Reference

V

NBS

Publications

U.S. DEPARTMENT

OF COMMERCE

National Bureau

of Standards

Center for Building

Technology

National Engineering

Laboratory

AlllDb EST7DM

NBSIR 81-2380

Economics and

Energy Conservation

in the Design of

New Single-Family

Housing

August 1981

NBSIR 81-2380

ECONOMICS AND ENERGY CONSERVATION IN THE

DESIGN OF NEW SINGLE-FAMILY HOUSING

ATIOHAL i(URKA«

09 tTAKDAKUS

UBSAAT

m i? 1982

mot f> c

Citt -

/ ! <p3

Id >r

Stephen R. Petersen

U S. DEPARTMENT OF COMMERCE

National Bureau of Standards

National Engineering Laboratory

Center for Building Technology

Building Economics and Regulatory Technology Division

Washington, DC 20234

August 1981

Prepared for The Department of Energy and

The Department of Housing and Urban Development

Washington, DC

U.S. DEPARTMENT OF COMMERCE, Malcolm Baldrige, Secretary

NATIONAL BUREAU OF STANDARDS, Ernest Ambler, Director
> '
ABSTRACT

This report Investigates the extent to which certain energy conservation

modifications to the envelope design of a new, single-family house are economically justified for a wide range of climates and projected energy costs. The

report provides background information on those factors that give rise to space

heating and cooling loads in buildings and examines in greater detail than in

previous reports the thermal interdependencies within and among envelope com- ponents that can greatly affect heating and cooling loads. Economic criteria

for determining a minimum life-cycle cost building envelope design are formulated and a priority-ranking method is developed to assist in the calculation

of these designs. An expanded version of the NBS Load Determination Program

is used to calculate the annual heating and cooling requirements and maximum

heating and cooling loads for a 1200 square foot, wood-frame house having a wide range of thermal improvements in 14 geographic locations. The report also

provides a methodology for interpolating these results to climatic conditions

other than the 14 analyzed. The analysis demonstrates that the optimal envelope design configuration varies over a wide range depending on climate, energy

costs, and modification costs.

Keywords: Architecture, building design, cost-benefit analysis, economics,

energy conservation, housing, insulation, space heating and cooling.

iii
PREFACE

This report is one of a series documenting NBS research and analysis efforts in

developing energy and cost data to support the Department of Energy/National

Bureau of Standards Building Energy Conservation Criteria Program. The work

reported in this project was performed under the Building Energy Performance

Criteria project and supported by Task Order A008-BCS under DoE/NBS Interagency

Agreement No. EA 77A 01-6010.

iv
ACKNOWLEDGMENTS

The author wishes to acknowledge the considerable assistance of Jim Barnett,

who set up and ran all of the NBSLD analyses used in this report. In addition,

appreciation is extended to Kim Barnes, Madeleine Jacobs, Belinda Collins, Carl

Muehlhouse, and Harold Marshall, who provided valuable comments in reviewing

the manuscript. Thanks are also due to the Word Processing Unit for typing the

many drafts and the final report.

V
TABLE OF CONTENTS

Page

ABSTRACT iii

PREFACE iv

ACKNOWLEDGMENTS v LIST OF TABLES ix

LIST OF FIGURES xll

EXECUTIVE SUMMARY xili

SI CONVERSION xvi

1. INTRODUCTION 1

1.1 Purpose and Scope 2 1.2 Organization 4

2. ENVELOPE DESIGN TO CONSERVE ENERGY: TECHNICAL ASPECTS 5

2.1 Basic Definitions 5 2.2 Fundamentals of Heat Transfer in Buildings 6

2.2.1 Thermal Conduction 6

2.2.2 Air Exchange 7 2.2.3 Radiation 7 2.2.4 Radiation Exchange and Convection 8

2.3 Space Heating and Cooling Loads 8

2.3.1 Space Heating Loads 9

2.3.2 Space Cooling Loads 10

2.4 Design Strategies for Reducing Heating and Cooling

Requirements 11

2.4.1 Space Heating Requirements 11

2.4.2 Space Cooling Requirements 11

2.4.3 Inconsistencies in Design Strategies 12

2.5 Interdependence Within and Among Building Components 13

2.5.1 Interdependence Within Envelope Components 13

2.5.2 Interdependence Among Envelope Components 13

2.5.3 Interdependence Between Space Heating and

Cooling Loads and Equipment Efficiency 15

3. ENVELOPE DESIGN TO CONSERVE ENERGY: ECONOMIC ASPECTS 16

3.1 Economic Analysis In Building Envelope Design 16

3.2 Economic Optimization In Envelope Design 18

vl
TABLE OF CONTENTS (cont'd.)

Page

3.2.1 Life-Cycle Cost Considerations in New

Housing Design 18

3.2.2 Evaluation of Future Costs and Savings 20

3.2.3 Envelope Design Optimization Criteria 23

3.3.4 Priority Ranking to Determine the

Incremental Savings Resulting from Component

Modifications 27

4. ENVELOPE CONFIGURATION AND MODIFICATIONS ANALYZED 31

4.1 Prototype Ranch House: Description and Operational

Assumptions 31

4.2 Design Modifications to Reduce Space Heating and

Cooling Requirements 41

4.2.1 Building Shape and Orientation 41

4.2.2 Window Orientation and Sizing 41

4.2.3 Insulation 42

4.2.4 Multiple Glazing 44

4.2.5 Doors 44

4.2.6 Modification Cost Data 46

5. LOAD ESTIMATING METHODOLOGY 48

6. THERMAL ANALYSIS AND PRIORITY RANKING OF ENVELOPE

MODIFICATIONS 56

6.1 Priority Ranking of Envelope Modifications 56

6.2 Results of Thermal Analysis 59

6.2.1 Heating and Cooling Requirements 59

6.2.2 Maximum Hourly Heating and Cooling Loads 69

6.2.3 Window and Wall Design by Orientation 72

6.2.4 Relative Sources of Envelope Component

Performance 84

6.2.5 Effect of House Size on Component Performance 84

7. ADJUSTMENTS FOR CLIMATE VARIATIONS 90

7.1 Interpolation of Annual Heating and Cooling Requirements . 90

7.2 Interpolation of Changes in Annual Heating and Cooling

Requirements 97

8. LIFE-CYCLE COST ANALYSIS OF SELECTED ENVELOPE MODIFICATIONS ... 105

8.1 Calculation of Present-Value, Life-Cycle Savings 105

8.2 Calculation of Present-Value, Life-Cycle Costs 107

8.3 Calculation of Optimal Envelope Component Modifications .. 110

vii
TABLE OF CONTENTS (cont'd.)

Page

9. SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS FOR FURTHER

RESEARCH 119

9.1 Summary 119

9.2 Conclusions 119

9.3 Recommendations for Further Research 120

REFERENCES 123

APPENDIX A - Selected Factors for Life-Cycle Costs Analysis ....... A-1

APPENDIX B - Estimating Present-Value Life-Cycle Property Tax

and Insurance Costs B-1

APPENDIX C - Long-Term Heating Degree Day and Cooling Degree

Hour Data C-1

viil
LIST OF TABLES

Page

2.1 Change in Time-Rate of Heat Transmission (U) Through

Alternative Frame Wall Systems Due to Insulated Siding 14

3.1 Discounting Formulas 21

4.1 Component Areas of 1200 Square Foot Prototype House 34

4.2 Basic Construction Details of Prototype House 35

4.3 Hourly Lighting, Equipment, and Occupant Heat Release Schedule .. 39

4.4 Alternative Component Designs and Corresponding U-Values

(Winter Design) 43

4.5 Alternative Wall Construction Methods to Increase Insulation

Above R-11 45

4.6 Envelope Modification Costs 47

5.1 Sample Output from NBSLD-XO 50

6.1 14 Selected Cities, TRY Reference Year, and Degree Days Used

in Thermal Analysis 57

6.2 Ranking of Modifications 58

6.3 Annual Heating Requirements by City and Cumulative Modification

Level 60

6.4 Reduction in AHR by City and Incremental Modification 63

6.5 Reduction in AHR per Dollar of Initial Cost by City and

Incremental Modification 64

6.6 Annual Cooling Requirements by City and Cumulative Modification

Level 65

6.7 Reduction in ACR by City and Incremental Modification 67

6.8 Reduction in ACR per Dollar of Initial Cost by City and

Incremental Modification 68

6.9 Annual Heating Hours Calculated for 1200 Ft^ House in

Selected Cities With Night Setback 70

6.10 Annual Cooling Hours Calculated for 1200 Ft^ House in Selected

Cities 71

ix
LIST OF TABLES (cont.d)

Page

6.11 Maximum Heating Loads for Selected Prototype Variations by

City a 73

6.12 Maximum Cooling Loads for Selected Prototype Variations by

City a 73

6.13 Annual South-Facing Window Heat Transfer During Heating Load

Hours: House H4 With Night Setback 79

6.14 Annual South-Facing Window Heat Transfer During Heating Load

Hours: House HlO With Night Setback 79

6.15 Effect of Change in South-Facing Glass Area on Annual Heating

Requirements : House HlO With Night Setback 80

6.16 Annual South-Facing Window Heat Transfer During Cooling Hours:

House HlO ..................o............................. ....... 81

6.17 Annual Wall Heat Loss During Heating Hours: House HlO 85

6.18 Annual Wall Heat Gain During Cooling Hours: House HlO 85

6.19 Relative Sources of Heat Loss During Heating Hours 86

6.20 Relative Sources of Heat Gain During Cooling Hours (Iq tj^) .... 87

6.21 Latent Cooling Requirements for All House Variations 88

7.1 TRY Heating Degree Days to Selected Bases 91

7.2 Best Linear Regression Results: Heating Degree Days and Annual

Heating Requirements 92

7.3 TRY Cooling Degree Days to Selected Bases 95

7.4 Best Linear Regression Results: Cooling Degree Days and

Annual Sensible Cooling Requirements 95

7.5 TRY Cooling Degree Hours to Selected Bases 98

7.6 Best Linear Regression Results: Cooling Degree Hours and

Annual Sensible Cooling Requirements 98

7.7 Best Linear Regression Results: Heating Degree Days and

Reductions in Annual Heating Requirements 101

7.8 Best Linear Regression Results: Cooling Degree Hours and

Reductions in Annual Cooling Requirements 101

X
LIST OF TABLES (cont’d.)

