mon-fri, 8to1 sat 2860 1.02 0.6% 1.2% 1.8%C4, 9to9 mon-fri 3120 1.04 1.6% 3.2% 4.7%C5, 9to9 mon-sun 4380 1.15 5.1% 10.3% 15.4%C6, 9to12 mon-sun 5475 1.21 7.5% 15.1% 22.6%C7, 24 hours 8760 1.35 12.6% 25.2% 37.9%

Table 8.3.10: Average Correction Factor (CF) of Low, Mid and High Energy Building Scenarios with 10%, 35%, 50% & 65% Equipment Base Load.

Table 7.3.10, showed that the proposed correction factors would provide a margin of error less than 5% (with 95% confidence) for annual operating hours of 2080 to 3120. As the annual operating hours of the building increases, the potential margin of error increases as well, until a peak of 25.2% (at 95% confident level) for a 24 hours operating building.

1 2 3 4 5 6 7 8 9 10 -

0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6

f(x) = 0.0029112879 x³ − 0.0547691722 x² + 0.37251275404 x + 0.33091289883R² = 0.998438453886193

Average Correction Factor

Annual Operating Hours/1000

Corr

ectio

n Fa

ctor

Chart 8.3.1: Polynomial Curve Fit of Average Correction Factor based on Building Operating Hours per Year

8.4 SummaryApplication of a correction factor was found to provide a higher confident level to allow building with different operating hours to be compensated to a building operating at 2700 hours per year. This correction factor provided a potential margin of error of less than 5% with 95% confident level for building with operating hours of 2080 to 3120 per year. For building with higher operating hours, the potential margin of error increases to maximum potential of 25.2% at 95% confident level.

With the introduction of a correction factor based on the operating hours of a building, the BEI formula can be revised as follows:


x 2700hours xCF

Where, BEIo = Office Building Energy Index as measured [kWh/(m²-year)]Rated Hours = Default operating hours of the building. CF = Correction Factor based on the Rated Hours of the building from the Tablen7.4.1 below.

Building Rated Hoursper Year CF

2080 0.892340 0.942600 0.992700 1.002860 1.023120 1.044380 1.155475 1.218760 1.35

Table 8.4.1: Average Correction Factor (CF) Proposed to Compensate Different Rated Hours

8.5 Industry Dialog FeedbackIt was deem that the proposed calibration method based on different operating hours of building is too complicated to be implemented at this point of time. In the interest of keeping the BEI computation methodology simple and easy to use, it was proposed by the industry that the BEI should be made applicable for building within the operating hours of 2,000 to 3,200 hours per year. The potential error between the two proposed limit of operating hours is only about 10%. It was deem that this error is within an acceptable limit for BEI computation for the building industry.

In short, the industry dialog session reveal that it is more important to keep the Malaysian BEI computation method simple and easy to use at this point of time to encourage more practitioners to use it now. Accuracy and complexities are only to be added on at a later stage once the basic BEI formulation has gained market acceptance.

9. Appendix

A. Office Building Energy Intensity (BEI), Whole Building Rating Method for MS 1525.

Building Energy Intensity (BEI) Definition The Whole Building Office BEI is defined as:


x 2700hours

Where, BEIo = Office Building Energy Intensity as measured [kWh/(m²-year)]Rated Hours is within 2,000 to 3,200 hours per year.

A minimum of 1 full calendar year (12 months) energy data from the utilities should be collected to compute the BEI.

Total Building Energy ConsumptionThe Total Building Energy Consumption is defined as the total net energy of electricity (or electricity equivalent) consumed or produced by the building. The building net energy consumption and production includes the following items:

All Energy consumed by Gross Floor Area (occupied and unoccupied) in the rated building. All Energy consumed by building mechanical, air conditioning, electrical, lift, plumbing, hot water and

other utility services in the rated building. All Energy consumed by the car park area in the rated building. All Energy consumed by Staff and cleaning facilities (including toilets, tea rooms and cleaners’ room &

cupboards) in the rated building. All Renewable Energy produced by the rated building. All/Partial Energy consumed by Computer Servers in the rated building:Energy from Computer Servers is added based on the following methods:

8. All Energy by Computer Server where: The total energy consumption of the server room is not sub-metered, or The server is used entirely by internal users of the rated building.

