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NREL is a national laboratory o the U.S. Department o Energy, Ofce o Energy

Efciency and Renewable Energy, operated by the Alliance or Sustainable Energy, LLC.

Retail Building Guide

or Entrance Energy

Efciency Measures

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Contents

Overview 1

Section 1 Vestibule Additions: Simplied Method 4

Section 2 Vestibule Additions: Simulation-Based Method 10

Section 3 Vestibule Additions: Leveraging an Example Simulation or Supermarkets 13

Section 4 Door Operation Changes: Simplied Method 17

Section 5 Door Operation Changes: Simulation-Based Method 22

Section 6 Door Operation Changes: Leveraging an Example Simulation or Large Retail Buildings 25

Reerences 29

Appendix A

Vestibule Additions: Background and Development o Equations 30

Appendix B

Door Operation Changes: Background and Development o Equations 33

Appendix C

Additional Considerations and Tips or Choosing Entrance Strategies 37

Appendix D

DOE Climate Zones and Representative Cities 40

Appendix E Worksheet or Section 1

Vestibule Additions: Simplied Method 41

Appendix F Worksheet or Section 3

Vestibule Additions: Leveraging an Example Simulation or Supermarkets 43

Appendix G Worksheet or Section 4

Door Operation Changes: Simplied Method 44

Appendix H Worksheet or Section 6

Door Operation Changes: Leveraging an Example Simulation or Large Retail Buildings 46

Nomenclature

ASHRAE American Society o Heating, Rerigerating and Air-Conditioning Engineers

CFM cubic eet per minuteCOP coecient o perormance

DOE US Department o Energy

NREL National Renewable Energy Laboratory

PNNL Pacic Northwest National Laboratory

TMY Typical Meteorological Year

AcknowledgmentsThis document was produced in collaboration with the Commercial Building Energy Alliances, a partnership sponsored by the

Department o Energy (DOE) The authors would like to thank the DOE Building Technologies Program or its support This document

was prepared or DOE under Task BEC71311

The Center or Electricity, Resources, and Building Systems Integration at NREL led the production o this guide The instructions arebased on analysis led by Justin Stein, and the guide was assembled by Justin Stein and Feitau Kung The authors acknowledge the

work o Eric Bonnema and Lesley Herrmann in developing earlier large retail building models that were modiied or this study The

authors thank Michael Deru, Daniel Studer, William Livingood, Matt Leach, and Rois Langner or their technical assistance and reviews

Several retail industry representatives contributed guidance that inormed the strategies discussed in this guide In particular,

Ben Ferrell and Paul Holliday o Lowes, Pat Hagan o Wawa, and David Oshinski o The Home Depot provided inormative data about

building system and operation assumptions Thank you to these and other members o the Retailer Energy Alliances Whole-Building

Systems Project Team or your eedback and support

3i

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2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simplified

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example

1Option A:

Simplified

Method

Reference

Appendice

Overview

Careully designed and operated building entrances can help control energy consumption and operating costs, as well as

increase occupant comort Historically, designers and operators have had little inormation about how much energy such

changes can save

This guide addresses the previous resource gap by synthesizing results rom multiple research eorts into methods and

examples that can be used by retail building engineers to produce preliminary savings estimates It provides step-by-step

instructions about how to estimate the energy and cost savings o two types o entrance energy eiciency measures: vesti-

bule additions and door operation changes

Examples show a whole-building energy savings potential range o 1%9% or these two measures For instance, an example

retail building in Chicago could save $2,000 annually with the addition o a vestibule1 Another example building in Chicago

with a large bay door could save $5,400 annually with a door operation change2

The measures can be applied to the ollowing types o entrances:

For vestibule additions: Doors, such as typical customer entrance doors, that open and close as individuals pass

through

For door operation changes: Doors, such as customer doors used or large item pickups or shipping and receiving,

which are let open or extended periods Measures may include changes to when or how long the doors are open

and changes to the eective door area

This document relects collaborative input rom the members o the Whole-Building Systems Project Team in DOEs Retailer

Energy Alliance

Options or Generating Initial Savings Estimates

For each measure, the guide provides several approaches:

Option A Use the Simpliied Method: You can use the equations and tables provided in this guide to generate

initial energy and cost savings potential estimates The instructions reerence a combination o indings rom

a National Renewable Energy Laboratory (NREL) analysis o two speciic building types and research by other

institutions

Applicability: Free-standing retail buildings Equations are provided or 10 climate zones

Advantages: Relatively quick and easy

Disadvantages: Little reedom to enter site-speciic inormation; does not capture system interactions

Option B Perorm Whole-Building Energy Simulation: You can use your estimated iniltration rates with

whole-building energy simulation to capture system interactions and site-speciic conditions The energy impact o

iniltration through entrances depends on a variety o actors, including building size; the time o day when doors

are open; whether the heating, ventilation, and air-conditioning (HVAC) system is heating or cooling when doors are

open; and whether humidity is a concern

Applicability: Free-standing retail buildings

Advantages: Freedom to enter site-speciic inormation; captures system interactions

Disadvantages: Requires more time and eort than other options; may require external expertise

Option C Leverage Examples From Research: Two simulation cases are provided as examples I your building is

similar to one, you can use the instructions to adapt the example results and estimate the energy and cost implica-

tions or your scenarios These theoretical models represent generic building types:

Supermarket Building Model With a Vestibule Addition

The supermarket building model is 45,000 t2 It includes a total sales area o 25,000 t2, rerigerated cases

throughout the sales area, and HVAC equipment with humidity controls

1 The vestibule addition includes sliding doors, where the interior and exterior doors are directly across rom each other The example assumes the building

is open 24 hours per day, the main entrance has a 42-t2 doorway, and an average o 110 people enter or exit the door per hour The savings also depend on

assumptions or wind at the site2 The baseline case includes a 20-t wide by 12-t high bay door that is open on average or 3 hours in the morning, typically rom 6:00 am to 9:00 am The

alternative case changes the deault opening height to 7 t and allows the door to open to the ull height o 12 t when necessary

Overview

11

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2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simpliied

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example

1Option A:SimpliiedMethod

Reerences

Appendices

VESTIBULE

ADDITIONS

D

O

O

R

O

PERATIO

N

Overview

Applicability: Supermarket buildings o similar scale and operation Results are provided or six climate zones

Advantages: Relatively quick and easy Captures system interactions or a generic example

Disadvantages: Little reedom to enter site-speciic inormation or capture site-speciic system interactions

Large Retail Building Model With Door Operation Changes

The large retail building model is 110,000 t2 It includes a total sales area o 87,500 t2 with no rerigerated

cases It was designed to represent a home improvement store with a bay door or customers purchasing

large items

Applicability: Large retail building o similar scale, use, and operation Results are provided or six climate

zones

Advantages: Relatively quick and easy Captures system interactions or a generic example

Disadvantages: Little reedom to enter site-speciic inormation or capture site-speciic system interactions

Figure 1 and Figure 2 provide decision trees that direct you to sections o interest or each measure and approach

Rene assumptions and

iterate using whole-building

simulation or other

analytical tools.

Implement selected

measure in your buildings.

See Appendix C for suggestions.

Reject measure.

Based on initial estimate,

choose next steps.

Vestibule Additions:Choose Approach for Initial Estimate

Option A:

Use the simplied method.

For: Free-standing retail

buildings

Pros: Speed; ease

Cons: Generic; does not

capture system interactions

Follow instructions in

Section 1 to estimatesavings.

Option B:

Perform whole-building

energy simulation.


buildings

Pros: More site-specic;


Cons: More time and

eort; may require

external expertise


Section 2 to estimate

savings.

Option C:

Leverage simulation

example from research.

For: Supermarkets of

similar scale and operation

Pros: Speed; ease; captures

system interactions for one

example

Cons: Applicability

constrained to similar

buildings

See Example Case in


savings.