Page

7.9 Incremental Reduction in AHR (1000 Btu/ft^) by Modification

and HDD50 ^02

7.10 Incremental Reduction in ACR (1000 Btu/ft^) by Modification

and CDH77^5 103

8.1 Calculation Procedures for Incremental Savings 108

8.2 Calculation Procedures for Incremental Costs Ill

8.3 Example Solution of Optimal Component Modifications 113

8.4 Representative Assumptions for Selected Values of Fj (Heating) .. 114

8.5 Representative Assumptions for Selected Values of F 2 (Cooling) .. 115

8.6 Optimal Component Specifications for Selected Values of Fj ...... 116

8.7 Optimal Component Specifications for Selected Values of Fj^

and F2 117

A-1 Present-Value of Mortgage Payments per $1000 Borrowed A-2

A-2 Present-Value of Interest Pa3nnents per $1000 Borrowed A-3

A-3 Modified Uniform Present Worth Factors A-4

A-4 Unit Energy Prices (Metered) and Corresponding Price per Million

Btu Output from Furnace A-5

A-5 Selected kWh Prices and Equivalent Output Price per Million

Btu for Selected Central Air Conditioner Efficiencies A-6

B-1 Present Value Factors for Estimating Future Property Taxes

and Insurance Costs B-4

B-2 Residential Property Tax Rates in Selected Large Cities B-5

C-1 Long-Term Cooling Degree Hour Data for Selected Cities and

Calculation Bases C-5

xi
LIST OF FIGURES

Page

3.1 Super-Insulated Single-Family House Built by NAHB Research

Foundation 17

4.1 Front and Rear Elevations of Prototype House 32

4.2 Floor Plan of Prototype House 33

4.3 Infiltration Rate Schedule (Air Changes Per Hour) 38

4.4 Hourly Internal Loads Assumed in the Prototype House

Simulation 40

6.1 Annual Heating Requirements as Reduced by Energy Conserving

Modifications in Selected Cities 61

6.2 Annual Cooling Requirements (to > t^) As Reduced by Energy

Conserving Modifications in Selected Cities 66

6.3 Maximum Heating Load as Reduced by Energy Conserving

Modifications in Selected Cities (With Night Setback) 74

6.4 Maximum Cooling Load as Reduced by Energy Conserving

Modifications in Selected Cities 75

6.5 Annual Heating Requirements as a Function of Maximum Heating

Loads ......... ....................................... ........... 76

6.6 Annual Cooling Requirements as a Function of Maximum Cooling

Loads ................ ............................... ............ 77

7.1 Annual Heating Requirements as a Function of HDD55 and HDD55

(H-4 House) 94

7.2 Annual Sensible Cooling Requirements as a Function of CDD55

and CDD72.5 House) 96

7.3 Annual Sensible Cooling Requirements as a Function of CDH55

and CDH72,5 (H-4 House) 99

C-1 Normal Seasonal Heating Degree Days — Base 65°F C-1

C-2 Normal Seasonal Heating Degree Days — Base 60°F C-2

C-3 Normal Seasonal Heating Degree Days — Base 55°F C-3

C-4 Normal Seasonal Heating Degree Days — Base 50°F C-4

xii
EXECUTIVE SUMMARY

The energy savings and economic value of making energy conservation improvements

to existing housing have been well documented since the oil embargo of 1973-1974.

An NBS report published at that time, Retrofitting Existing Housing for Energy

Conservation; An Economic Analysis , provided the first systematic analysis of

the costs and benefits of some of these conservation measures — insulation,

storm windows, and weatherstripping — for a wide range of climates and energy

prices. An important part of that study was determining the optimal usage of

such measures from the standpoint of life-cycle costs. The study showed that,

in general, homeowners could economically justify a much higher level of investment in energy conservation measures in existing housing than was indicated by

industry, utility, consumer group, or government recommendations. The conclusions of that earlier NBS study are reflected in many current energy

conservation recommendations for existing housing.

Similar implications can be drawn for new housing as well. By incorporating a number of energy conserving features into the building envelope design, prior

to construction, the requirements for space heating in new single family residences can be reduced dramatically relative to those of most existing residences

and unmodified new housing. These features begin with the increased use of

attic, wall, and floor insulation; multiple glazing; and measures to reduce air

infiltration. Additional design features include improved thermal storage capability; the shape and orientation of the house as well as the internal location

of living areas; and the size, orientation, and management of windows. Cooling

requirements can also be reduced substantially at the design stage, primarily

through attic insulation, increased thermal mass, solar shading devices, and

whole-house ventilation.

This report investigates the extent to which certain building envelope design

modifications, primarily related to increased use of insulation and multiple

glazing, are economically justified for the range of climates found in the

United States and for a wide range of projected energy costs.

To carry out this analysis, economic criteria for determining the minimum

life-cycle cost envelope design are formulated. Considerable attention is given

to describing the interdependent relationships between and within the building

components. A methodology, called "priority ranking," is developed to determine

the incremental savings resulting from component modifications. The incremental

reductions in heating and cooling requirements resulting from each successive

modification are calculated based on the assumption that all the higher

priority — that is, more cost-effective modifications — have been made. This

approach has certain limitations, which are discussed, but it offers a reasonably accurate methodology for determining the optimal levels of thermal

resistance in the envelope components.

The priority ranking methodology was used to develop estimates of optimal

envelope component configurations for 14 geographic locations and four heating

types in each of these locations. The guidelines that are developed also take

into account construction costs and financial investment criteria relevant to

homeowners

xili
This report represents a significant advance over previous work of a similar

nature because the heating and cooling requirements and reductions in those

requirements resulting from the modifications were estimated using a dynamic

load determination program, NBSLD, instead of steady-state methods and aggregate climatic data. Actual hourly climatic data for each location examined

were utilized and the results corrected for long-term climatic trends. In

addition, the thermal interdependencies among the envelope components were examined to a greater degree than in previous reports.

Results of the thermal analysis are reported in considerable detail, including

annual heating and cooling requirements, maximum heating and cooling loads,

annual heating and cooling hours corresponding to changes in the envelope

design, heat gain and loss through south-facing windows and the walls of the

four major orientations during heating and cooling hours, and latent cooling

requirements

,

A number of significant conclusions are derived from this analysis including

the following points:

1) Optimal envelope design configurations vary over a wide range depending

on climate, energy costs, and modification costs. For example, optimal

attic insulation resistances in houses with electric heat and air con- ditioning range from R-19 in Miami to R-49 in Minneapolis. If only

heating reductions are considered, optimal attic insulation levels may

be less than R-11 in locations with very mild winter climates.

2) Increasing the size of south-facing, double-glazed windows in a well

insulated house will reduce heating loads in very few locations unless

substantial internal mass is available to store the heat gained in non- heating hours and release it during subsequent heating hours, A substantial night setback of the thermostat during heating periods will

increase the relative benefits of large south-facing windows compared

to a uniform day-night thermostat setting,

3) The orientation of a house appears to have little effect on its

heating requirements if the orientation and size of its windows are not changed. Instead, the total surface area of the house is more

important. However, the orientation of the house during cooling

periods significantly affects cooling requirements; the heat gain

through north- and south-facing walls together is considerably less

than that through walls facing east and west. Moreover, orienting

windows and daily living areas toward the south side of the house

would likely have more effect on annual heating requirements than the

actual orientation of the house itself. Because the north-facing wall

loses significantly more heat than the south-facing wall, serious con- sideration should be given to improving its thermal characteristics

relative to those of the other walls in climates where heating loads

predominate.

xlv
4) Modified heating degree day and cooling degree hour data can provide

a useful and relatively accurate means of interpolating heating and

cooling (sensible) requirements to other locations based on more

precise calculations in known climates. In addition, these modified

data can be used to correct the results based on Test Reference Year

climatic data, to better reflect long-term climatic trends. These

data can provide a means for establishing improved climatic classification schemes for use in establishing energy budgets or thermal

performance guidelines for new buildings.

5) Reductions in annual heating requirements are generally more than

proportional to reductions in maximum (or design) loads. Thus, methodologies which base reductions in heating requirements on reductions

in design loads will underestimate the potential savings from envelope

design modifications. The opposite is true for reductions in annual

cooling requirements. This lack of direct proportionality may have

significant implications with respect to equipment sizing and partload operations.

Additional research is required to resolve certain technical and economic

issues and these are outlined in the report. The technical issues are related

to the ability to better quantify the effects of design changes on annual energy

requirements, including improvements that are needed in NBSLD and similar loadestimating programs. The economic issues are related to determining optimal

building designs with respect to space heating and cooling.

In summary, this report provides new insights into the economic and thermal

aspects of energy conservation in new housing design; it provides guidelines

that will be useful to homebuyers , homebuilders, architects, and utilities.

The information in this report also can provide the technical background and

data for government policies and strategies related to energy use in housing.

However, the role of government in regulating energy use in buildings can be

diminished if the general public recognizes the long-term cost advantages of

energy conservation considerations in the design of new housing.

XV
SI CONVERSION

In view of the presently accepted practice of the building industry in the

United States and the structure of the NBS Load Determination computer program

used in this report, common U.S. units of measurements have been used throughout

this report. In recognition of the position of the United States as a signatory

to the General Conference of Weights and Measures, which gave official status

to the metric SI system of units in 1960, appropriate conversion factors have

been provided in the table below. The reader interested in making further use

of the coherent system of SI units is referred to:

NBS SP330, 1972 Edition, "The International System of Units" E380-72 ASTM Metric

Practice Guide (American National Standard Z210.1).

Metric Conversion Factors

Length: 1 inch (in) = 24.4 millimeters (mm)

1 foot (ft) = 0.3048 meter (m)

Area: 1 ft2 = 0.092903 m2

Volume

Fluid Capacity:

1 ft3 = 0.028317 m3

1 gallon (gal) = 3.78541 liters (L)

Temperature

Temperature Interval:

1°F = 9/5°C + 32

1°F = 5/9°C or K

Mass

Mass per unit volume:

Mass per unit length:

Mass per unit area:

1 pound (lb) = 0.453592 kilogram (kg)

1 Ib/ft = 1.48816 kg/m

1 lb/ft2 = 4.88243 kg/m2

1 lb/ft3 = 16.0185 kg/m3

Energy:

Heat flow rate:

R~value

U-value

1 Btu = 1.05506 kilojoules (kj)

1 Btu/h = 0.293071 Watt (W)

1 Btu/(ft2)(h)(°F) = 5.67826 W/(m2)(K)

l(ft2)(h)(°F)/Btu = 0.176110(m2)(K)/W

xvi
1 . INTRODUCTION

The energy savings and economic value of making energy conservation improvements

to existing housing have been well documented since the oil embargo of 1973-1974

An NBS report published at that time. Retrofitting Existing Housing for Energy

Conservation; An Economic Analysis ,^ provided the first systematic analysis of

the costs and benefits of some of these conservation measures — insulation,

storm windows, and weatherstripping for a wide range of climates and energy

prices. An important part of that study was determining the optimal usage of

such measures from the standpoint of life-cycle cost. The study showed that,

in general, homeowners could economically justify a much higher level of investment in energy conservation measures in existing housing than was indicated by

industry, utility, consumer group, or government recommendations. The conclusions of that earlier NBS study are reflected in current NBS energy conservation

recommendations for existing housing,

Similar Implications can be drawn for new housing as well. By incorporating a number of energy conserving features into the building envelope design, prior

to construction, the requirements for space heating in new, single-family residences can be reduced dramatically relative to those of most existing residences

These features begin with the increased use of attic, wall, and floor insulation

multiple glazing; and measures to reduce air infiltration. Additional design

features include improved thermal storage capability; the shape and orientation

of the house as well as the internal location of living areas; and the size,

orientation, and management of windows.