9. Partial Energy by Computer Server where: The server room has a mix of internal and external users, and The external used IT equipment and/or facility services are separately sub-metered. The floor area that may be excluded is determined by measuring the area covered by the

externally used IT equipment. The Assessor must obtain written documentation from the tenant that confirms that the

IT equipment in the excluded area is used entirely for external users. 10. Proportionally Energy by Computer Server where:

The server room has a mix of internal and external users, and The total energy consumption of the server room is sub-metered, and The external used IT equipment and/or facility services are not separately sub-metered,

and It is possible to determine the numbers of internal and external users of the IT

equipment.

Total Exclusion from Building Energy Consumption: All Energy by Computer Server where:

o The total energy consumption of the server room is sub-metered, ando The server room is used entirely for external users, or as a disaster recovery site for another

external data center, oro It is too difficult to determine the number of external users.o The Assessor must obtain written documentation from the tenant that confirms that the

server room is either used entirely for external users or as a disaster recovery site for another external data center.

Total Rated AreaThe Total Rated Area is determined through a process which:

Total Rated Area = Gross Floor Area of a development. Adjustment to the Total Rated Area for unoccupied spaces.

Gross Floor Area (GFA) of a development The GFA is defined as all covered floor areas of a building, except otherwise exempted and uncovered areas for commercial uses are deemed as the Gross Floor Area of the building. Gross floor area is measured on the overall dimensions of the building or part of the building on each floor below and above ground and includes internal and external walls.

It includes: Stairs and lifts shafts. Corridors and covered passages by which there is no public right of way. Conference rooms, board rooms, director rooms, assembly rooms and libraries. Computer rooms. Changing rooms and lavatories. Canteens, restaurants, cafeterias, kitchens, restrooms, recreation rooms, etc. Basements with activity generating uses.

It excludes: Basement car and cycle parking accommodation. Car parking above ground. Space for commercial vehicles awaiting loading or unloading. Roof top garden. Pedestrian linkage to Transit Stations (direct subterranean/underground pedestrian linkage).

Adjustment for unoccupied spaces:The Rated Area is reduced by the same proportion of the space unoccupied time. If a space is 100% unoccupied, the space has to be removed from Rated Area. If a space is occupied 9 months in a year, the Rated Area of the space is 9/12.

Rated HoursFor each Rated Area, the rated hours for that space have to be established. Rated hour is defined as the number of hours a particular area is occupied in a full year and shall follows the default business working hours of the premise.

An area weighted average rated hours is then used for the computation of the BEIo.

Rated Hours=A1H 1+A2H2+A3H 3+…+AnH n

A1+A2+A3+…+An

Where, A = Rated Area (m²)H = Hours of Occupancy of the Rated Area (hours)Hours of occupancy should be obtained based on the default business hours as declared by the building owner or tenant themselves. It should not be based on air-conditioning hours of the building.

Server Room: The rated hours of server room is based on the number of hours the server room is operating in a full year.

Default System Coefficient of Performance for District Cooling PlantThe System Coefficient of Performance (SCOP) for a District Cooling Plant is defined herewith as:

SCOP= kWh ( coolingdelivered )kWhe(district cooling plant)

Where, kWh (cooling delivered) = total cooling load delivered to buildings by district cooling plant (kWh)kWhe(district cooling plant) = total electricity and/or electricity equivalent consumption by the district cooling plant (kWh)

A minimum of one (1) full year data should be provided to compute the average System Coefficient of Performance to estimate the Air-Conditioning Electricity Equivalent for the building with the equation below.

CoolingElectricity Equivalent (kWh)=Cooling Energy PurchasedSCOP

Where,Cooling Energy Purchased,is the Annual Chilled Water Energy provided to the rated building. (kWh)SCOP, is the Average System Coefficient of Performance of the District Cooling

Plant.

A System Coefficient of Performance (SCOP) of 3.8 for District Cooling system shall be used if measured data or rated data is not available from the District Cooling Plant.

Building Occupancy Density The annual average building occupancy density shall be provided alongside the computed BEI of the rated building.

The rated building occupancy population is defined as the number of persons legitimately working in the rated building. It excludes visitors to the building but includes equivalent full time occupants. I.e. 2 part time persons working 50% of the working hours in the building is equivalent to 1 person.

The annual average building population is computed with the equation below:

AP=P1+P2+P3+…+P12

12

Where, AP = Annual Building Average Population P1 = Building Total Population of month oneP2 = Building Total Population of month twoP3 = Building Total Population of month threeP12 = Building Total Population of month twelveFull 12 months populations should be provided.