Figure 1 Decision tree or vestibule additions

2

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2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simplified

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example

1Option A:

Simplified

Method

Reference

Appendice

Overview

Rene assumptions and

iterate using whole-building

simulation or other

analytical tools.

Implement selected

measure in your buildings.

See Appendix C for suggestions.

Reject measure.

Based on initial estimate,

choose next steps.

Door Operation Changes:Choose Approach for Initial Estimate

Option A:

Use the simplied method.


buildings

Pros: Speed; ease

Cons: Generic; does not




savings.

Option B:

Perform whole-building

energy simulation.


buildings

Pros: More site-specic;


Cons: More time and

eort; may require

external expertise



savings.

Option C:

Leverage simulation

example from research.

For: Large retail buildings

of similar scale, use, and

operation

Pros: Speed; ease; captures

system interactions for one

example

Cons: Applicability

constrained to similar

buildings

See Example Case in Section

6 to estimate savings.

Figure 2 Decision tree or door operation changes

3

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4

AppendicesAppendicesAppendicesAppendicesAppendices

2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simpliied

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example


Reerences

Appendices

VESTIBULE

ADDITIONS

D

O

O

R

O

PERATIO

N

Overview

4

This method applies to

Building type: Free-standing retail buildings Equations are provided or 10 climate zones

How the door is used: The door opens and closes as individuals pass through, as with a typical customer entrancedoor (This excludes doors let open or extended periods)

Door location: At the perimeter o a conditioned space

Compare to other methods in this guide


Disadvantages: Little reedom to enter site-specic inormation; does not capture system interactions

Introduction

Vestibules can reduce iniltration at entrances where:

Doors open and close as individuals pass through, rather than being let open or extended periods Traic passes requently into conditioned spaces

Revolving doors are not practical

You can use this section to estimate the energy and cost implications associated with vestibule additions

Appendix A provides details about how the steps and equations in this section were developed

Instructions

Follow these instructions to irst estimate iniltration rates associated with your current door use scenario Then proceed

with the simpliied calculations to complete the savings estimate (A worksheet is provided in Appendix E to supplement this

section)

Step 1 Estimate an airlow coeicient based on door uses per hour

Use Equations 11 through 14 to estimate the corresponding airlow coeicients or cases with and without a vestibule and

cases with dierent door types and orientations The door use rate (people per hour) is the average number o one-way trips

through the door

This value should be the annual average door use rate during entrance operating hours Once you deine the entrance

operating hours, you need to use the same value or this parameter throughout the section

I you do not know the actual door use rate, you can use the average number o retail sales transactions per hour as an estimate

Example: During a typical week, a retail building has 3,500 transactions. There is one customer entrance, which is unlocked

between 10:00 a.m. and 8:0 0 p.m. each day, for 70 entrance operating hours per week. This yields an average of 50 transactions per

hour during entrance operating hours. Because this is the only customer entrance, the retailer assumes that 50 people on average

enter and exit the door per hour. This translates to 100 one-way trips per hour, or a door use rate of 100 people per hour.

Section 1

Vestibule Additions: Simpliied Method

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6


2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simpliied

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example


Reerences

Appendices

VESTIBULE

ADDITIONS

D

O

O

R

O

PERATIO

N

Overview

Step 4 Select a low-normalized climate actor

The low-normalized climate actor is a user input that will be used in Equation 16 This input accounts or variations in inil-

tration rate by climate, and is normalized by the iniltration low rate through the door Use Table 12 to select the appropriat

actor or your location Choose the city with the most similar climate (See Appendix D or a US map o the DOE climate

zones and representative cities)

Example: A retail building is located in Columbus, Ohio. The building owner uses Appendix D and Table 12 to determine that Chicago

Illinois, has the most similar climate as it is in the same climate zone. The owner selects the Climate Zone 5A value, FCF= 0.00994.

Table 12 Flow-Normalized Climate Factors (FCF)

LocationFlow-Normalized Climate Factors, FCF

(MMBtuday/h/cm)Climate Zone Reerence City

1A Miami, Florida 000051

2A Houston, Texas 000193

3A Atlanta, Georgia 000501

3B Las Vegas, Nevada 000389

4A Baltimore, Maryland 000761

4C Seattle, Washington 000775

5A Chicago, Illinois 000994

5B Boulder, Colorado 000966

6A Minneapolis, Minnesota 001185

7 Duluth, Minnesota 001515

Step 5 Identiy a time-o-day multiplier

I you know your door typically opens and closes within speciic timerames, you can use the time-o-day multipliers in

Table 13 to adjust your estimate Otherwise, assume a time-o-day multiplier o 1 The dierences between the average

outdoor and indoor temperatures or the speciied timerames were used to develop the multipliers

Example: A retail building entrance in Columbus, Ohio, is typically open to customers from 7:00 a.m. to 9:00 p.m. The owner uses

Appendix D and Table 13 and observes that Chicago, Illinois, has the most similar climate as it is in the same climate zone. The

owner also notes that the average entrance operating hours (7:00 a.m. to 9:00 p.m.) overlap three timeframes in the table: 6:00 a.m.

to 12:00 p.m., 12:00 p.m. to 6:00 p.m., and 6:00 p.m. to 12:00 a.m. The time-of-day multipliers for these timeframes are 0.95, 0.83,

and 1.05, respectively.

Option 1: The owner could calculate a simple average of these three time-of-day multipliers to yield MT= 0.94.

Option 2: The owner could calculate a weighted average. Of the 14 entrance operating hours per day, 5 fall between 6:00 a.m.and 12:00 p.m., 6 fall between 12:00 p.m. and 6:00 p.m., and 3 fall between 6:00 p.m. and 12:00 a.m. With this option,

MT= 0.95 (5/14) + 0.83 (6/14) + 1.05 (3/14) = 0.92.

(If this example were continued into Step 6, the entrance operating hours, H, in Equation 16 would equal 14 hours per day.)

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7

AppendiceAppendiceAppendice

2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simplified

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example

1Option A:

Simplified

Method

Reference

Appendice

Overview

Table 13 Time-o-Day Multipliers (MT) or Vestibule Equations

Location Timerame That Best Aligns With Entrance Operating Hours

ClimateZone

Reerence City12:00 a.m. to

6:00 a.m.6:00 a.m. to12:00 p.m.

12:00 p.m. to6:00 p.m.

6:00 p.m. to12:00 a.m.

1A Miami, Florida 021 114 184 081

2A Houston, Texas 146 115 023 116

3A Atlanta, Georgia 138 108 060 094

3B Las Vegas, Nevada 145 096 036 123

4A Baltimore, Maryland 127 098 071 104

4C Seattle, Washington 133 097 071 099

5A Chicago, Illinois 117 095 083 105

5B Boulder, Colorado 141 089 063 106

6A Minneapolis, Minnesota 116 100 085 099

7 Duluth, Minnesota 118 099 080 102

Step 6 Estimate your energy savings potential

Use Equation 16 to estimate the whole-building energy savings potential associated with your vestibule addition

Esavings = FCF MT H (CFMC CFMP) (16)

where:

Esavings = annual whole-building energy savings potential (MMBtu)

FCF = low-normalized climate actor (MMBtuday/h/cm; see Table 12)

MT = time-o-day multiplier (dimensionless; see Table 13)

H = entrance operating hours per day, annual average (h/day)

CFMC = average iniltration rate during hours o use or current strategy (cm)

CFMP = average iniltration rate during hours o use or proposed strategy (cm)

Example: Continuing the example from Step 5, a retail building entrance in Columbus, Ohio, is open on average from 7:00 a.m. to

9:00 p.m. The entrance operating hours, H, in Equation 16 would equal 14 hours per day. Use this in Equation 16 along with the

values for FCF, MT, and CFM that you found in previous steps.