Cooling requirements can also be reduced substantially at the design stage,

primarily through attic insulation, increased thermal mass, solar shading

devices, and whole-house ventilation. Several studies have examined some or all of these potential conservation features and have generally concluded

that their increased use is warranted from both a conservation and economic

standpoint ,3

Initially, design improvements to reduce energy requirements in new housing will

have a smaller impact on total national energy consumption than modifications

1 S. Petersen, Retrofitting Existing Housing for Energy Conservation; An

Economic Analysis, BSS 64, National Bureau of Standards, Washington, D.C.,

1974.

2 For example, see; M, Jacobs and S. Petersen, "Making the Most of Your Energy

Dollars in Home Heating and Cooling," NBS Consumer Information Series 8,

National Bureau of Standards, Washington, D.C., 1975.

3 For example see; J. C, Moyers, The Value of Thermal Insulation in

Residential Construction; Economics and the Conservation of Energy , U.S,

Atomic Energy Commission, Oak Ridge National Laboratory, 1971; Residential

Energy Consumption, Single-Family Housing (Final Report), HUD-PDR-29-2

,

Hittman Associates, Inc., Columbia, MD, 1975; and S. Petersen, Retrofitting

Existing Housing for Energy Conservation,

1
to existing housing because, currently, the proportion of existing housing to new housing is greater. But by the end of this century, nearly one-third of

the housing in the United States will have been constructed since the oil

embargo of 1974,1 go that the impact of conservation in new housing in response

to higher energy prices will be substantial.

In addition, there is a substantially greater potential for reducing heating

and cooling enerey requirements in new housing compared to existing housing.

From an economic viewpoint, the useful life over which conservation costs can

be amortized is often longer for new housing and these additional costs can generally be included in a long-term mortgage. From a technical viewpoint, the

design opportunities to reduce energy use are more varied. For example, structural modifications which would be prohibitively expensive to make in existing

housing can often be made at a relatively small cost increase in new housing.

Structural modifications allow greater capacity for insulation in walls, ceilings, and floors; better window designs and less expensive methods for triple

glazing; tighter construction to reduce air leakage; better locations for ductwork; more efficient heating and cooling equipment; and better zoning of

interior areas.

1.1 PURPOSE AND SCOPE

With these considerations in mind, the primary purpose of this report is to

investigate the extent to which certain building envelope design improvements,

especially those which involve increased costs at the time of construction, are economically justified on a life-cycle basis for the range of climates found

in the United States and for a wide range of projected energy costs. Energy

conservation guidelines are developed which take into account climate, energy

costs, construction costs, and financial investment criteria relevant to homeowners. Such guidelines can be of considerable help to homebuyers , homebuilders, architects, and utilities. This information also can provide the

technical background and data for government policies and strategies related to

energy use in housing. It is hoped, however, that the role of government in

regulating energy use in buildings can be diminished if builders and homebuyers

recognize the long-term cost advantage of increased energy conservation

considerations in the design of new housing,

A secondary purpose of this report is to demonstrate the fundamental economic

relationship between energy conservation and energy consumption in building

design. This relationship is established by using life-cycle cost analysis as

a tool in the actual design process. Life-cycle cost considerations are systematically incorporated into the design process to determine design configurations that minimize life-cycle costs. This requires detailed knowledge of both

the economic and technical interrelationships that characterize energy use in

buildings, not only for the building as a whole, but for each of its energyrelated components.

1 Data Resources, Inc,, Energy Review, Lexington, MA, Winter 1980-81.

2
The economically optimal envelope designs developed in this report with respect

to heating and cooling loads are based on a 1200 square-foot, single-family,

ranch-style house. However, the conclusions of this report with respect to

optimal insulation levels and multiple glazing are generally valid for a wide

range of wood-frame house sizes. Guidelines for Insulation in masonry walls of

single-family houses are reported separately.

The National Bureau of Standards Load Determination (NBSLD) program is used to

analyze the heating and cooling loads corresponding to the various design alternatives examined in this report. NBSLD simulates the hourly dynamic thermal

response of the building envelope and provides results that are sensitive to

solar gains, internal heat release, occupancy schedules, air Infiltration and

hourly climate data. In addition, NBSLD makes it possible to model interdependent relationships among the envelope components in a manner not generally

possible with less sophisticated approaches to load calculation.

The cost data used in the analysis were provided under contract in 1977 by a source close to the housing construction industry, the NAHB Research Foundation.

These data were adjusted to reflect increases in construction costs to 1979, the

year in v/hich the major part of this report was completed.

Annual heating and cooling requirements corresponding to a wide range of design

modifications and climate conditions are included in addition to calculations

of actual energy savings. Eventually this type of data may prove useful in

the development of "energy budgets" to be used in performance criteria for new

housing.

Basically, the report emphasizes the design of the thermal envelope of a conventional dwelling unit. Although the report does not consider design alternatives for heating, ventilating and air conditioning (HVAC) equipment, the

effect of the seasonal efficiency of such equipment on both annual energy use

and the economically optimal envelope design is an important element in the

analysis. The report does not deal with optimal envelope configurations that

incorporate solar heating and cooling equipment, although some implications

for passive solar designs are discussed. Nor does this report investigate

window management techniques or daylighting schemes that can be incorporated

into the envelope design.

1 See S. Petersen, K. Barnes and B. Peavy, Determining Cost-Effective

Insulation Levels for Masonry and Wood-Frame Walls in New Single-Family

Housing , BSS 134, National Bureau of Standards, Washington, D.C, 1981.

2 The NAHB Research Foundation is a wholely owned subsidiary of the National

Association of Home Builders.

^ Advanced versions of the NBSLD computer program needed for the dynamic

analysis of daylighting and window management schemes were not available

at the time this report was prepared. Since that time a new version of

NBSLD that incorporates daylighting analysis has been developed. See

T. Kusuda , NBSLD, The Computer Program for Heating arid Cooling Loads in

Buildings , (Revised) NBSIR - Draft Report, National Bureau of Standards,

Washington, D.C., April 1981.

3
1 . 2 ORGANIZATION

The report begins with section 2, which provides background information on those factors which give rise to space heating and cooling loads in buildings.

This section describes the fundamental principles of heat transfer through the

building envelope and the interdependent relationships within and among envelope

components that affect heating and cooling loads. Performance guidelines for

designing a more energy-efficient building envelope are outlined. In section

3, the economic criteria for determining the minimum life-cycle cost envelope

design are formulated. A priority ranking method to assist in the calculation

of the minimum life-cycle cost design is developed. Section 4 describes the

prototype single-family, detached house used in the thermal analysis and the

modifications to reduce conductive heat transfer through the building envelope

that are analyzed.

In section 5, the expanded output version of the NBSLD program is described.

Section 6 discusses the results of the thermal analysis in some detail. These

results include data for 14 different locations throughout the United States.

These locations were selected because they cover a wide range of climates and,

hence, heating and cooling requirements. Section 7 correlates the heating and

cooling requirement data for the prototype house with aggregate climatic data.

This provides a basis for interpolating the results of the thermal analysis to

other locations. In section 8, the economic assumptions used to estimate the

A generalized

change these

and

cost effectiveness of the modifications considered are discussed,

computational methodology is presented which allows the reader to

assumptions to better reflect specific requirements. Conclusions

recommendations for further research are discussed in section 9.

4
2. ENVELOPE DESIGN TO CONSERVE ENERGY: TECHNICAL ASPECTS

In this section, the basic terminology and concepts necessary for understanding

how building design affects space heating and cooling requirements are defined.

Design strategies for reducing such requirements are then examined. Lastly,

this section describes the interdependencies between building envelope components and explains how these interdependencies affect heating and cooling

loads

2.1 BASIC DEFINITIONS

Buildings are designed to satisfy a large number of performance objectives,

ranging from providing basic shelter to expressing personal aesthetic preferences. One of the most basic performance objectives for an occupied building

is providing thermal comfort. This report shows how this objective can be

satisfied at minimum life-cycle cost, while simultaneously satisfying the other

building performance criteria imposed by the occupant.

Thermal comfort has been defined from a physiological viewpoint as that state

of mind which expresses satisfaction with the thermal environment.^ In general,

the major determinants of thermal comfort in buildings are clothing, activity

of occupants, dry-bulb air temperature, relative humidity, air movement, and

mean radiant temperature. The first two factors are controlled entirely by the

occupant; the last four depend largely on the overall building design and the

mechanical heating and cooling systems within, although these may be controlled

to some extent by the building occupants.

Space heating or cooling loads occur when the HVAC equipment must be operated

in order to satisfy minimum thermal comfort requirements. Generally, the

controls for HVAC equipment in houses are sensitive only to the dry-bulb air

temperature. However, occupants can easily change the set point at which

the equipment is turned on if the combined effect of the major comfort determinants falls outside of the comfort zone. In some houses, separate sensors and

equipment (humidifier and/or dehumidifier) are provided for humidity control.

Space heating and cooling requirements are defined here as the integration of

space heating and cooling loads over time.

Space heating and cooling loads and space heating and cooling requirements can

be reduced both by improvements to the building design and changes in thermostat settings (lower for heating, higher for cooling). Purchased energy requirements can also be reduced through improvements in the conversion efficiency of

the heating and cooling equipment; however, this report focuses only on the

design of the building envelope.

^ "Thermal Environmental Conditions for Human Occupancy," ASHRAE Standard

55-74, American Society of Heating, Refrigerating and Air-Conditioning

Engineers, Inc,, New York, 1974.

5
2.2 FUNDAMENTALS OF HEAT TRANSFER IN BUILDINGS

The building envelope is made up of components that enclose the conditioned

spaces and through which thermal energy, or heat, may be transferred to, or from, the exterior. The envelope includes not only components through which

thermal energy is directly transferred, such as walls and windows, but "buffer"

components as well, such as attics, attached garages, and crawlspaces.

Heat is transmitted through the building envelope by three principal means:

thermal conduction, air exchange, and radiation. Each of the three mechanisms

plays an important role in determining heating and cooling loads; each can be

significantly modified in the design process to reduce these loads. The relationship of each to space heating and cooling loads can be stated precisely in

mathematical terras;^ however, this is beyond the scope of this report. Instead

a verbal description of each heat transfer mechanism is outlined to provide a consistent basis for the later discussion of design strategies to reduce space

heating and cooling requirements.