The rated building occupancy density shall be computed using the equation below:

Occupancy Density (m2/ person)=Rated AreaAP

Where, Rated Area = Total Rated Area as computed in Section 3 (m²) AP = Annual Building Average Population (persons)

B. Details of Energy Simulation Model for Section 5: BEI Rated AreaA medium rise building of 17 floors is assumed for this study. The floor to floor height is assumed to be 4 meter. The floor areas are as described in the table provided below.

No Descriptions Floor Area Units Ventilation Concept1 Office Floor Area 1650 m2/floor AC

2Lift Lobby/Walkway 170 m2/floor AC (default)

3 3 no AHU rooms 100 m2/floor AC4 4 no lift shafts 165 m2/floor NV5 Pantry 22 m2/floor NV 6 2 fire staircases 72 m2/floor NV

7 Toilets 80 m2/floorNV if located with external façade. 10 ach otherwise.

Total Area per Floor 2259 m2/floorNo of Floors 17 floorsTotal Building GFA 35,598 m2

For each simulation case, the air-conditioning system was sized for the peak design cooling load. Thereafter dynamic energy simulation of 1 full year was conducted to provide the annual energy consumption of the building for each case study.

These assumptions were made in this study to generate a comparison between building forms: No Descriptions Strategy1 Toilet Ventilation

Strategy100% Natural Ventilation. Window area assumed to be 10% of floor area. Only 50% window area is open for ventilation.

2 Toilet Lighting Strategy

100% electrical lights at 10W/m², switched on during occupancy hours. Occupancy sensor is assumed to be installed. It is assumed that the toilet lights is only switched on 50% of the time during occupancy hours and switched off during non-occupancy hours. In addition, 50% of the electrical lights will be switched off whenever outdoor exceed 15,000 lux level.

3 Pantry Lighting Strategy

100% electrical lights at 10W/m², switched on during occupancy hours. Occupancy sensor assumed as well, that will keep the lights to be switched off 50% of the time. In addition, 50% of the electrical lights will be switched off whenever outdoor exceed 15,000 lux level.

4 Pantry Ventilation Strategy

100% Natural Ventilation, Window area is assumed to be 10% of floor area. Only 50% window area is open for ventilation.

Pantry Small Power A small fridge of 330 watt is on continuously. 5 Fire Escape

Staircases Lighting Strategy

2 W/m²Lights are switched off from 8am to 7pm daily. Window area is assumed to be 10% of floor area. Only 50% window area is open for ventilation.

6 Lift Lobby/Walkway 100% lights at 10 W/m² switched on during occupancy hours from 9am to 6pm weekdays. 50% lights on during other hours and

weekends. 7 AHU rooms Always assumed to be located away from external wall because it

does not benefit in terms of daylight harvesting or view out and because it is also an air-conditioned space.

8 Office Lighting Strategy

15 W/m² switched on from the hours of 9am to 6pm week days. Office spaces with external walls are assumed to be harness daylight up to 3.5 meter depth from the façade whenever outdoor horizontal illumination is higher than 15,000 lux. In addition, 5% lights are assumed switched on during non-occupancy hour in the office space.

9 Office Small Power 15 W/m² peak load is assumed during office hours of 9am to 6pm with 30% dip of power consumption from 12:30 noon to 1:30pm on weekdays. 35% of the peak load is assumed for all other hours.

Other key assumptions:

No. Descriptions Assumptions1 Windows to wall ratio 70% for façade connected to Office space.

Window area assumed to be 10% of floor area for external façade connected to Pantry, Toilet, and Fire Escape Staircase.

2 Glazing properties Single glazing tinted. SHGC = 0.65VLT = 45%U-value 5.7 W/m²K

3 External Wall properties Typical 100mm thick Concrete Wall with 15mm Cement Screed, U-value 3.2 W/m²K

4 Internal Wall properties Typical Internal Brick Wall with Cement Screed, U-value 2.0 W/m²K

5 Roof properties Insulated Flat Roof, Heavy Weight with 50mm polystyrene foam used for a U-value of 0.52 W/m²K

6 Ventilation System VAVFan Total Pressure: 3” w.g. (750 Pa)Fan Total Efficiency: 65%Turn Down Ratio: 30%Design Off-coil Temperature: 12°C

7 Chill Water System Variable Primary FlowPump Total Head: 35 mPump Total Efficiency: 65%Minimum Flow Rate: 70% of peak. Chill Water Supply Temperature: 6.7°CChill Water Return Temperature: 13.4°C