Step 7 Select cooling and heating raction multipliers

Use Table 14 to identiy the appropriate cooling and heating raction multipliers that correspond to your location and the

time your door is typically in use Choose the city with the most similar climate (See Appendix D or a US map o the DOE

climate zones and representative cities) The multipliers relect the proportion o energy savings potential that is attributable

to cooling or heating energy savings

Assuming Esavings is positive in Step 6, a positive cooling (or heating) raction multiplier in Table 14 indicates that the

proposed strategy will reduce the cooling (or heating) load

The cooling raction multiplier is occasionally a low negative number In such cases, i Esavings is positive, the proposed strategy

will increase the cooling load slightly, but the net whole-building energy consumption will still decrease

As in the example rom Step 5, i the average entrance operating hours overlap multiple timerames, a cooling raction

multiplier and a heating raction multiplier can be estimated in Step 7 by per orming either a simple average or a weighted

average o values rom applicable timerames in the table

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8


2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simpliied

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example


Reerences

Appendices

VESTIBULE

ADDITIONS

D

O

O

R

O

PERATIO

N

Overview

Table 14 Entrance Cooling (MCLG) and Heating (MHTG) Fraction Multipliers or Vestibule Equations

Location Entrance

Cooling and

Heating

Fraction

Multipliers

Timerame That Best Aligns With Entrance Operating Hours

ClimateZone

ReerenceCity

All Day(24-HourPeriod)

12:00 a.m.to

6:00 a.m.

6:00 a.m.to

12:00 p.m.

12:00 p.m.to

6:00 p.m.

6:00 p.m.to

12:00 a.m.

1AMiami,

Florida

MCLG 100 100 100 100 100

MHTG 000 000 000 000 000

2AHouston,

Texas

MCLG 029 011 026 100 000

MHTG 071 111 074 000 100

3AAtlanta,

Georgia

MCLG 001 003 000 009 002

MHTG 099 103 100 091 102

3BLas Vegas,

Nevada

MCLG 023 002 018 069 008

MHTG 077 102 082 031 092

4ABaltimore,

Maryland

MCLG 001 002 000 002 002

MHTG 101 102 100 098 102

4CSeattle,

Washington

MCLG 004 002 005 005 005

MHTG 104 102 105 105 105

5AChicago,

Illinois

MCLG 001 002 001 001 002

MHTG 101 102 101 099 102

5BBoulder,

Colorado

MCLG 001 002 001 001 003

MHTG 101 102 101 099 103

6AMinneapolis,

Minnesota

MCLG 001 002 001 000 002

MHTG 101 102 101 100 102

7Duluth,

Minnesota

MCLG 002 001 001 002 002

MHTG 102 101 101 102 102

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9


2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simplified

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example

1Option A:

Simplified

Method

Reference

Appendice

Overview

Step 8 Estimate the costs associated with cooling and heating

According to your utility rate structure, estimate the costs o electricity or cooling ($/kWh) and natural gas or heating

($/therm) or your scenarios

Step 9 Estimate your cost savings potential

Use Equation 17 and the estimated annual whole-building energy savings potential (value rom Step 6) to estimate the

energy cost savings potential

Csavings = Esavings (1000/341 MCLG CCLG + 10 MHTG CHTG) (17)

where:

Csavings = annual energy cost savings potential ($)

Esavings = annual energy savings potential (MMBtu)

MCLG = cooling raction multiplier (dimensionless; see Table 14)

CCLG = cost o electricity or cooling ($/kWh)

MHTG = heating raction multiplier (dimensionless; see Table 14)

CHTG = cost o natural gas or heating ($/therm)

1000/341 = conversion actor (kWh/MMBtu)

10 = conversion actor (therm/MMBtu)

Step 10 Choose your next steps

Use these initial estimates to decide whether to perorm urther site-speciic analyses or engage vendors or contractors to

price retroit or new construction options Appendix C provides suggestions about how to implement such a measure

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10


2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simpliied

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example


Reerences

Appendices

VESTIBULE

ADDITIONS

D

O

O

R

O

PERATIO

N

Overview

10


Building type: Free-standing retail buildings

How the door is used:The door opens and closes as individuals pass through, as with a typical customer entrancedoor (This excludes doors let open or extended periods)

Door location: Any


Advantages: Freedom to enter site-specic inormation; capture system interactions

Disadvantages: Requires more time and efort; may require external expertise

Introduction

Vestibules can reduce iniltration at entrances where:

Doors open and close as individuals pass through, rather than being let open or extended periods

Traic passes requently into conditioned spaces

Revolving doors are not practical

Engineers can use whole-building energy simulations to estimate the energy and cost implications associated with vestibule

additions This section provides iniltration rates or a building with and without a vestibule or use in a whole-building

energy simulation

Engineers who have already used Section 1 to conduct an initial estimate can also use this section to conduct a site-speciic

analysis beore implementing such a measure


InstructionsUse the ollowing steps to irst estimate iniltration rates associated with your current door use scenario Then proceed with

whole-building energy simulation to complete the savings estimate

Step 1 Estimate an airlow coeicient based on door uses per hour

Use Equations 21 through 24 to estimate the corresponding airlow coe icients or cases with and without a vestibule and

cases with dierent door types and orientations The door use rate (people per hour) is the average number o one-way trips

through the door

This value should be the annual average door use rate during entrance operating hours Once you deine the entrance

operating hours, you need to use the same value or this parameter throughout the section

I you do not know the actual door use rate, you can use the average number o retail sales transactions per hour to estimate i

Example: During a typical week, a retail building has 3,500 transactions. There is one customer entrance, which is unlocked

between 10:00 a.m. and 8:0 0 p.m. each day, for 70 entrance operating hours per week. This yields an average of 50 transactions per

hour during these hours. The retailer assumes 50 people on average enter and exit the door per hour. This translates to 100 one-way

trips per hour, or a door use rate of 100 people per hour.

Section 2

Vestibule Additions: Simulation-Based Method

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11


2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simplified

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example

1Option A:

Simplified

Method

Reference

Appendice

Overview

For a case without a vestibule:

CA = 00024 PPH2 + 3813 PPH 4219 (21)

For a vestibule with swinging doors:

CA = 00016 PPH2 + 2722 PPH 8591 (22)

For a vestibule with sliding doors, where the inner and outer doors are across rom each other:

CA = 00013 PPH2 + 2479 PPH 7518 (23)

For a vestibule with sliding doors, where the outer doors are on the let or right side o the vestibule:

CA = 00012 PPH2 + 2229 PPH 6637 (24)

where:

CA = airlow coeicient ((cm)/t2/(in o water)05)

PPH = annual average door use rate during entrance operating hours (people per hour)

The equations are second-order polynomial best it lines that summarize selected airlow coeicients rom Yuill (1996) See

Appendix A or details

Step 2 Identiy a pressure actor

Choose your pressure actor, RP, rom Table 21 The methodology rom the section titled Air Leakage through Automatic

Doors in Chapter 16 o theASHRAE Handbook of Fundamentals (ASHRAE 2009) was used to derive the values You can adjustthe conservatism or aggressiveness o your iniltration estimate by selecting dierent assumptions or average wind speed

and local wind pressure coeicient, CP Appendix A provides methodology details

Table 21 Pressure Factors (RP)

Average Wind SpeedWhen Door Is in Use

(mph)

Option 1:Assume Wind Pressure Coecient

With Moderate Impact on Infltration(Cp = 0.45)

Option 2:Assume Wind Pressure Coecient

With Maximum Impact on Infltration(Cp = 0.70)

5 007 009

10 015 018

15 022 028

20 029 037

Step 3 Estimate your iniltration rates

Apply your airlow coeicients, pressure actor, and door area in Equation 25 (ASHRAE 2009) Estimate your iniltration rates