2.2.1 Thermal Conduction

Thermal conduction is the process of heat transfer through a material medium

in which kinetic energy is transmitted by particles of the material from particle to particle without gross displacement of the particles. ^ The driving

force of conductive heat transfer is the temperature differential across the

material medium. Under steady-state conditions, the amount of heat transferred

through the medium is directly proportional to this temperature differential.

However, under dynamic conditions, where the temperature differential fluctuates over time, the amount of heat transferred through the medium is modified

by the thermal storage capacity of the medium.

Some envelope components (e.g., walls) may have a significant thermal storage

capacity. Thus, conductive heat losses from (or gains to) the conditioned

space should be measured at the inside surface of the envelope components. It

is these surface losses or gains, sometimes referred to as surface "fluxes,"

which actually influence the air temperature and mean radiant temperature of

the conditioned space. The usefulness of the thermal storage capacity of the

envelope components should be measured primarily in terms of its ability to

modify surface fluxes during actual heating or cooling periods; modification

of surface fluxes during periods when there are no heating or cooling loads

will have little effect on later heating or cooling loads.

^ For a more precise statement of these relationships, see T. Kusuda, NBSLD,

the Computer Program for Heating and Cooling Loads in Buildings , BSS 69,

National Bureau of Standards, Washington, D.C., 1976.

^ ASHRAE Handbook of Fundamentals , American Society of Heating, Refrigerating,

and Air-Conditioning Engineers, Inc., New York, 1972, p. 533.

6
In addition to the building envelope itself, interior partitions and furnishings

can act as thermal storage devices, moderating changes in Interior air temperature by storing or releasing heat according to their own physical properties.

As with the envelope components, the usefulness of this interior storage capacity also is measured primarily in terms of its surface fluxes during actual

heating and cooling periods.

2.2.2 Air Exchange

Air exchange in houses results from air infiltration and exfiltration,

ventilation, and the opening of doors during entry and exit. Air infiltration

(exfiltration) is the uncontrolled inward (outward) air leakage through cracks

and interstices in or around envelope components. Ventilation is controlled

air exchange due to unpowered sources, such as open windows, and powered sources,

such as kitchen and bathroom exhaust fans and whole-house ventilators. In general, the greater the wind pressure and the temperature differential between

inside and outside, the greater the rate of air exchange due to any of these

means

Air exchange contributes to heating and cooling loads in two ways. The first

is due to sensible heat loss or gain ; that is, the heat loss or gain resulting

from the difference between outside and inside air temperature. The second is

due to latent heat losses or gains ; that is , the amount of heat required to

change the state of moisture in the air from liquid to vapor or vice versa. Control of relative humidity in the conditioned space requires the ability to

add or remove latent heat from the air.

2.2.3 Radiation

Solar radiation is transmitted directly through the building envelope through

transparent envelope components, such as windows, glass doors, and skylights.

(Solar radiation incident on the exterior envelope surfaces is transmitted to

the conditioned space by conduction and is therefore not considered here.) The

transmitted solar radiation is made up of both direct (beam) or diffuse (scattered) radiation. Clear sheet glass transmits from 85 to 90 percent of the

incident radiation between 0.3 and 3.0 microns (shortwave), but is virtually

opaque to long-wave radiation above 3.0 microns. 1 Thus, when the shortwave

radiation is absorbed by a surface within a room and then reemitted as longwave radiation, the heat cannot escape directly. This characteristic of

architectural glass is called the "greenhouse effect."

Solar radiation does not directly contribute to heating and cooling loads.

First, it must be absorbed by the surfaces within a room, raising their temperatures. Some of this absorbed energy is released directly to the inside air,

while some is stored for release at a later time or is lost by increased con- duction through the building envelope. In addition, some of this thermal energy

is reradiated to other surfaces in the room where it is reabsorbed. Thus, not

^ ASHRAE Handbook of Fundamentals, p. 394.

7
all of the solar gain transmitted into the conditioned space is instrumental in

reducing heating loads or in increasing cooling loads.

The extent to which solar heat gains actually affect these loads depends on (1)

the extent to which heating or cooling loads exist during hours when solar

radiation is transmitted into the building, (2) the ability of the building

envelope to resist changes in conductive heat transmission due to increases in

inside envelope surface temperatures, (3) the ability of the envelope, internal

partitions, furnishings, and air to store the heat gain from solar radiation in

order to reduce or eliminate potential heating loads at a later time or to

increase or Initiate cooling loads at a later time, and (4) the extent to which

heat gain by solar radiation in one room of a building is circulated to other

rooms in order to offset heating loads or increase cooling loads in those other

rooms

2.2.4 Radiation Exchange and Convection

In addition to heat transfer through the building envelope, heat transfer within

the conditioned spaces can have a significant impact on heating and cooling

loads. Heat transfer within the conditioned spaces occurs by two principal

means: radiation exchange and convection. Radiation exchange occurs when two

interior surfaces having different temperatures "see" one another. Thermal

energy radiates from the warmer surface to the colder surface, reducing the

temperature of the former and increasing the temperature of the latter until

an equilibrium is reached (although not generally the same temperature).

Because internal radiation exchange can influence the rate of heat loss or gain

through the building envelope, it is of some concern in the design process.

For example, during heating periods the warmer interior partitions will radiate

to the colder inside surfaces of the building envelope. This in turn raises

the temperature of the envelope surfaces and increases conductive heat losses.

This heat transfer mechanism gives rise to some interdependence among the various components of the building. As the envelope components are better insulated against conductive heat transfer, both the temperature differentials and

the rate of conductive heat loss diminish, so that the interdependence due to

radiation exchange diminishes as well. However, window surfaces, which tend to

be colder than the other room surfaces during heating periods, are still

significant sources of this Interdependence.

Heat transfer by convection , or air movement within the room, is also important.

In general, the greater the temperature difference among the various room surfaces, the greater the rate of convection. Convective currents can have a significant effect on the rate of heat transfer between the air and the room

surfaces; they also can create uncomfortable drafts. As with radiation exchange,

as all of the envelope components are better Insulated the temperature differences among the room surfaces decrease and the effect of convection on heat

loss and comfort is decreased as well.

2.3 SPACE HEATING AND COOLING LOADS

Space heating and cooling loads result when the thermal comfort criteria of the

building occupants are not satisfied by the moderating effects of the building

8
itself. In such cases, mechanical equipment must be used to reestablish or maintain thermal comfort. This mechanical equipment generally adds or removes sensible and latent heat to or from the air until comfort requirements are reestablished. In some cases, a radiant heat source, rather than direct warming of the air, is used to satisfy thermal comfort criteria during heating

periods.

The existence and size of a space heating or cooling load do not depend entirely

on the rate at which thermal energy is transmitted through the building envelope

and out of, or into, the conditioned space. Other factors which affect space

heating and cooling loads are internal heat release from occupants, appliances,

hot water usage, and lights. In addition, heat release from massive interior

partitions and furnishings, in which excess thermal energy may have been stored

from previous hours, can help offset heat losses through the building envelope.

If such massive storage media have been cooled below the indoor ambient temperature during previous hours, they also may be instrumental in offsetting cooling

requirements

2.3.1 Space Heating Loads

Space heating loads result when the net rate of heat loss from the conditioned

space at the minimum acceptable indoor temperature exceeds the rate of instantaneous heat gain from internal heat release sources. Over the course of a year, the number of hours in which space heating loads occur can be reduced by

modifying the building envelope to reduce conductive and infiltrative heat

losses and/or to increase solar gains. This reduction occurs because internal

heat gains can completely offset net heat losses during more hours of the year.

A key element in the evaluation of many design modifications is determining the

actual hours in which heating loads occur. Modifications to the building envelope which reduce net heat losses from the conditioned space are primarily useful only to the extent that they do so during periods when heating loads are incurred. For example, increasing the area of south-facing windows in order to

increase midday solar gain during the winter months is primarily useful only

to the extent that there are heating loads to offset during those hours, ^ unless

the increased solar gain can be stored Internally and recovered at a later time

when heating loads do exist. If the house is designed with relatively high

levels of insulation and is relatively tightly constructed to minimize air

Infiltration, there will be many fall, winter, and spring afternoons when no heating loads exist and thus an Increase in solar gain due to an increase in

window size may not be useable in reducing heating losses. On the other hand,

the increase in window area will increase conductive heat loss and, therefore.

^ To the extent that this increased solar gain may improve thermal comfort

conditions above the minimum acceptable conditions, this increased gain may

have some value to the occupants. In addition, the increased daylight may

reduce the need for artifical lighting. The Interrelationship between window

area and daylighting benefits is discussed in T. Kusuda and B. Collins,

Simplified Analysis of Thermal and Lighting Characteristics of Windows; Two

Case Studies, BSS 109, National Bureau of Standards, Washington, D.C., 1978.

9
will increase heating loads and may even increase the number of heating load

hours during periods when sunlight is not available.

Proper evaluation of both solar gains and internal heat storage, therefore,

requires that the calculation of heating and cooling loads be based on relatively short time intervals (usually one hour or less) rather than dally,

monthly, or seasonally.

2.3.2 Space Cooling Loads

Space cooling loads result (1) when the rate of heat gain from Internal sources

and solar radiation is greater than the net rate of heat loss (if any) from the

conditioned spaces at the maximum acceptable Indoor temperature, or (2) when

there is a net heat gain into the conditioned space at the maximum acceptable

indoor temperature. Thus, space cooling loads may exist even when the outdoor

temperature is lower than the Indoor temperature.

Although Internal heat and solar gains reduce heating loads, they increase

cooling loads; in well insulated houses they may make up half of the annual

cooling requirements. I*Jhen natural ventilation is not used, the number of

hours annually in which space cooling loads occur may actually increase as the

building envelope is better insulated. The increase in load hours will generally occur during those periods when the outdoor temperature is lower than the

indoor temperature but not low enough to completely offset the internal and

solar heat gains. To a large extent, this undesirable effect of otherwise

energy conserving design modifications can be offset by increasing ventilation

rates. However, poor air quality, external noise, or high humidity levels may

restrict the practicality of such actions.

As indicated earlier, space heating and cooling loads integrated over time are referred to as space heating and cooling requirements. Typically, space heating and cooling requirements are expressed in annual tenas. While maximum (or

"design") hourly heating and cooling loads are important for selecting HVAC

equipment capacity, annual heating and cooling requirements are more relevant

in determining the long-term energy requirements for operating the building

and the cost effectiveness of design modifications to reduce these requirements

Numerous simplified methods for estimating annual energy requirements have been

developed. However, accurate calculation of annual heating and cooling require

ments and corresponding purchased energy requirements generally requires an hour-by-hour load analysis (or an analysis based on even shorter time

intervals )

.

1 Newer load calculation methods using modified degree data and solar gain

data are providing reasonably accurate results. However, these methods are only now being made available for general use and were not available when

this report was initiated.