8 Chiller Multiple Centrifugal Chillers in Parallel. Chiller capacity is identical with an allowable maximum per chiller is 800 ton. COP = 5.7 (0.62 kW/ton)

9 Condenser System Constant flow at rated condition (3 gpm/ton)Pump Total Head: 30 mPump Total Efficiency: 65%Design Condenser Water Supply Temperature: 29.4°CDesign Condenser Delta Temperature: 5.6°K

10 Cooling Tower Fan power at 0.025 kW/HRT

11 Fresh Air Supply Ashrae 62.1 (2007) 11 Infiltration The infiltration rate of the building will be based on

assumption of a crack along the window perimeter. Windows are assumed to be 2.8m height (for 70% WWR with ribbon window layout) and each piece of window is 1.2 meter width. It is also assumed that 2 pieces of windows is required to make the total height of 2.8 meter. The assumption of crack coefficient is based on 0.13 (l s-1 m-1 Pa-0.6) for weather-stripped hinged window.11

The simulation study will use wind pressure coefficients taken from the Air Infiltration and VentilationCentre’s publication Air Infiltration Calculation Techniques – An Applications Guide12. These coefficients are derived from wind tunnel experiments.

12 Office Occupancy Weekdays: 10 m²/person, 9am to 6pm, with 50% reduction at lunch time of 12:30 noon to 1:30pm.Weekends: Empty

13 Lift Core Lift Core is assumed to have an infiltration rate of 1 ach during occupancy hours and 0.5 during non-occupancy hours. Lift power is ignored in this study because it will be the same for all the buildings and have a small influence on the total energy consumption of the building.

14 Façade and External Lights Façade and external lights are ignored in this study because it will be the same for all the buildings and have a small influence on the total energy consumption of the building.

15 Other Misc Power All other miscellaneous power use is ignored. These items includes potable water pumps, escalators, security access system, etc. because it will be the same for all the buildings and have a small influence on the total energy consumption of the building.

No Descriptions Base Case 1 & 3, Larger Common Area

1Office Floor Area (m²/floor) 1650 1650

2

Lift Lobby/Walkway (m²/floor)

170 245.1

33 no AHU rooms (m²/floor) 100 100

11An Analysis and Data Summary of the AIVC’s Numerical Database. Technical Note AIVC 44, March 1994. Air Infiltration and Ventilation Centre.12Air Infiltration Calculation Techniques – An Applications Guide, Air Infiltration and Ventilation Centre.University of Warwick Science Park.Sovereign Court, Sir William Lyons Road, Coventry CV4 7EZ.

44 no lift shafts (m²/floor) 165 165

5 Pantry (m²/floor) 22 40.73

6Fire staircases (m²/floor) 72 72

7 Toilets (m²/floor) 80 96.72

8Total Area per Floor (m²) 2094 2204.55

9 No of Floors 17 1710 Total GFA (m²) 35,598 37,47711 Total NLA (m²) 28,050 28,05012 Total ACA (m²) 32,640 33,917

13Floor to Floor Height (m) 4 4

14 Floor Efficiency 78.8% 74.8%

15 Plan View

Details of Energy Simulation Model for Section 7: Building Operating Hours & NormalizationThe same building model is used from Section 5 for this study. There are 3 major items addressed by Section 7 simulation model. These are:

1. Building Energy Efficiency Scenarios.a. Low Energy Building Scenario.b. Mid Energy Building Scenario. c. High Energy Building Scenario.

2. Equipment (Small Power) Base Load Scenarios.a. 10% Equipment base load. b. 35% Equipment base load. c. 50% Equipment base load. (65% for High Energy Building Scenario)

3. 8 Different Building Operating Hours.

Building Energy Efficiency Scenarios:

Descriptions Low Energy Building Mid Energy Building High Energy BuildingExternal Walls Brick Wall

U-value: 2.95 W/m²KConcrete WallU-value: 3.4 W/m²K

Concrete WallU-value: 3.4 W/m²K

External Windows Double GlazingU-value: 3.12 W/m²KSHGC: 0.25

Single Tinted GlazingU-value: 6.0 W/m²KSHGC: 0.63

Single Tinted GlazingU-value: 6.0 W/m²KSHGC: 0.63

Roof Insulated Flat Roof Insulated Flat Roof Insulated Flat Roof

U-value: 0.5 W/m²K U-value: 0.5 W/m²K U-value: 0.5 W/m²KOffice Internal Load Lighting: 10.5 W/m²