(cm) or cases with and without a vestibule

CFM = CA A RP (25)

where:

CFM = iniltration rate (cm)

CA = airlow coeicient ((cm)/t2/(in o water)05)

A = area o the door opening (t2)

RP = pressure actor ((in o water)05)

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12


2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simpliied

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example


Reerences

Appendices

VESTIBULE

ADDITIONS

D

O

O

R

O

PERATIO

N

Overview

Step 4 Estimate your energy and cost savings potential

Use the iniltration rates rom Step 3 in your own energy simulations to estimate the impact o iniltration on energy

consumption and cost or dierent scenarios I you have a model o an existing building without a vestibule, you can model

a vestibule addition by altering the iniltration rates associated with its entrance




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2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simplified

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example

1Option A:

Simplified

Method

Reference

Appendice

Overview

13


Building type: Supermarket building o similar scale and operation as the example in this section Results are

provided or six climate zones

How the door is used:The door opens and closes as individuals pass through, as with a typical customer

entrance door (This excludes doors let open or extended periods)

Door location: Main entrance located at perimeter o conditioned sales area


Advantages: Relatively quick and easy; captures system interactions or a generic example

Disadvantages: Little reedom to enter site-specic inormation or capture site-specic system interactions

Introduction

NREL researchers used EnergyPlus (DOE 2011a) to evaluate the energy savings potential associated with vestibule additions

in supermarket buildings I your building is similar to the analyzed building, you can use the instructions in this section to

estimate the energy and cost savings potential

The baseline condition included a double door at the main entrance Whole-building energy savings potential was estimated

or two energy e iciency measures at this entrance:

Adding a vestibule as an upgrade without modiying the HVAC equipment

Adding a vestibule with a downsize in HVAC equipment as part o a deep retroit

The irst measure is simpler; the second enables additional savings, including a reduction in an energy


How the Instructions Were Developed or the Example Simulation

The supermarket building model is 45,000 t2 It includes a total sales area o 25,000 t2, rerigerated cases throughout the

sales area, and HVAC equipment with humidity controls The hours o typical door use are assumed to be 6:00 am to

11:00 pm The model was adapted rom the DOE Commercial Reerence Building supermarket model or new construction

(DOE 2010) Equipment eiciencies were based on the requirements in ASHRAE (2007)

Iniltration rates into the large sales area were modiied or cases with and without a vestibule to quantiy the eects o a

vestibule addition The entrance was assumed to be located at the perimeter o a sales area The results show the estimated

energy savings potential

This analysis reerenced Yuill (1996) and ASHRAE (2009) Equation A3 was used to estimate iniltration rates as discussed in

Appendix A Assumptions included a 42-t2 door area, representing a typical double door, and a pressure actor o 03, appli-

cable to buildings shorter than 50 eet (ASHRAE 2009) The average rate o door traic was assumed to be 107 people per

hour entering and exiting the building during occupied hours; this value was based on Yuill (1996), who monitored the door

use o 59 retail buildings The maximum rate o door tra ic was assumed to be 180 people per hour; this value was derived

rom an examination o door schedules used in DOE (2010) A graph o this door use schedule is shown in Figure 3

With these assumptions, the peak iniltration rate was estimated to be 4,300 cm or a door with a vestibule and 7,600 cm

without a vestibule The average iniltration rates were estimated to be 2,700 cm and 4,700 cm or a door with and without

a vestibule, respectively Appendix A provides details about how airlow coeicients were estimated

Section 3

Vestibule Additions: Leveraging an Example Simulation or Supermarkets

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2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simpliied

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example


Reerences

Appendices

VESTIBULE

ADDITIONS

D

O

O

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N

Overview

Figure 3 Rate o door trac or each hour (adapted rom DOE 2010)

Instructions

Use the ollowing steps to estimate the savings potential associated with vestibule additions or your supermarket based on

the analysis or a similar building (A worksheet is provided in Appendix F to supplement this section)

Step 1 Estimate your percent energy savings potential

Use Table 31 to estimate the annual whole-building percent energy savings potential These results were based on

whole-building energy simulations o a generalized supermarket building Choose the city with the most similar climate

(See Appendix D or a US map o the DOE climate zones and representative cities)

Table 31 Percent Energy Savings Potential or Supermarket Vestibule Additions

LocationAnnual Whole-Building Percent Energy Savings Potential or

Adding a Vestibule at One Double-Door Entrance

Climate

ZoneReerence City

Adding a Vestibule Without

HVAC Modifcations

Adding a Vestibule With

HVAC Modifcations

1A Miami, Florida 06% 64%

3B Las Vegas, Nevada 14% 17%

4C Seattle, Washington 26% 26%

5A Chicago, Illinois 37% 48%

5B Boulder, Colorado 23% 25%

7 Duluth, Minnesota 41% 44%

In humid regions such as Climate Zones 1A and 5A, the dierence between savings with and without HVAC modiication

tends to be greater than in drier regions such as Climate Zones 3B and 5B This is a consequence o dierences in humidity

and its eect on cooling energy To simpliy the comparison, the same rootop unit system type and control strategy were

used or all climate zones No changes were made or active humidity control in the humid climates In practice results may

vary or dierent systems and humidity control strategies

You should consider the ollowing details as you review the results in Table 31 Energy savings depend on design assump-

tions such as system type and size In locations with humidity issues, these assumptions signiicantly depend on the presence

or absence o humidity control In the warm-humid climate zones, or example, alternative system types (advanced direct

expansion or desiccant systems) may be installed or dehumidiication I you pursue site-speciic analyses in Step 6, you

should adjust your assumptions accordingly For new construction and deep retroit cases, you should also consider reducing

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2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simplified

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example

1Option A:

Simplified

Method

Reference

Appendice

Overview

the system size i a reduction in iniltration reduces the HVAC load The ability to downsize will depend on the magnitude o

load reduction and the available sizes o HVAC equipment Reducing the system size can enable additional savings, including

a reduction in an energy


Use Equation 31 to estimate the energy savings potential associated with a vestibule addition or your supermarket Enter

the annual whole-building percent energy savings potential identiied rom Step 1, as well as your stores measured annual

whole-building energy use (MMBtu)

Esavings = E%savings Etotal (31)

where:


E%savings = percent whole-building energy savings potential (%)

Etotal = current measured annual whole-building energy use (MMBtu)


Use Table 32 to identiy the appropriate cooling and heating raction multipliers that correspond to your location and

the time that your door is typically in use Choose the city with the most similar climate (See Appendix D or a US map o

the DOE climate zones and representative cities) The multipliers relect the proportion o energy savings potential that isattributable to cooling or heating energy savings

Assuming Esavings is positive in Step 2, a positive cooling (or heating) raction multiplier in Table 32 indicates that the

proposed strategy will reduce the cooling (or heating) load



Table 32 Entrance Cooling (MCLG) and Heating (MHTG) Fraction Multipliers or Vestibule Equations

LocationEntrance Cooling and Heating Fraction Multipliers

or Example Case(With Entrance Operating Hours o 6:00 a.m. to 11:00 p.m.)Climate Zone Reerence City

1A Miami, FloridaMCLG 100

MHTG 000

3B Las Vegas, NevadaMCLG 033

MHTG 067

4C Seattle, WashingtonMCLG 005

MHTG 105

5A Chicago, IllinoisM

CLG000

MHTG 100

5B Boulder, ColoradoMCLG 001

MHTG 101

7 Duluth, MinnesotaMCLG 002

MHTG 102

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2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simpliied

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example


Reerences

Appendices

VESTIBULE

ADDITIONS

D

O

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N

Overview







Csavings = Esavings (1000/341 MCLG CCLG + 10 MHTG CHTG) (32)where:












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AppendiceAppendiceAppendiceAppendiceAppendice

2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simplified

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example

1Option A:

Simplified

Method

Reference

Appendice

Overview

17


Building type: Free-standing retail buildings Equations are provided or 10 climate zones

How the door is used:The door is let open or extended periods

Door location: At the perimeter o a conditioned space



Disadvantages: Little reedom to enter site-specic inormation; does not capture system interactions

Introduction

Door operation measures can include changes to when or how long the doors are open and changes to the eective door

area These measures may be applied to customer doors used or large item pickups, or to shipping and receiving doors

used by retailers and their product distributors This section provides a simpliied method or estimating the energy and cost

implications associated with alternative door operation

Appendix B provides details about how the steps and equations in this section were developed

Instructions

Use the ollowing steps to estimate the energy and cost savings potential associated with alternative door operation

(A worksheet is provided in Appendix G to supplement this section)

Step 1 Select an area-normalized climate actor

The area-normalized climate actor is a user input or Equation 41 This input accounts or variations in iniltration rate by

climate, and is normalized by door area Use Table 41 to select the appropriate actor or your location Choose the city with

the most similar climate (See Appendix D or a US map o the DOE climate zones and representative cities)

Example: A retail building is located in Portland, Oregon. The building owner uses Appendix D and Table 41 to determine that Seattle,Washington, has the most similar climate as it is in the same climate zone. The owner selects the Climate Zone 4C value, FCA = 0.943.

Table 41 Area-Normalized Climate Factors (FCA)

LocationArea-Normalized Climate Factors, FCA

(MMBtuday/h/t2)Climate Zone Reerence City


2A Houston, Texas 0271

3A Atlanta, Georgia 0460


4A Baltimore, Maryland 0886




6A Minneapolis, Minnesota 1753


Section 4

Door Operation Changes: Simpliied Method

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2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simpliied

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example


Reerences

Appendices

VESTIBULE

ADDITIONS

D

O

O

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PERATIO

N

Overview

Step 2 Identiy a time-o-day multiplier

I you know your door is typically let open within speciic timerames, you can use the time-o-day multipliers in Table 42

to adjust your estimate Otherwise, assume a time-o-day multiplier o 1 The dierences between the average outdoor and

indoor temperatures or the speciied timerames were used to develop multipliers Multipliers are provided or various

climate zones Choose the city with the most similar climate (See Appendix D or a US map o the DOE climate zones and

representative cities)

Example: A retail building in Portland, Oregon, has a door that is typically left open for two 30-minute delivery periods each day.

Both usually occur between 5:00 a.m. and 8:00 a.m.

The building owner uses Appendix D and Table 42 and observes that Seattle, Washington, has the most similar climate as it is in thesame climate zone. The owner also notes that the probable delivery window (5:00 a.m. to 8:00 a.m.) overlaps two timeframes in the

table: 12:00 a.m. to 6:00 a.m., and 6:00 a.m. to 12:00 p.m. The time-of-day multipliers for these timeframes are 1.33 and 0.97, respectively

Option 1: The owner could calculate a simple average of 1.33 and 0.97 to yield MT= 1.15 for this case.

Option 2: The owner could calculate a weighted average. One third of the probable delivery window falls between 12:00 a.m. and

6:00 a.m.; t wo thirds falls between 6:00 a.m. and 12:00 p.m.; so the weighted average is M T= 1.33 (1/3) + 0.97 (2/3) = 1.09.

(If this example were continued into Step 4, HCin Equation 41 would be the total duration of all periods when the door is left open;

with two half-hour delivery periods each day, HCwould equal one hour per day.)

Table 42 Time-o-Day Multipliers (MT) or Door Operation Equations

Location Timerame Within Which Open-Door Periods Occur

ClimateZone

Reerence City12:00 a.m. to

6:00 a.m.6:00 a.m. to12:00 p.m.

12:00 p.m. to6:00 p.m.

6:00 p.m. to12:00 a.m.

1A Miami, Florida 012 114 195 080

2A Houston, Texas 151 114 017 117

3A Atlanta, Georgia 147 106 058 088

3B Las Vegas, Nevada 137 096 046 121

4A Baltimore, Maryland 131 098 065 106

4C Seattle, Washington 133 097 070 099

5A Chicago, Illinois 117 096 082 105

5B Boulder, Colorado 140 090 064 106

6A Minneapolis, Minnesota 116 100 085 099

7 Duluth, Minnesota 116 100 081 103

Step 3 Identiy your current and proposed strategies

Identiy your current door operation strategy and propose an alternative

Estimate the average hours per day the door is let open or your current strategy and or a proposed alternative strategy

Estimate the eective door area or your current strategy and or a proposed alternative strategy The eective door area

is deined as ollows:

I the door is partially open, as can be the case with an overhead door, the eective door area is the uncovered

proportion o the doorway

I a door has an additional covering, such as a strip door curtain, its e ective door area can be assumed to be equal to

the percent iniltration reduction caused by the additional covering, multiplied by the total door area

Consult manuacturers or estimates o how much their products will reduce iniltration rates or your scenarios

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2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simplified

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example

1Option A:

Simplified

Method

Reference

Appendice

Overview

Example: A retailer has a 42-ft2 door with a plastic strip door curtain separating a conditioned space from the outdoor

environment. The manufacturer claims the curtain will reduce infiltration rates by X% for this kind of application. The

retailer could assume that the effective door area is X% 42 ft2.

Energy eiciency strategies may include:

Instruct delivery personnel to close doors more requently This may also aect delivery time, however, so you may

irst wish to estimate energy and delivery cost impacts

Install sensor-operated quick-opening doors This may reduce the time doors are open and mitigate delivery cost

impacts

Employ partial door opening strategies You may want to use a lower deault overhead door height or most deliver-ies and switch to the maximum door height or larger deliveries Another strategy is to install curtains to reduce the

eective door area


Use Equation 41 to estimate the whole-building energy savings potential associated with your alternative door operation

The equation is written such that when Esavings is positive, the proposed strategy saves energy over the current strategy

Esavings = FCA MT (AC HC AP HP) (41)

where:


FCA = area-normalized climate actor (MMBtuday/h/t2; see Table 41)

MT = time-o-day multiplier (dimensionless; see Table 42)

AC = eective door area or current strategy (t2)

HC = hours per day door is let open or current strategy (h/day)

AP = eective door area or proposed strategy (t2)

HP = hours per day door is let open or proposed strategy (h/day)


Use Table 43 to identiy the appropriate cooling and heating raction multipliers that correspond to your location and thetime your door is typically in use Choose the city with the most similar climate (See Appendix D or a US map o the DOE

climate zones and representative cities) The multipliers relect the proportion o energy savings potential that is attributable

to cooling or heating energy savings

Assuming Esavings is positive in Step 4, a positive cooling (or heating) raction multiplier in Table 43 indicates the proposed

strategy will reduce the cooling (or heating) load



As in the example rom Step 2, i the average entrance operating hours overlap multiple timerames, a cooling raction

multiplier and a heating raction multiplier can be estimated in Step 5 by per orming either a simple average or a weighted

average o values rom applicable timerames in Table 43

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2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simpliied

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example


Reerences

Appendices

VESTIBULE

ADDITIONS

D

O

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N

Overview

20

Table 43 Entrance Cooling (MCLG) and Heating (MHTG) Fraction Multipliers or Door Operation Equations

Location Entrance

Cooling and

Heating

Fraction

Multipliers

Timerame Within Which Open-Door Periods Occur

ClimateZone

Reerence CityAll Day

(24-HourPeriod)

12:00 a.m.to

6:00 a.m.

6:00 a.m.to

12:00 p.m.

12:00 p.m.to

6:00 p.m.

6:00 p.m.to

12:00 a.m.