10
2.4 DESIGN STRATEGIES FOR REDUCING HEATING AND COOLING REQUIREMENTS

There are numerous design modifications compatible with the basic performance

objectives of single-family housing that can significantly reduce long-term

space heating and cooling requirements. Such design modifications may reduce

the capacity requirements of mechanical heating and cooling equipment as well.

To some extent, design modifications for reducing heating requirements will

also reduce cooling requirements. However, in some cases these design strategies are incompatible and a compromise solution must be determined. Economic

criteria for selecting the economically optimal combination of envelope modifications will be discussed later, in section 3. The remainder of this section

will outline building design strategies to reduce space heating and cooling

requirements, based on the discussion presented above.

2.4.1 Space Heating Requirements

Design strategies to reduce space heating requirements include methods to

(1) reduce conductive heat losses;

(2) increase conductive heat gains (due to solar radiation on opaque

envelope components);

(3) decrease air infiltration;

(4) increase solar gains through windows;

(5) circulate internal and solar heat gains to areas where they are most

useful or, alternatively, to locate areas where these gains are most

needed (e.g., family room) near the source of these gains; and

(6) to increase the thermal storage capacity of the building and its

furnishings

Although all these design strategies can substantially reduce space heating

requirements, some are Incompatible with conventional housing designs. For

example, reducing conductive heat losses and increasing conductive heat gains

cannot both be accomplished unless the conductance of the envelope components

can be changed in place. (This process has • been demonstrated using plastic

beads of insulation that can be moved in and out of a wall or window. However,

this is not currently practical in conventional housing.)

2.4.2 Space Cooling Requirements

Design strategies to reduce space cooling requirements include methods to

(1) reduce conductive heat gains;

(2) increase conductive heat losses (where the outside surface temperature

is lower than the inside surface temperature);

(3) decrease infiltration if the outdoor temperature is above the Indoor

temperature;

(4) increase ventilation if the outdoor temperature is below the indoor

temperature and the air quality is acceptable;

(5) decrease solar gains;

11
(6) decrease Internal heat gains by venting to the outside, the selection

of more efficient equipment and appliances, or the isolation of

equipment and appliances from the conditioned space; and

(7) increase the thermal storage capacity of the building and its

furnishings if flushing with cool night or morning air is practical

before the outdoor air temperature warms up.

Depending on the outside temperature, the first two strategies may be somewhat

incompatible if conductive heat gain and heat loss occur through the same envelope component. Otherwise, all other strategies are compatible with

conventional building design.

2.4.3 Inconsistencies in Design Strategies

Two major inconsistencies arise when a house is being designed to reduce both

heating and cooling loads. A design that will reduce conductive heat losses

and hence heating loads will work against increasing conductive heat losses

and hence cooling loads when the outside temperature is lower than the inside

temperature. Similarly, increases in solar heat gains and Internal heat gains

are desirable in terms of reducing heating loads, but are undesirable for

reducing cooling loads.

The first of these is the most serious with respect to heat losses through

floors. Conductive heat losses through the floor to unheated spaces below can Increase heating loads substantially during heating periods and reduce cooling

loads substantially during cooling periods. Designing a floor that has a variable resistance to heat transmission is not currently practical; thus a design

compromise must be reached based on the net annual Impact on heating and

cooling expenditures attributable to floor insulation.

Conductive heat losses through other envelope components during actual cooling

periods are not generally significant if natural ventilation is used when outdoor temperatures are lower than indoor temperatures. However, if natural

ventilation is not provided when outdoor temperatures fall below indoor temperatures, an increase in the thermal resistance of walls, window, and doors will

likely increase cooling loads.

The design inconsistencies concerning solar heat gains can be resolved largely

by using selective shading devices, either outside (e.g., awnings or roof overhang) or inside (e.g., blinds or drapes). External shading devices tend to be

more effective than internal shading devices since they absorb or reflect solar

radiation before it reaches the building envelope.

The treatment of Internal heat gains depends largely on their source. Some sources of internal heat gains can be vented rather easily (e.g., clothes drier,

bathrooms, kitchens) when it is advantageous to do so. Operational decisions

(e.g., deciding not to bake or to take a hot bath during cooling hours) can reduce the effects of internal heat gains as well. Thus the differential effects

of solar and internal heat gains can be largely alleviated by careful design

procedures and selective operational strategies.

12
There is no question that space heating and cooling requirements in buildings

can be reduced significantly at the design stage by implementing these design

strategies. However, whether such reductions are worthwhile to the user depends

on the dollar value of the energy saved and the cost of implementing those

strategies. In section 3, economic decision-making criteria for selecting the

most cost-effective building design will be discussed.

2.5 INTERDEPENDENCE WITHIN AND AMONG BUILDING COMPONENTS

A key factor to consider in calculating the change in space heating and cooling

requirements (and the corresponding change in purchased energy requirements)

due to modifications to envelope components is interdependence within and among

building components. Interdependence within components occurs when the effects

of a design modification to a component are dependent on the overall design of

that component. Interdependence among envelope components occurs when the modification of one component affects the thermal and/or energy-related performance

of another. In addition, interdependence between the overall envelope design

and the heating and/or cooling equipment performance can have a significant

effect on actual purchased energy requirements. As a result, an accurate calculation of the change in purchased energy requirements due to the modification

of any given energy-related building component requires that the design of all

the other components be considered simultaneously.

2.5.1 Interdependence Within Envelope Components

Interdependence at the envelope component level is especially strong with

respect to changes in the rate of heat transmission of those components. For

example, the reduction in heat transmission through an exterior wall resulting

from the use of insulation inserts in the exterior siding (e.g., R-3 polystyrene)

depends to a large extent on the overall thermal resistance of that wall before

the insulated siding is added. Table 2.1 provides an example of the change in

the rate of thermal transmission for a wall due to an increase in the thermal

resistance of the exterior siding for two alternative wall designs, one without

and one with insulation in the wall cavity (R-0 and R-11 respectively). In the

former case the effect of insulated siding on the rate of heat transmission (U)

is nearly five times greater than the latter (0.081 and 0.017, respectively).

Because this interrelationship is so strong, it cannot be overlooked even in

simple modeling approaches that are used to estimate reduced space heating and

cooling requirements due to design modifications.

2.5.2 Interdependence Among Envelope Components

There are two types of interdependence among envelope components: "thermal"

interdependence and "load" interdependence. Thermal interdependence relates the

change in thermal performance of a modified component to the thermal performance

of the other envelope components. Load interdependence relates the change in

net heat transmission due to the modification of the building envelope to an actual change in space heating or cooling requirements. These interdependent

relationships are often overlooked in simplistic analyses and therefore are examined further at this point.

13
Table 2.1 Change in Time-Rate of Heat Transmission (U) Through Alternative

Frame Wall Systems^ Due to Insulated Siding

Cavity Insulation

R-0 R-11

U-value of Uninsulated Siding 0.208 0.081

U-value of Insulated Siding (R-3) 0.127 0.064

Change in U-value 0.081 0.017

^ Based on Table 4A, Coefficients of Transmission (U) of Frame Walls, p. 365,

ASHRAE Handbook of Fundamentals (20 percent framing factor used).

Thermal interdependence has three primary causes: (1) radiation exchange among

the interior surfaces of the envelope; (2) convection currents on the inside

surfaces of the envelope; and (3) solar radiation transmitted through one component (e.g., windows) and reflected or absorbed by other inside envelope surfaces. Each of these can influence heat transmission through unmodified

envelope components, thereby changing the net effectiveness of any component

modification. As noted in section 2.2, this interdependence diminishes as the

overall envelope is better Insulated.

Load interdependence results from the fact that a component modification can only reduce a heating or cooling load at any given time if a load actually

exists at that time. For example, as the building envelope becomes better

Insulated and tighter in terms of infiltration characteristics, the hours in

which heating loads exist decrease significantly. (This effect is shown for

the prototype house in table 6.9, p. 70.) This is because internal and solar

gains can completely offset envelope heat loss at a lower outdoor temperature.

Any further reduction in envelope heat loss can save energy only in the

remaining heating hours. Thus whether or not a modification to a given component will reduce a heating load in any hour depends on the thermal Integrity

of the overall building envelope.

Similarly, the total number of cooling hours depends on the overall thermal

integrity of the building envelope. However, if air conditioning is used only

in hours when the outdoor temperature equals or exceeds the indoor temperature,

the number of cooling hours will stay relatively constant as the overall rate

of thermal transmission is decreased since internally generated heat must be

removed regardless of the envelope design. Under such conditions cooling load

interdependence is not nearly as significant as heating load interdependence.

14
2.5.3 Interdependence Between Space Heating and Cooling Loads and

Equipment Efficiency

Finally, the Interrelationships between space heating and cooling loads and the

conversion efficiency of the heating and cooling equipment must be considered.

Assuming that these loads can be accurately calculated, purchased energy requirements can be determined If the conversion efficiency of the heating and cooling

equipment Is known.

However, the conversion efficiency of the equipment depends In part on the

heating or cooling load and the Indoor and outdoor temperatures. Thus, as the

heating loads are decreased, the average heating equipment efficiency may change

as well, due to an Increase In part load operations and the elimination of

operations at the higher outdoor temperatures when steady-state efficiencies

are the highest. This effect can be offset somewhat by reducing the heating

equipment size to better reflect reduced design capacity requirements. For

the cooling loads, the reduction In design capacity requirement Is more than

proportional to the reduction In average cooling load size, which tends to

reduce part-load operations and Improve the seasonal performance of properlysized cooling equipment.!

All calculations throughout the remainder of this study assume that the capacity

of the heating and cooling equipment Is sized to the design heating and cooling

loads using the best available sizing criteria. Furthermore, It Is assumed that

for small changes In annual heating or cooling requirements the change In equipment efficiency Is negligible. Future studies should be undertaken to study

the effects of envelope design changes on equipment efficiency.

1 These reductions In average space heating and cooling requirements and

capacity requirements will be discussed further In section 6.
3. ENVELOPE DESIGN TO CONSERVE ENERGY: ECONOMIC ASPECTS

3.1 ECONOMIC ANALYSIS IN BUILDING ENVELOPE DESIGN

As stated earlier, space heating and cooling requirements in new buildings can

be reduced greatly through a variety of design improvements. For example, the

house pictured in figure 3.1 is a specially designed, 1200 ft^ (plus basement)

single-family dwelling that incorporates a number of energy conserving features.

These features include R-38 attic insulation, R-23 wall insulation, triple glazing, large south-facing window areas, a fully insulated basement, and extensive

measures to reduce uncontrolled air infiltration. The design heating load was

so low for this house (approximately 16,000 Btu/hr) that a specially ordered

heat pump was required to properly match its output capacity to the load.