People: 10 m²/personEquipment: 10.5 W/m²

Lighting: 15 W/m²People: 10 m²/personEquipment: 15 W/m²

Lighting: 21 W/m²People: 10 m²/personEquipment: 21 W/m²

Walkway (Lift Lobby) Internal Load

Lighting: 7 W/m² Lighting: 10 W/m² Lighting: 16 W/m²

Staircase Internal Load Lighting: 2 W/m² Lighting: 2 W/m² Lighting: 2 W/m²Pantry Internal Load Lighting: 6 W/m²

Fridge: 330 WattLighting: 10 W/m²Fridge: 330 Watt

Lighting: 15 W/m²Fridge: 700 Watt

Toilet Internal Load Lighting: 6.5 W/m² Lighting: 10 W/m² Lighting: 13 W/m²AHU Fan Efficiency 72% total efficiency

750 total pressure65% total efficiency750 total pressure

52% total efficiency750 total pressure

AHU Fan Type VAV VAV CAVChiller COP 3 Centrifugal chillers,

COP 6.3, 6.7°C supply Temp, Delta T of 5.6°C

3 Centrifugal chillers, COP 5.7, 6.7°C supply Temp, Delta T of 5.6°C

3 Screw chillers,COP 5.5, 6.7°C supply Temp, Delta T of 5.6°C

Chilled Water Pump Variable Primary, 330 W per l/s

Variable Primary, 528 W per l/s

Constant Primary600 W per l/s

Condenser Water Pump

Constant350 W per l/s



Cooling Tower VSD control0.0105 W per kW heat rejection

2 speed control0.0105 W per kW heat rejection

Constant speed0.0105 W per kW heat rejection

8 Different Building Operating Hours:

Cases Operating hours (Mon-Fri)

Operating Hours (Sat)

Operating Hours (Sun)

Yearly Operating Hours

Base Case 9am to 5pm off off 2080Case 1 9am to 6pm off off 2340Case 2 8am to 6pm off off 2600Case 3 8am to 6pm 8am to 1pm off 2860Case 4 9am to 9pm off off 3120Case 5 9am to 9pm 9am to 9pm 9am to 9pm 4380Case 6 9am to 12 midnight 9am to 12 midnight 9am to 12 midnight 5475Case 7 24 hours 24 hours 24 hours 8760Table 7.1: Simulation Cases of Different Building Operating Hours

Descriptions Base Case Case 1 Case 2 Case 3AC Hours Mon-Fri: 8am to

5:30 pmSat: OffSun: Off

Mon-Fri: 8am to 6:30 pmSat: OffSun: Off

Mon-Fri: 7:30am to 6:30 pmSat: OffSun: Off

Mon-Fri: 7:30am to 6:30 pmSat: 7:30am to 1pmSun: Off

Lobby Lights Mon-Fri: 100% 9am to 5:30 pm, 50% 5:30 pm to 9amSat: 50% Sun: 50%

Mon-Fri: 100% 9am to 6:30 pm, 50% 6:30 pm to 9amSat: 50% Sun: 50%

Mon-Fri: 100% 8am to 6:30 pm, 50% 6:30 pm to 8amSat: 50% Sun: 50%

Mon-Fri: 100% 8am to 6:30 pm, 50% 6:30 pm to 8amSat: 100% 8am to 1 pm, 50%

onwardsSun: 50%

Office Lights Mon-Fri: 100% 9am to 5pm, 5% 5pm to 9amSat: 5%Sun: 5%Daylight Harvesting 26% of space

Mon-Fri: 100% 9am to 6pm, 5% 6pm to 9amSat: 5%Sun: 5%Daylight Harvesting 26% of space

Mon-Fri: 100% 8am to 6pm, 5% 6pm to 8amSat: 5%Sun: 5%Daylight Harvesting 26% of space

Mon-Fri: 100% 8am to 6pm, 5% 6pm to 8amSat: 100% 8am to 1pm, 5% 1pm onwardsSun: 5%Daylight Harvesting 26% of space

Office Occupancy Mon-Fri: 100% 9am to 5pm. 50% 12 noon to 1 pm. Sat: 0%Sun: 0%

Mon-Fri: 100% 9am to 6pm. 50% 12 noon to 1 pm. Sat: 0%Sun: 0%

Mon-Fri: 100% 8am to 6pm. 50% 12 noon to 1 pm. Sat: 0%Sun: 0%

Mon-Fri: 100% 8am to 6pm. 50% 12 noon to 1 pm. Sat: 100% 8am to 1pm Sun: 0%

Office Equipment Mon-Fri: 100% 9am to 5pm. 70% 12 noon to 1 pm. Base Load 5pm to 9amSat: Base LoadSun: Base Load