1AMiami,

Florida

MCLG 100 100 100 100 100

MHTG 000 000 000 000 000

2A Houston, TexasMCLG 027 012 023 100 003

MHTG 073 112 077 000 103

3AAtlanta,

Georgia

MCLG 002 004 000 015 004

MHTG 098 104 100 085 104

3BLas Vegas,

Nevada

MCLG 028 003 026 076 012

MHTG 072 103 074 024 088

4ABaltimore,

Maryland

MCLG 001 002 001 000 002

MHTG 101 102 101 100 102

4CSeattle,

Washington

MCLG 004 002 005 005 005

MHTG 104 102 105 105 105

5AChicago,

Illinois

MCLG 001 002 001 000 001

MHTG 101 102 101 100 101

5BBoulder,

Colorado

MCLG 001 001 001 000 002

MHTG 101 101 101 100 102

6AMinneapolis,

Minnesota

MCLG 001 002 001 000 002

MHTG 101 102 101 100 102

7Duluth,

Minnesota

MCLG 001 001 001 002 001

MHTG 101 101 101 102 101




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2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simplified

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example

1Option A:

Simplified

Method

Reference

Appendice

Overview





where:










Use these initial estimates to decide whether to perorm urther site-speciic analyses, engage vendors or contractors toprice retroit or new construction options, or test door operation changes Appendix C provides suggestions about how to

implement such a measure

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2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simpliied

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example


Reerences

Appendices

VESTIBULE

ADDITIONS

D

O

O

R

O

PERATIO

N

Overview

22


Building type: Free-standing retail buildings

How the door is used: The door is let open or extended periodsDoor location: Any


Advantages: Freedom to enter site-specic inormation; captures system interactions

Disadvantages: Requires more time and efort; may require external expertise

Introduction


area These measures may be applied to customer doors used or large item pickups, or to shipping and receiving doors used

by retailers and their product distributors

Engineers can use a simulation-based approach to conduct their irst assessment o an alternative door operation measure

Engineers who have already used Section 4 to conduct an initial estimate can also use this section to conduct a site-speciic

analysis beore implementing such a measure


Instructions

Use the ollowing steps to estimate the savings potential associated with alternative door operation

Step 1 Estimate your iniltration rates

An NREL whole-building energy simulation analysis examined iniltration impacts or eective door areas up to 230 t2 The

relationship between iniltration rate and eective door area was airly linear in the 0 to 230-t2 range that was examined The

230-t2 upper limit was based on Retailer Energy Alliance member eedback about the size o their largest customer doors

Use Table 51 or Equation 51, and choose the table values or the city with the most similar climate to estimate your monthly

or annual average iniltration rates (see Appendix D or a US map o the DOE climate zones and representative cities):

I you have a large door with an eective area near 230 t2, use Table 51

To estimate the iniltration rates o eective door areas smaller than 230 t2, use Equation 51

Section 5

Door Operation Changes: Simulation-Based Method

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2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simplified

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example

1Option A:

Simplified

Method

Reference

Appendice

Overview

Table 51 Inltration Rates (cm) or a 230-t2 Efective Door Area

Month

Location

1A(Miami,Florida)

3B(Las Vegas,

Nevada)

4C(Seattle,

Washington)

5A(Chicago,Illinois)

5B(Boulder,Colorado)

7(Duluth,

Minnesota)

January 31,200 19,800 26,200 33,900 25,300 36,400

February 33,400 21,400 23,100 40,400 29,400 38,000

March 36,300 26,000 27,700 35,800 28,600 39,600

April 39,600 40,300 39,100 41,700 30,500 34,100

May 32,000 27,700 29,500 29,500 27,400 31,500

June 24,500 39,200 25,000 35,700 27,200 29,900

July 29,900 29,900 26,500 26,900 22,100 27,600

August 29,600 30,100 26,200 30,700 20,100 23,500

September 22,900 20,100 28,900 27,500 23,100 32,500

October 25,200 28,100 26,800 41,100 18,300 36,300

November 36,900 19,500 34,300 33,000 26,600 35,200

December 35,600 16,300 21,400 35,100 26,200 30,600

Annual average 31,400 26,500 27,900 34,300 25,400 32,900

The equation or estimating iniltration rates o eective door areas smaller than 230 t2 is:

CFM = (A/230) CFM230 (51)

where:CFM = iniltration rate (cm)

A = eective door area (t2)

230 = reerence eective door area used to produce Table 51 values (t2)

CFM230 = iniltration rate rom Table 51 (cm)

Note that the usability o Equation 51 or doors larger than 230 t2 was not assessed

Step 2 Estimate your energy and cost savings potential

Use the iniltration rates determined in Step 1 in your own energy models to estimate the impact o iniltration on energy

consumption and cost or dierent scenarios One way to do this is to create a separate iniltration object that represents inil-tration through an open door Use other iniltration objects to represent iniltration that occurs when the door is shut This

could include iniltration through imperections in the door construction, as well as other elements o the building envelope,

such as walls, roos, and windows

For the doors iniltration object, you may need to deine an iniltration schedule that speciies iniltration rates or multiple

times o day These schedules can be used to represent when doors are open or closed For times when the door is open, use

the iniltration rate rom Step 1 as your input For times when the door is closed, set the iniltration rate to zero (or the door

iniltration object only)

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2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simpliied

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example


Reerences

Appendices

VESTIBULE

ADDITIONS

D

O

O

R

O

PERATIO

N

Overview

Once you have deined an iniltration object and schedule or your baseline scenario, you can adjust your inputs to represent

alternative scenarios Changes to inputs or the alternative scenarios may include:

Change the times when the iniltration rate is zero or nonzero to represent a modiication to when or how long the doors

are open

Change the magnitude o the nonzero iniltration rates to represent a change in the eective door area

Alternatively, some simulation applications may allow you to calculate iniltration rates rom other user inputs For example,

the EnergyPlus iniltration object allows you to speciy such inputs as the neutral pressure o the building, the door area, and

the door orientation For more details, consult the user documentation or your whole-building simulation application


Use these initial estimates to decide whether to perorm urther site-speciic analyses, engage vendors or contractors to price

retroit or new construction options, or test door operation changes in your stores Appendix C provides suggestions about

how to implement such a measure

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2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simplified

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example

1Option A:

Simplified

Method

Reference

Appendice

Overview

25


Building type: Large retail building o similar scale, use, and operation as the example in this section Results are

provided or six climate zones

How the door is used: The door is let open or extended periods

Door location: An entrance located at the perimeter o a conditioned sales area


Advantages: Relatively quick and easy; captures system interactions or a generic example

Disadvantages: Little reedom to enter site-specic inormation or capture site-specic system interactions

Introduction


area These measures may be applied to customer doors used or large item pickups, or to shipping and receiving doors used

by retailers and their product distributors

NREL researchers used EnergyPlus (DOE 2011a) to evaluate the energy savings potential associated with door operation

changes in large retail buildings Various alternative strategies were simulated or a bay door located at the perimeter o a

sales area I your building is similar to the analyzed building, you can use the instructions in this section to adapt the example

results and estimate the energy and cost savings potential or your scenarios


How the Instructions Were Developed or the Example Simulation

The large retail building model is 110,000 t2 It includes a total sales area o 87,500 t2 with no rerigerated cases This

model was created by modiying whole-building energy models developed at NREL (see the Acknowledgments section)

In this example, the building model was designed to represent a home improvement store with a bay door or customers

purchasing large items Equipment eiciencies were based on the requirements in ASHRAE (2007)Feedback rom Retailer Energy Alliance members suggested that such buildings do not requently include active humidity

controls, but that occupants may manually override deault thermostat settings i necessary to maintain comort To simu-

late this eect, the building model lowered the thermostat set point rom 74F to 72F when the dew point temperature

exceeded 57F The temperature set point was reset to 74F each day A dew point o 57F represented a threshold above

which people start to notice discomort

Table 61 provides a summary o estimated percent energy increase or an example case This depicts the energy impact o

leaving a 230-t2 door open or an average o 3 hours per day The results are provided or all climate zones that were analyzed