From an economic viewpoint, two important questions must be considered in

evaluating such an energy conserving building design:

(1) Could the same reduction in space heating and cooling requirements

be achieved by an alternative, but thermally equivalent, envelope

configuration at a lower conservation cost?l

(2) Is the thermal performance of the overall building the most costeffective for the climate, energy costs, and the conservation costs

prevalent at the building site? That is, could an alternative level

of conservation reduce life-cycle heating- and cooling-related costs

further.

Both of these questions are fundamental to the design process for new buildings.

The first is Important in determining the least-cost envelope configuration

that satisfies the overall performance objectives of the building, including a given limitation on space heating and cooling requirements. The second question relates to the scale of the overall energy conservation objective. If the

level of thermal performance achieved in the example above is appropriate for

the climate and energy costs encountered at that building site, how much further

should it be Improved in more severe climates, or for alternate energy sources with higher unit costs (e.g., electric resistance heating in place of a heat

pump or direct combustion of fossil fuels)? Conversely, if the building con- figuration is found to be economically unjustifiable for the conditions encoutered , to what extent should the overall thermal performance of the building be

reduced?

Economic analysis is useful in finding deterministic solutions to both of these

design problems. As energy and housing costs continue to increase, central

heating and air conditioning become more prevalent, and supplies of the lower

cost fuels (e.g., natural gas) are curtailed for new housing starts, the answer

to these questions will become increasingly Important.

^ "Conservation cost," as used here, includes all costs related to improving

the thermal performance of the building over its expected life.

16
Qt

17

Figure

3.1

Super-Insulated

Single-Family

House

Built

by

NAHB

Research

Foundation
3.2 ECONOMIC OPTIMIZATION IN ENVELOPE DESIGN

The configuration and scale problems addressed above arise because, in

satisfying the given performance requirements of a building envelope, ^ it is

often possible to substitute one design method for another. For example, in

the configuration problem, where performance requirements include maximum permissible space heating and cooling requirements, one energy conservation technique (e.g., increased wall insulation) can usually be substituted for another

(e.g., multiple glazing) without changing annual energy requirements or significantly affecting the overall building performance objectives. In the scale

problem, where space heating and cooling requirements are variable, energy con- servation improvements are substitutable for future energy consumption expenditures while continuing to satisfy the other building performance criteria.

Economic analysis can be used in the envelope design process to determine

simultaneously the least-cost design configuration that is consistent with the

least-cost scale of thermal integrity. If all design-related costs over the

life of the building are considered (including energy conservation costs and

energy consumption costs), this analysis will provide the lowest possible lifecycle cost design that will meet the performance requirements of the building.

This resulting design is frequently referred to as economically "optimal."

This section discusses the basic principles of life-cycle cost analysis and the

economic criteria for determining optimal design solutions. The remainder of

the report focuses on the application of economic analysis to the energy conser- vation design of a prototype, single-family house for a range of climates and

cost conditions.

3.2.1 Life-Cycle Cost Considerations in New Housing Design

Life-cycle cost analysis in building design requires that all expected costs

related to the satisfaction of building performance requirements over the

building's expected useful life be accounted for on a time equivalent basis,

usually in present-value terms. These costs include not only "first" costs

such as design, construction, and selling costs, but operating and maintenance

costs as well, including utility bills, insurance, property taxes, repairs,

and replacement and salvage costs, if any. The objective of life-cycle cost

^ These performance requirements include not only considerations for thermal

comfort but for space, health, safety, structural integrity, and aesthetics.

It must be recognized that such "requirements" are to some extent negotiable,

in that user demand for them decreases as their costs increase relative to

other user wants. However, the designer is generally provided with an objective assessment of the overall performance expectations of a building, and

thus these may be viewed as fixed in the final stages of the design process.

18
analysis in building design is to minimize the sum of these costs while

satisfying all building performance requirements.

The life-cycle cost approach to design optimization provides an objective and

consistent framework for analyzing the costs associated with energy use in

buildings. Ideally, all energy-related costs incurred over the life of the

building, from drawing board to demolition, should be considered. At the

design stage, many of these costs can only be estimated, based on the most

realistic assumptions available. But this does not diminish the Importance of

the life-cycle cost approach as a framework for decision-making. Most business

decisions are made under varying conditions of uncertainty, but proper analysis

can minimize the inherent risks associated with alternative actions. Assumptions made about future costs may be less than perfect, but it is better to

make assumptions than ignore these costs entirely. Moreover, life-cycle cost

analysis provides a consistent basis for sensitivity analysis with respect to

those variables most likely to deviate from their expected values. Where

probabilities can be assigned to the outcome of the important variables (e.g.,

to the long-term rate of increase in energy costs), design solutions can be

found that minimize expected life-cycle energy-related costs.

Life-cycle cost considerations sharply contrast with design objectives based

on minimum first cost, especially with regard to energy use in buildings. The

emphasis on first cost has often been attributed to the speculative nature of

new housing construction and the relatively rapid turnover of home ownership.

Other explanations for the lack of concern for thermal integrity may be more

appropriate. Historically, energy costs were decreasing relative to construction costs up until the early 1970 's. Moreover, the widespread use of central

resistance heating and air conditioning in new housing, both major consumers

of electrical energy, is a relatively recent phenomenon. As a result, there was little incentive to consider energy conservation in housing design except

in severe climates until energy prices began to rise and the availability of

lower-cost heating fuels (i.e., natural gas) began to diminish.

This report assumes only one owner over the life of the house. While this

assumption may appear to be unrealistic, it provides a deterministic scenario

for estimating the costs and benefits of conservation features, with results

generally comparable to those of an analysis that would focus on several

shorter-term owners who are able to capitalize the unamortized portion of

their conservation investment at the time of resale. As energy prices continue

to increase, homebuyers will more likely be willing to pay more for houses

with cost-effective conservation features, making it easier for sellers to

regain their investment under such circumstances.

^ For a more complete discussion of the life-cycle cost concept applied to

building design see R. Ruegg, S. Petersen, and H. Marshall, Recommended

Practice for Measuring Life-Cycle Costs of Buildings and Building Systems , NBSIR 80-2040, National Bureau of Standards, Washington, D.C., 1980, and

H. Marshall and R. Ruegg, Simplified Energy Design Economics , SP 544,

National Bureau of Standards, Washington, D.C., 1980.

19
3.2,2 Evaluation of Future Costs and Savings

Before proceeding to the economic criteria for design optimization, a brief

discussion is necessary on evaluating costs or savings incurred in different

time periods. Specifically, costs or savings incurred in different time

periods cannot be summed until they are adjusted to reflect the time-value of

money. This process is generally referred to as "discounting." In this report,

all future costs and savings will be discounted to their present value so that

they may be directly compared to initial costs. Several mathematical formulas

are useful in evaluating one-time future costs or savings or streams of future

costs or savings over the life of a building in present-value terms. These

formulas are provided in table 3.1. In addition, table 3.1 Includes a "uniform

capital recovery" formula which can be used to calculate the principal and

interest payment required per time period in order to repay or loan over a specified length of time in uniform dollar amounts.

It is difficult to select an appropriate discount rate for general usage

because individual circumstances differ considerably. The discount rate

should reflect the real (i.e., net of inflation), after-tax, rate-of-return on

the best alternative Investment opportunity foregone, or the effective cost of

borrowing, if borrowing is required to finance new investments such as energy

conservation improvements. For many homeowners it is difficult to keep up with

inflation on a before-tax basis, let alone on an after-tax basis, and thus

their effective discount rate may be negative (i.e., less than zero percent).

For those who must borrow to finance new investments and who are in a relatively

low tax bracket (say 20 percent), a realistic discount rate based on the real

cost of borrowing may be closer to four percent, assuming an 18 percent nominal

borrowing rate and 10 percent inflation^.

Frequently, the mortgage interest rate for new housing is used as the discount

rate for energy conservation measures. However, this is not the appropriate

rate unless it coincides with the homebuyer's personal discount rate. This is

due to the nature of escalating energy costs, constant mortgage payments, and

a down payment requirement. Where incremental savings in present-value terms ^ may be equal to, or only slightly greater than, the present value of the corre- sponding Increase in monthly mortgage payments and the down pa}nnent, the homeowner may not realize a positive cash flow for some marginal conservation

investments for a number of years into the life of the building. Since this

negative cash flow may require postponement of other consumer goods purchases

or alternative investments, the homebuyer’s personal discount rate is the

appropriate discount rate to use in the analysis of costs and savings.

When using this discount rate, the calculation of the present value of all

mortgage payments, adjusted to reflect income tax deductions for Interest payments, is the most accurate method of incorporating the mortgage interest rate

into the analysis. Calculation of the present value of increased property

taxes and insurance is also consistent with this approach.

^ 1 + 0.18 ( 1 -0 . 2 ) _ 1 = .04

20
Table

3.1

Discounting

Formulas

CO

CM

CO

CO. CO . CO

<u + I •H IS/ s + •--<

e^*

(1^

IS•H+

e^*

P-i

bO t-H N—

!-H "H <

P«4 <d <I

II II II

Pm P4 Pm

bO

d

d

d

d

CU CU (U x: x: X 4J > Is cd rH

P4 § Pm I cx cd

CU 1 o O o

CO 'd

d 'd

d CO p>l d ^ d M d CU •H •H •tH <44 CO <44 CO <44 CO •H •H •H O O O ^ H H < H < < < • • d • • o • • •H • • 4J

CdM

4-4 < <I

CO3

r-4 !—

M

p4 +

<3 <

4- 4- 4- I S

•H+

O-< 'O

CU44

CU •d

•H

d

CO

(U

d

X oo

<u i bo o d

•dd •H

dM • CU •H 4-4 ,Q

<H CO

d

•H CU -d o Pu O H CO *H

44

44 CU

c^* < O P- -d CU CU J3 > 4-) • •H • CU P • O O • CU <44 P

CU

c** CU

p < -Q cdp o . p p <+

P-

•K ^-s

CU IS Pi

CU 3 Pm CJ 3 iH d3 CP

r—

IS cd V.X

cd 04 > > d cd p ' P (U iH rH p d d *H cd 3 d CU cd CU <P p a

QJ 0) s CO rH CO t4 •rH

p

@ CO Pm CU 3 CU -d C4

O

CC CU CO

p

a P o cd piM

iz:

p

w P4 P Pm 12 CJ

Pm o

CTJ cda

a cd ^H CU iH p P iH P (U

I-H 3 o CU

O 3 o > 0 bo a P 3 <p a <P o u d P •H I-H •H p •H O o •r4 O d cd d o d CU Pm CO Pm p> > tP Pm d) Pi

0)

(U rC

:s

mua

•H

(Uo

0)

V-i O

ra

4-) d

<u

tdPCO

(U •HM

(U

COB

)-i od <u •

:3 4J CO

Cd T3

cd

d

O

bOd

4-)