Mon-Fri: 100% 9am to 6pm. 70% 12 noon to 1 pm. Base Load 6pm to 9amSat: Base LoadSun: Base Load

Mon-Fri: 100% 8am to 6pm. 70% 12 noon to 1 pm. Base Load 6pm to 8amSat: Base LoadSun: Base Load

Mon-Fri: 100% 8am to 6pm. 70% 12 noon to 1 pm. Base Load 6pm to 8amSat: 100% 8am to 1pm, Base Load 1 pm onwardsSun: Base Load

Pantry Lights Mon-Fri: 100% 9am to 5pm. Daylight Harvesting 50% of spaceSat: OffSun: Off

Mon-Fri: 100% 9am to 6pm. Daylight Harvesting 50% of spaceSat: OffSun: Off

Mon-Fri: 100% 8am to 6pm. Daylight Harvesting 50% of spaceSat: OffSun: Off

Mon-Fri: 100% 8am to 6pm. Daylight Harvesting 50% of spaceSat: 100% 8am to 1pm. Sun: Off

Staircase Lights Mon-Sun: 100% 6:30 pm to 8amDaylight 8am to 6:30 pm

Mon-Sun: 100% 6:30 pm to 8amDaylight 8am to 6:30 pm



Toilet Lights Mon-Fri: 50% 9am to 5pmSat: OffSun: Off

Mon-Fri: 50% 9am to 6pmSat: OffSun: Off

Mon-Fri: 50% 8am to 6pmSat: OffSun: Off

Mon-Fri: 50% 8am to 6pmSat: 50% 8am to 1pm Sun: Off

Descriptions Case 4 Case 5 Case 6 Case 7AC Hours Mon-Fri: 8am to 9

pmSat: OffSun: Off

Mon-Sun: 8am to 9 pm

Mon-Sun: 8am to 12 midnight

24 hours daily

Lobby Lights Mon-Fri: 100% 9am to 9 pm, 50% 9 pm to 9amSat: 50% Sun: 50%

Mon-Sun: 100% 9am to 9 pm, 50% 9 pm to 9am

Mon-Sun: 100% 9am to 12 midnight, 50% 12 midnight to 9am

24 hours daily

Office Lights Mon-Fri: 100% 9am to 9pm, 5% 9pm to 9amSat: 5%Sun: 5%Daylight Harvesting 26% of space

Mon-Sun: 100% 9am to 9pm, 5% 9pm to 9amDaylight Harvesting 26% of space

Mon-Sun: 100% 9am to 12 midnight, 5% 12 midnight to 9amDaylight Harvesting 26% of space

24 hours dailyDaylight Harvesting 26% of space

Office Occupancy Mon-Fri: 100% 9am to 9pm. 50% 12 noon to 1 pm. Sat: 0%Sun: 0%

Mon-Sun: 100% 9am to 9pm. 50% 12 noon to 1 pm.

Mon-Sun: 100% 9am to 12 midnight. 50% 12 noon to 1 pm.

100% 24 hours daily

Office Equipment Mon-Fri: 100% 9am to 9pm. 70% 12 noon to 1 pm. Base Load 9pm to 9amSat: Base LoadSun: Base Load

Mon-Sun: 100% 9am to 9pm. 70% 12 noon to 1 pm. Base Load 9pm to 9am

Mon-Sun: 100% 9am to 12 midnight. 70% 12 noon to 1 pm. Base Load 12 midnight to 9am

100% 24 hours daily

Pantry Lights Mon-Fri: 100% 9am to 9pm. Daylight Harvesting 50% of spaceSat: OffSun: Off

Mon-Sun: 100% 9am to 9pm. Daylight Harvesting 50% of space

Mon-Sun: 100% 9am to 12 midnight. Daylight Harvesting 50% of space

24 hours daily Harvesting 50% of space

Staircase Lights Mon-Sun: 100% 6:30 pm to 8amDaylight 8am to 6:30 pm




Toilet Lights Mon-Fri: 50% 9am to 9pmSat: OffSun: Off

Mon-Sun: 50% 9am to 9pm

Mon-Sun: 50% 9am to 12 midnight

50% 24 hours daily

executive summary - pam northern...

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