Table 61 Whole-Building Energy Increase or Example Door Condition

Location Whole-Building Energy Percent IncreaseBaseline: Door Is Always ClosedAlternative: 230-t2 Bay Door Is Open 3 Hours/DayClimate Zone Reerence City

1A Miami, Florida 20%

3B Las Vegas, Nevada 19%

4C Seattle, Washington 53%

5A Chicago, Illinois 78%

5B Boulder, Colorado 40%

7 Duluth, Minnesota 93%

Section 6

Door Operation Changes: Leveraging an Example Simulation or Large Retail Building

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26


2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simpliied

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example


Reerences

Appendices

VESTIBULE

ADDITIONS

D

O

O

R

O

PERATIO

N

Overview

Instructions

Use the ollowing steps to estimate the energy and cost savings potential associated with alternative door operation or large

retail buildings (without rerigerated cases) (A worksheet is provided in Appendix H to supplement this section)

Step 1 Select an energy savings actor

The energy savings actor is a user input that will be used in Equation 61 This input accounts or variations in energy savings

potential or each climate Use Table 62 to select the appropriate climate actor or your location Choose the city with the

most similar climate (See Appendix D or a US map o the DOE climate zones and representative cities)

Table 62 Energy Savings Factor (FES)

LocationEnergy Savings Factor, FES

(MMBtuday/h/t2)Climate Zone Reerence City







Step 2 Identiy your current and proposed strategies

Identiy your current door operation strategy and propose an alternative

Estimate the average hours per day the door is let open or your current strategy and or a proposed alternative strategy

Estimate the eective door area or your current strategy and or a proposed alternative strategy The eective door area

is deined as ollows:

I the door is partially open, as can be the case with an overhead door, the eective door area is the uncovered

proportion o the doorway

I a door has an additional covering, such as a strip door curtain, its e ective door area can be assumed to be equal to

the percent iniltration reduction caused by the additional covering, multiplied by the total door area

Consult manuacturers or estimates o how much their products will reduce iniltration rates or your scenarios

Example: A retailer has a 42-ft2 door with a plastic strip door curtain separating a conditioned space from the outdoor

environment. The manufacturer claims the curtain will reduce infiltration rates by X% for this kind of application. The

retailer could assume that the effective door area is X% 42 ft2.

Energy eiciency strategies may include:

Instruct delivery personnel to close doors more requently This may also aect delivery time, however, so you may

irst wish to estimate energy and delivery cost impacts

Install sensor-operated quick-opening doors This may reduce the time doors are open and mitigate delivery cost

impacts

Employ partial door opening strategies You may want to use a lower deault overhead door height or most deliver-

ies and switch to the maximum door height or larger deliveries Another strategy is to install curtains to reduce the

eective door area

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2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simplified

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example

1Option A:

Simplified

Method

Reference

Appendice

Overview


Use Equation 61 to estimate the whole-building energy savings potential associated with alternative door operation

The equation is written such that when Esavings is positive, the proposed strategy saves energy over the current strategy

Esavings = FES (AC HC AP HP) (61)

where:


FES = energy savings actor (MMBtuday/h/t2); see Table 62)

AC = eective door area or current strategy (t2)

HC = hours per day door is let open or current strategy (h/day)

AP = eective door area or proposed strategy (t2)

HP = hours per day door is let open or proposed strategy (h/day)


Use Table 63 to identiy the appropriate cooling and heating raction multipliers that correspond to your location Choose

the city with the most similar climate (See Appendix D or a US map o the DOE climate zones and representative cities) The

multipliers relect the proportion o energy savings potential that is attributable to cooling or heating energy savings

Assuming Esavings is positive in Step 4, a positive cooling (or heating) raction multiplier in Table 63 indicates that theproposed strategy will reduce the cooling (or heating) load



Table 63 Entrance Cooling (MCLG) and Heating (MHTG) Fraction Multipliers or Door Operation Equations

Location Entrance Cooling and Heating FractionMultipliers or Example Case

(With Door Let Open Between 1:00 p.m. and 4:00 p.m.)Climate Zone Reerence City

1A Miami, FloridaMCLG 100

MHTG 000

3B Las Vegas, NevadaMCLG 100

MHTG 000

4C Seattle, Washington

MCLG 006

MHTG 106

5A Chicago, IllinoisMCLG 001

MHTG 099

5B Boulder, ColoradoMCLG 001

MHTG 099

7 Duluth, MinnesotaMCLG 002

MHTG 102

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Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simpliied

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example


Reerences

Appendices

VESTIBULE

ADDITIONS

D

O

O

R

O

PERATIO

N

Overview

Step 5 Estimate your costs associated with cooling and heating







where:







1000/341 = conversion actor (kWh/MMBtu)10 = conversion actor (therm/MMBtu)


Use these initial estimates to decide whether to perorm urther site-speciic analyses, engage vendors or contractors to

price retroit or new construction options, or test door operation changes Appendix C provides suggestions about how to

implement this measure

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2Option B:

Simulation

Method

3Option C:

Leverage

Example

4Option A:

Simplified

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example

1Option A:

Simplified

Method

Reference

Appendice

Overview

29

ASHRAE (2002)ASHRAE Guideline 14-2002, Measurement of Energy and Demand Savings. Atlanta, GA: American Society o

Heating, Rerigerating and Air-Conditioning Engineers, Inc

ASHRAE (2007)ANSI/ASHRAE/IESNA Standard 90.1-2007, Energy Standard for Buildings Except Low-Rise Residential Buildings.

Atlanta, GA: American Society o Heating, Rerigerating and Air-Conditioning Engineers, Inc

ASHRAE (2009)ASHRAE Handbook: Fundamentals Atlanta, GA: American Society o Heating, Rerigerating and Air-

Conditioning Engineers, Inc

DOE (2004) Adapted rom a climate zone map developed or the US DOE and irst published in ASHRAE Standard 901-2004

Available at http://apps1eereenergygov/buildings/publications/pds/building_america/ba_climateguide_7_1pd Last

accessed December 2010

DOE (2010) Commercial Reerence Buildings www1eereenergygov/buildings/commercial_initiative/reerence_buildingshtml

DOE (2011a) EnergyPlus Energy Simulation Sotware, Version 60 Washington, DC: US Department o Energy http://apps1

eereenergygov/buildings/energyplus/

DOE (2011b) EnergyPlus Energy Simulation Sotware: Weather Data Sources http://apps1eereenergygov/buildings/energy-

plus/weatherdata_sourcescm

Haberl, JS, Culp C; Claridge, DE (2005)ASHRAEs Guideline 14-2002 for Measurement of Energy and Demand Savings: How to

Determine What Was Really Saved by the Retrofit, pp 113

Memtech (2011) Weatherstripping ~ Door Seals. Retrieved Aug 23, 2011, rom wwwmemtechbrushcom/weatherstrip/

door-weatherstrippinghtm

NBE Australia (2009) PVC Strip Door Installation Installation manual retrieved Aug 15, 2011, rom wwwnbeaustraliacomau/

Data%20Downloads/install_pvc_strip_door_sspd

PNNL (2009) Vestibule Case Study. Retrieved Aug 15, 2011, rom the Building Energy Codes Resource Center at http://resource-

centerpnlgov/cocoon/mor/ResourceCenter/article/1484

Wulingho, DR (1999) Energy Efficiency Manual. Wheaton, MD: Energy Institute Press, pp 826857

Yuill, GK (1996) Impact o High Use Automatic Doors on Iniltration Project 763-TRP, American Society o Heating,