M

d3 l-i o o O WCO d 4-»

n

•H

d OJ 3 a ^ o

4JO S

(X CO

•r4 nH <4-1 <U Td O

CJ

CU

dO CJcd 4J CU

CU fo c CU o d

<4-4 o <4-1 o % B

CO 3

CO

4-1 d

d

OJ P

CO 3

0) 4-1 M 3

cx<4-l

cd cd

CO

0)M

4J CU d <1

(U

d

<wo do

4-» CO

CU <4-1 u o

CU 4J

U

d CU •H rQs ^ 3 Cd d

cda

d

4J o

cd *H 0 w

•H CO cd p Td iH

(U o cd CX -H O 1 P CO

<44 CU <U O C4 'd la d

<U 44

CU

d >

Cd o

II II II II II

Xi P*4

CO T3O

•H

44

CUado

•H

4J

Cd !—

Cd

CJCO

CU

4=o

cdCU

44

CU>o

CU 4J

Cd44

4Jd3

44

CU

•H

4-) cdbOd

•H

4-1 cd rH

CdO

CO

CU

CO

*r4d

CU

PL4 -dd

•H

<44OH

d

CU +

CU -f

•H

-I-

<»< CUI oC I p:

II <1 oj

21

where

eo=

rate

of

escalation

ofA

in

period I

(Oq

i£=

the

interest

or

discount

rate

in

period I

(i©"

no=

length

of

period I

(n^=

0).
Tables A-1, A-2, A-3, and A-4 in appendix A provide calculated factors for

estimating the present value of mortgage payments and interest payments over

the life of the mortgage loan, and the present value of energy expenditures

(or savings) over a given useful lifetime, respectively. Appendix B provides

a methodology for estimating the present value of property taxes and insurance

for use in the life-cycle cost analysis of heating and cooling costs. Table

B-1 in appendix B provides calculated factors for estimating Increased property taxes and insurance liabilities consistent with the assumptions made in

this report.

Total life-cycle costs (TLCC) related to heating and cooling energy usage over

the useful life of the building can be calculated in simple terms as:

IC = initial energy conservation investment costs (related to heating and

cooling usage),

R = replacement conservation costs,

S = resale value (or salvage value) of conservation features at end of

useful life,

A = annually recurring operating, maintenance, and repair (OM&R) costs

(except energy) resulting from conservation investments,

N = non-annually recurring OM&R costs resulting from energy conservation

investments

,

E = energy costs,

and all costs are in life-cycle, present-value dollars.

A more comprehensive TLCC analysis will include adjustments to initial costs

due to the financing of the investment and conservation tax credits (if any)

plus increased property tax liabilities, so that equation (3-5) becomes

TLCC =IC+R-S+A+N+E (3-5)

where

TLCC =C+R-S+A+N+E+P' (3-6)

where

C = D + M-Tj-Tc (3-7)

P* = P - Tp, and (3-8)

D = down payment

,

M = present value of mortgage payments

22
Tj = present valife of Income tax savings from interest , ^ Tc = present value of conservation tax credits,

P' = net present value of increased property taxes,

P = present value of increased property taxes, and

Tp = present value of Income tax savings from increased property

taxes

In the following subsection, the economic criteria for design optimization are based on the costs and savings incurred over the life of a building, discounted

to present value in order to enable their comparison on a time-equivalent basis.

3.2.3 Envelope Design Optimization Criteria

Having established a consistent basis for calculating energy-related life-cycle

costs in the previous subsection, basic economic optimization criteria can now

be formulated for use in the design of building envelopes. These criteria are based on the substitutability of alternative energy-conserving design modifications both among one other and for building energy requirements. Although this

report focuses on the thermal performance aspects of building envelope design,

it is assumed throughout that the non-thermal performance requirements of each

envelope component and the overall building design are satisfied at all times.

For the purposes of this report, the sum of average annual space heating and

cooling requirements, Q, corresponding to a given building envelope design and

the thermal comfort requirements of its occupants, is defined in terms of net

thermal energy units delivered to the conditioned space, i.e., after on-site

conversion and distribution losses, if any. The thermal performance of the

individual envelope components is defined in terms of their ability to reduce

net envelope heat losses during heating periods and net heat gains during

cooling periods. As stated previously, the thermal performance of these components is somewhat interdependent and the change in Q attributable to a modification to one component may vary depending on the thermal performance of the

other components. This interdependence must be considered in specifying

the substitution of one conservation modification for another.

The envelope design optimization process begins only after the non-thermal

performance requirements of the building envelope have been satisfied and the

basic building design has been initially specified. It is assumed that the

designer has considered the thermal performance aspects of the building in its

basic design, based on prior knowledge and good judgment. However, it is also

assumed that, up to this point, life-cycle cost considerations have not been

specifically addressed in finalizing the envelope design with respect to

thermal performance.

There are four criteria in the envelope optimization process; these are formulated below in a logical sequence for consideration in the envelope

design process. In practice, however, all four criteria must be satisfied

1 Income tax savings depend on the marginal rate of income taxation (i.e.,

tax bracket) for federal, state, and local income taxes.

23
simultaneously in the final envelope design. The first three criteria apply to

the determination of the least-cost design configuration^ consistent with 0> a prespecified design constraint on 0. (O might be called an "energy budget"

for space heating and cooling.) The fourth criterion provides the basis for

selecting the level of 0 that minimizes the total cost of energy conservation

and energy consumption expenditures over the life of the building, while satisfying all thermal and non-thermal building performance requirements. As the

optimal scale of Q changes, the least-cost envelope configuration consistent

with that scale will change as well.

The first criterion in the envelope optimization process requires the

determination of the least-cost design for any specified level of thermal performance over the practical range of consideration for each envelope component.

This involves a thermal analysis of the means and rate of heat transfer for each

component and a cost-engineering analysis to determine the least costly method

of reducing heat transfer. The thermal performance of an envelope component

includes more than its overall thermal conductance and air permeability. Other

factors affecting thermal performance that might be considered are: air temperature differentials from Inside to outside, air movement across the surfaces,

absorptivity and emissivlty of the surfaces, radiation exchange to and from

other components, shading and orientation of the component, and the thermal

storage capacity of the component.

Essentially, this first criterion requires that for any desired level of

thermal performance, materials (subcomponents) with lower costs per unit of

thermal performance will be substituted for materials with higher unit costs

until no further substitution is economically possible. Consistent with this

step, less costly thermal insulation (e.g., mineral wool) is generally used

instead of other more costly building materials (e.g., lumber) as a means of

increasing the thermal resistance of an opaque envelope component beyond that

needed for its basic structural integrity.

In some cases the structural design of a component must be altered to increase

its thermal performance beyond some nominal level. In such a case, any

increase in structural costs must be allocated to the cost of the additional

thermal performance that it provides. Insulation materials with higher costs

per resistance unit may be used if they provide the desired level of thermal

^ Cost here refers to the present value of all expenditures incurred in

increasing the thermal integrity of the building envelope. This includes

consideration for durability of materials, replacement and maintenance costs,

taxes, and insurance. Salvage value may be properly considered here as a negative conservation cost. However, the salvage value of most building

materials related to conservation is very small in present-value terms and

can therefore generally be Ignored if the analysis extends over the useful

life of the building,

2 Where thermal performance is continuously variable, the cost of increasing

thermal integrity is best formulated in equation form, Ivhere thermal performance is increased in discrete units, a cost schedule is more appropriate.

24
performance at a lower cost than that of a structural modification that can be

avoided with their use. This sometimes leads to the use of relatively expensive "high efficiency" insulation materials such as plastic foams instead of

less expensive conventional insulation materials with lower efficiency such as mineral wool and cellulose.

In some cases , the thermal performance of a component can be increased

continuously or nearly continuously (e.g., loose-fill insulation in attics).

In other cases, thermal performance can be increased only by discrete increments

(e.g., double and triple glazing). In general, as the thermal performance of

any component is increased, the total cost of that component is expected to

increase as well. The rate at which the total cost of each component increases

with improvement in its thermal performance plays an integral role in

establishing its optimal configuration.

The second criterion in the envelope design optimization process requires the

determination of the level of thermal performance for each component, given the

combination_of components in the basic envelope design, which satisfies the

constraint 0 at minimum total conservation cost. This criterion requires that

the thermal performance of one component be increased and the thermal performance of others be correspondingly reduced as long as the cost of the former

modification is less than the savings from the latter modifications. This substitution process is carried out among all the components until no further substitution is economically desirable. At this point, an economic balance has

been achieved; that is, the last dollar spent on improved thermal performance

for each component has the same effect in satisfying the constraint 0. Any

further substitution must increase the overall cost of achieving 0. For

example, the cost of increasing the thermal performance of the attic is generally less than that of exterior walls because of the structural modifications

needed to increase the thermal resistance of walls. As a result, the leastcost envelope design will generally specify more attic insulation than wall

insulation. However, the last dollar spent on both wall and attic insulation

should produce the same energy savings. Where discrete increments are considered, such a balance may not be perfectly satisfied. However, as long as no further substitution will reduce conservation costs, the minimum cost solution

has been determined.

The third criterion in the envelope design optimization process requires the

determination of^ the least-cost configuration of components consistent with

the constraint 0. For example, wall areas might be substituted for window

areas (or v^ce versa, according to orientation) in order to reduce the cost of

satisfying Q. In addition, a change in the aspec^t ratio or orientation of the

envelope may also reduce the cost of satisfying Q. Up to some point, it may

cost less to modify the configuration of components to achieve 0 than to improve

the thermal performance of the individual components themselves. Thus, the

substitution of configuration modifications for component modifications may

further reduce the cost of satisfying 0.

Non-construction costs may also have to be included in the determination of the

least-cost envelope design. These costs are related to the building occupant’s

needs, both real and perceived. For example, a significant change in window

25
area may be unacceptable to the occupant, even if it reduces the purchase cost

of a house. Or, in the case of modifying aspect ratios or envelope orientation,

the resulting dimensions of the house may be impractical for the lot size or in

terms of useful space arrangement. Estimating these costs is difficult, partly

because they are Intangible and partly because they vary from occupant to occupant. As a result, house designs (especially for speculatively built housing)

are usually constrained by revealed market preferences.

As with the first and second criteria, substitutions should be made amon^

components as long as these substitutions reduce the cost of satisfying Q.

Again, an economic balance is achieved in that the last dollar spent on each

raodif ication_ of component size will have the same effect in satisfying the

constraint Q. Any other configuration of envelope components will increase

the total cost of satisfying that constraint.

At this point the basic economic criteria for determining the least costly

envelope design consistent with Q have been defined. As stated earlier, all

of these criteria must be satisfied simultaneously.

The fourth and final criterion in the envelope design process requires the

determination of the optimal level of Q, Oqj that minimizes the total lifecycle cost related to the thermal comfort requirements of the building occupants.