Rerigerating and Air-Conditioning Engineers, Inc, Atlanta, GA

Reerences
http://apps1.eere.energy.gov/buildings/publications/pdfs/building_america/ba_climateguide_7_1.pdfhttp://localhost/var/www/apps/conversion/tmp/scratch_1/www1.eere.energy.gov/buildings/commercial_initiative/reference_buildings.htmlhttp://apps1.eere.energy.gov/buildings/energyplus/http://apps1.eere.energy.gov/buildings/energyplus/http://apps1.eere.energy.gov/buildings/energyplus/weatherdata_sources.cfmhttp://apps1.eere.energy.gov/buildings/energyplus/weatherdata_sources.cfmhttp://www.memtechbrush.com/weatherstrip/door-weatherstripping.htmhttp://www.memtechbrush.com/weatherstrip/door-weatherstripping.htmhttp://www.nbeaustralia.com.au/Data%20Downloads/install_pvc_strip_door_ss.pdfhttp://www.nbeaustralia.com.au/Data%20Downloads/install_pvc_strip_door_ss.pdfhttp://resourcecenter.pnl.gov/cocoon/morf/ResourceCenter/article/1484http://resourcecenter.pnl.gov/cocoon/morf/ResourceCenter/article/1484http://resourcecenter.pnl.gov/cocoon/morf/ResourceCenter/article/1484http://resourcecenter.pnl.gov/cocoon/morf/ResourceCenter/article/1484http://www.nbeaustralia.com.au/Data%20Downloads/install_pvc_strip_door_ss.pdfhttp://www.nbeaustralia.com.au/Data%20Downloads/install_pvc_strip_door_ss.pdfhttp://www.memtechbrush.com/weatherstrip/door-weatherstripping.htmhttp://www.memtechbrush.com/weatherstrip/door-weatherstripping.htmhttp://apps1.eere.energy.gov/buildings/energyplus/weatherdata_sources.cfmhttp://apps1.eere.energy.gov/buildings/energyplus/weatherdata_sources.cfmhttp://apps1.eere.energy.gov/buildings/energyplus/http://apps1.eere.energy.gov/buildings/energyplus/http://localhost/var/www/apps/conversion/tmp/scratch_1/www1.eere.energy.gov/buildings/commercial_initiative/reference_buildings.htmlhttp://apps1.eere.energy.gov/buildings/publications/pdfs/building_america/ba_climateguide_7_1.pdf

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Method

3Option C:

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Example

4Option A:

Simpliied

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example


Reerences

Appendices

VESTIBULE

ADDITIONS

D

O

O

R

O

PERATIO

N

Overview

Appendix A

Vestibule Additions: Background and Development o Equations

30

This appendix explains how the instructions in Section 1, Section 2, and Section 3 were derived The methodologies reerenc

a previous study o vestibule iniltration (Yuill 1996), Chapter 16 o the ASHRAE Handbook of Fundamentals (ASHRAE 2009), and

an analysis conducted by NREL

Derivation o Airlow Coeicients or IniltrationIn the instructions in Section 1 and Section 2, air low coeicients must be derived beore iniltration rates and related energy

savings are estimated In Section 3, your building is assumed to have similar iniltration rates, so you do not need to sepa-

rately estimate additional iniltration rates

The Yuill study provides two sets o airlow coeicients: one does not correct or the presence o a person in the doorway; th

other does This document uses the latter set o coeicients

The Yuill study also provides coeicients or multiple door types and conigurations To represent a typical baseline case and

a high-e iciency alternative, this simulation example in Section 3 uses the average value o the no vestibule options and

the most eicient o the with vestibule options There was very little variation in perormance within the no vestibule and

with vestibule categories Thereore, selection o alternative options within the scope o the Yuill study is expected to have

minimal impact on savings estimates Many other design options are possible; however, analysis o additional designs was

outside the scope o the simulation example

A second-order polynomial best-it line was used to summarize selected airlow coe icients rom the Yuill study This is

provided as Equations 11 through 14 and Equations 21 through 24

Derivation o Pressure Coeicients

The methodology rom the section titled Air Leakage Through Automatic Doors in Chapter 16 o ASHRAE (2009) was used

to derive the pressure coeicients in Section 1 and Section 2 The methodology involves calculating a local wall pressure

coeicient, CS, or low-rise buildings This is then used to ind the local wind pressure coeicient, CP These values vary with

wind angle, so Table 11 and Table 21 provide two options: CP equals 070 when the absolute value o CS is at its maximum

value o about 05; CP equals 045 when the absolute value o CS is about 025 The values also assume that or low-rise retail

buildings, stack eect would be negligible relative to wind pressure

For a more precise estimate, consult ASHRAE (2009)

Derivation o Factors and Multipliers

Depending on whether you choose the methodology o Section 1, Section 2, or Section 3, intermediate actors and

multipliers may be needed to complete energy savings estimates The derivation o these actors and multipliers is

explained below

Equation A1, adapted rom ASHRAE (2009), was the basis o additional equations in this document

Q = 108 CFM T (A1)

where:

Q = iniltration load (Btu/h)

CFM = iniltration rate (cm)

T = indoor-to-outdoor temperature dierence (F)

108 = conversion actor (Btu/h/cm/F)

The conversion actor o 108 assumes the density o air is 0075 (lb/t3) and the speciic heat o air is 024 (Btu/lb/F)

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3Option C:

Leverage

Example

4Option A:

Simplified

Method

5Option B:

Simulation

Method

6Option C:Leverage

Example

1Option A:

Simplified

Method

Reference

Appendice

Overview

Equation A1 can be rearranged to calculate an iniltration load, LFN, which is normalized by the low rate o in iltration as

shown in Equation A2:

LFN = 108 T (A2)

where:

LFN = low-normalized iniltration load (Btu/h/cm)

T = monthly average indoor-to-outdoor temperature dierence (F)

108 = conversion actor (Btu/h/cm/F)

Indoor-to-outdoor temperature dierences, T, were calculated by reerencing data rom Typical Meteorological Year Version2 (TMY2) weather data iles (DOE 2011b) These iles provide monthly average temperatures or each hour o the day

The low-normalized iniltration load or a given time period can then be translated into a low-normalized HVAC power

requirement, PFN, using assumptions or HVAC system eiciency in Equation A3:

PFN = LFN/(COP or ) (A3)

where:

PFN = low-normalized HVAC power requirement (Btu/h/cm)

LFN = low-normalized iniltration load (Btu/h/cm)

COP = coeicient o perormance (dimensionless)

= heating eiciency (dimensionless)

A low-normalized climate actor, FCF, can then be calculated using the low-normalized HVAC power requirement

FCF = PFN D 106 (A4)

where:

FCF = low-normalized climate actor (MMBtuday/h/cm)

PFN = low-normalized HVAC power requirement (Btu/h/cm)

D = number o days in analysis period (days)

To account or seasonal variations in outdoor temperature, monthly average low-normalized climate actors were calculated

or each month o a typical year The monthly values were then summed to produce an annual average

For the methodology o Section 1, Table 12 provides the annual average low-normalized climate actors or each o theanalyzed climate zones I you know your door typically opens and closes within speciic timerames, you can use the time-o-

day multipliers in Table 13 to adjust your estimate TMY weather data were used to derive these multipliers, excluding data

rom hours outside the applicable time-o-day ranges

The cooling and heating raction multipliers in Table 14 and Table 32 relect the proportion o energy savings potential

that is attributable to cooling energy savings or heating energy savings These are annual values, so they take into account

seasonal changes The breakdown depends on the proportion o time iniltration contributes to the cooling or heating load

and depends on HVAC system eiciencies In this analysis, the ollowing eiciencies were assumed based on requirements in

ASHRAE Standard 901-2007:

Cooling system COP o 37

Natural gas heating system eiciency o 80%

To represent typical, generic retail building conditions, the balance point temperature was assumed to be 55F, and theaverage indoor temperature was assumed to be 71F Outdoor temperature assumptions were based on TMY data

The cooling and heating raction multipliers

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