Essentially, this criterion requires the substitution of improvments in the

thermal performance of the building envelope for energy usage wherever the

Incremental cost of the thermal Improvements is less than the dollar value

of the incremental energy savings realized. If the cost of the last units of

thermal performance already exceeds their attributable savings, Oq has been

exceeded and the thermal performance of the building envelope must be reduced

until Incremental savings are equal to their incremental costs.

Now an economic balance is achieved between the cost of increased thermal

performance and the cost of the energy resources used for space heating and

cooling. That is, the last dollar spent on energy conservation (over the life

of the building) has the same productivity (in terms of satisfying thermal comfort requirements) as the last dollar spent on energy consumption. No further

change in the envelope design can reduce the total present-value, life-cycle

cost of achieving the thermal comfort requirements of the building occupants.

This criterion requires that the incremental life-cycle dollar savings (in

terms of reduced energy requirements) be calculated for each additional building envelope modification considered. These incremental savings are then compared with the incremental costs incurred on a present-value basis. All

modifications with incremental savings greater than or equal to incremental

costs are included in the optimal envelope design; modifications with

incremental savings less than Incremental costs are not.

This fourth criterion is central to any economic analysis of energy

conservation in building design because it determines the extent to which

design energy requirements should be tightened up in response to rising energy

prices. For any given location, the greater the energy costs relative to con- servation costs, the greater will be the optimal level of thermaj (jerformance

26
for the envelope and the lower will be Qq. Similarly, the greater the

conservation costs relative to energy costs, the lowejr will be the optimal

level of thermal performance and the greater will be Oq_i Th® more efficient

the heating and cooling equipment, the greater will b^ OoJ the less efficient

the heating and cooling equipment, the lower will be Qq,

The fourth optimization criterion is stated somewhat differently than the

previous ones. In the first three criteria the constraint Q was stated in

terms of annual heating and cooling requirements, as measured in thermal energy

units. In this last step, the constraint Q is not only released but heating

and cooling requirements per se are no longer primary to the optimization

process. Instead, the primary factor is the cost of the energy consumed (or

saved) to satisfy the thermal comfort requirements of the occupants. The cost

of that energy is a function of purchased energy prices and the efficiency of

the space heating and cooling equipment. Moreover, the cost of energy used

for heating may differ significantly from cooling costs, and the efficiency of

the heating equipment may differ significantly from cooling efficiency. Therefore, the dollar value of a unit change in annual heating requirements may be

quite different than a unit change in annual cooling requirements, ^ The first

three steps in the enveJLope design optimization can be made more consistent

with this last step if Q is expressed in terms of the dollar value of the average annual heatj^ng and cooling requirement instead of its thermal energy value.

This redefined Q has more meaning from an economic standpoint than the previous

definition, and will be used in determining optimal building envelope configurations in this report.

These steps in the envelope design optimization process have been presented in

a logical order, but as stated earlier, all four steps must be satisfied simultaneously in the finalized design. If the thermal performance of each envelope

component could be increased continuously at Increased cost and the interdependent relationships among all the components could be modeled mathematically,

the optimal design configuration could be directly determined by differentiation, However, because of the discrete nature of most component modifications

(e,g,, insulation batt resistances and multiple glazing), and the difficulty of

specifying the interdependent relationships among components in mathematical

form, an alternative methodology for design optimization must be developed.

This is done in the following subsection,

3,2,4 Priority Ranking to Determine the Incremental Savings Resulting From

Component Modifications

It would be a relatively easy task to determine the optimal envelope

configuration if there were no interdependencies among the envelope components.

First, the optimal thermal performance of each component would be determined

individually, based on incremental savings and cost analysis, without regard

^ Note that in cases where a modification reduces heating requirements but

Increases cooling requirements, or vice versa, the net savings in dollar

terms are used in finding the optimal energy-related component design.

27
to the overall envelope configuration. Then, substitutions of related component

areas could be made (e.g., windows and wall areas), ignoring unrelated envelope

components (e.g., ceiling and floor). This simplistic approach is often used

when insufficient information regarding the interdependencies among envelope

components is available.

Today, however, it is possible to quantify the effects of interdependencies

among components to a considerable extent through the use of high speed computers, advanced computational algorithms, and hourly climatic data. When this

type of analysis is carried out , computed reductions in heating and cooling

requirements in a given building resulting from the modification of any one of

its components will vary depending on the overall design configuration of that

building. When such advanced computational methods are employed (as they are

in this report) , the methodology used to determine the optimal envelope design

must consider the effects of this interdependence. At the same time, the methodology must be relatively easy to use in the design analysis or the costs of

searching for an optimal solution may outweigh the incremental benefits. Ease

of computation is especially important in this report because optimal designs

are sought for a wide range of climates and energy costs.

The final selection of a methodology must weigh a number of factors. For

instance, the most accurate methodology for determining the optimal design con- figuration for a new building envelope is also the most costly. This "brute

force" methodology requires that the total life-cycle costs associated with

each possible alternative configuration be calculated. The configuration with

the lowest total life-cycle cost is, by definition, the optimal design. While

the number of configurations to be considered can be greatly reduced by using

good engineering judgment to eliminate improbable designs, this methodology

would still require an inordinate amount of computer time and manpower and is

therefore unacceptable as a general approach.

A more efficient methodology might be developed which converges on the optimal

design configuration. However, this would still require a large number of

computer analyses to model adequately the interdependent relationships.

To resolve these difficulties, an alternative approach to design optimization

is outlined here which will generally result in the same solution but at con- siderably less computational expense. This approach concentrates on calculating the Incremental contribution of each design modification to the reduction

of heating and/or cooling requirements. These modifications are introduced

sequentially into the thermal analysis in decreasing order of relative cost

effectiveness, along with all the more cost-effective modifications, as follows;

First, the heating and cooling requirements of the house without any of the

energy conserving modifications are determined. Then the heating and cooling

requirements are recalculated as the first, most cost-effective, modification

is incorporated into the design and the reduction in those reqireraents relative

to the base case is calculated. The incremental reduction in space heating and

cooling requirements is determined in like fashion for each additional modification, leaving all of the previous (and, by definition, more cost-e i ive)

modifications in the design. As a result, once a given modification lias been

established as cost effective on an absolute basis, all of the preceding

modifications will be cost effective as well.

28
This methodology will be referred to as the "priority ranking" process. This

approach has certain limitations; however, it offers a reasonably accurate

methodology for determining the optimal levels of thermal resistance in the

envelope components. In addition, the same computer analyses of the heating

and cooling requirements, in expanded form to show the contribution of each

component to these requirements, can provide much of the information needed to assess the effects of substitutions among components and reorientation of the

building.

The priority ranking methodology is a two-step process. In the first step, a trial ordering of modifications, in terms of decreasing relative cost effectiveness, is established, based on good engineering judgment and the results of

previous analyses. Computer analyses of the modifications in this trial

sequence generally will provide results that are sufficient to rank the modification by relative cost effectiveness. This can be verified when the analysis

of this second ordering is completed.!

The priority ranking approach is based on several assumptions about the effects

of the modifications considered.

(1) Any Improvement in the thermal performance of a component will

Increase the cost of that component within the range of investigation.

(2) The change in the load-reducing potential of any component modification

attributable to the overall level of thermal performance of the

building envelope will not affect the rank order of the envelope

modifications considered. This is because the incremental decision

to select any one of several alternative component modifications at

any given point is made based on the same envelope configuration at

that point.

(3) The interdependence between the overall envelope design and the

efficiency of the heating and cooling equipment is irrelevant for the same reason as (2).

(4) Thus, the only type of interdependence that potentially can present a problem in the priority ranking methodology is thermal Interdependence,

the interdependence among components due primarily to radiation

exchange. This occurs because an Increase in the thermal performance

of one envelope component can increase the heat loss through other

components, thereby Improving the cost effectiveness of insulation in

those other components. Theoretically, this situation could create

some instability in the ranking of modifications that are very similar in terras of cost effectiveness. This, however, is not likely to

! In the thermal analysis discussed in section 6, this sequential ordering is

based on reductions in heating requirements only in order to facilitate the

analysis. As a result, the modifications can be ranked in terms of

decreasing energy savings per dollar invested, since the dollar savings are directly proportional to energy savings.

29
result in a significant problem in identifying the optimal combination

of design modifications because this effect on the modifications found

to be marginally cost effective is quite small. Moreover, the precise

effect of radiation exchange on reductions in heating and cooling

loads is difficult to calculate because of shortcomings in the available radiation exchange algorithms. For these reasons, this type of

interdependence is not directly considered in the priority ranking

methodology,

A final point should be noted: Any attempt to include modifications to the

heating and cooling equipment that increase its conversion efficiency in the

general priority ordering process is likely to fail. This is because of the

high degree of interdependence between the envelope and the equipment operation

in terms of energy usage. As the thermal integrity of the envelope is improved,

the resulting energy savings from any equipment modification decrease, because

the equipment is used less. Similarly, any improvement in the conversion efficiency of the heating or cooling equipment will result in smaller energy savings from any envelope modification. Thus, the priority ranking of envelope

and equipment modifications together may indicate that some conservation measures are cost effective which would not be selected in a more careful analysis.

In fact, the optimal envelope configuration and optimal equipment design must

be determined simultaneously .

^ This simultaneous solution to equipment and envelope design is the subject

of a forthcoming NBS Interagency Report by the author titled "Siraultaneous

Economic Optimization of Building Envelope Components and HVAC Equipment

Selection at the Design Stage."

30
4. ENVELOPE CONFIGURATION AND MODIFICATIONS ANALYZED

4.1 PROTOTYPE RANCH HOUSE; DESCRIPTION AND OPERATIONAL ASSUMPTIONS

It is possible to make rough estimates of the thermal performance of individual

envelope components and load reductions resulting from modifications to those

components using simplistic steady-state heat transfer assumptions. For this

type of analysis, it is not necessary to specify the overall building design.

However, in order to determine these values using more sophisticated computation methods, the building configuration must be specified in some detail.

Moreover, to obtain meaningful data on component performance and load reduction

potentials, sensitivity analyses of the most significant energy-related design

parameters, such as building size, window areas, and orientation, should be

provided. This also requires a detailed description of the building configuration. This section provides a detailed description of the building and its

modifications that are analyzed in this report.

The basic building design is a 1200 ft^, single-family, detached, ranch-style

house. This house is shown in figures 4.1 (elevations) and 4.2 (floor plan).

It is nearly identical to the "compact, ranch-style" house proposed in a recent

NBS publication, 1 as typical of a great deal of new and existing housing in the

United States. It is not intended to be a model house that should be copied

outright because of its inherent design qualities. Rather, it is intended to serve as a starting point for evaluating envelope design modifications.

The 1200 ft^ area of this house is smaller than the 1974 national average of

1684 ft2 for detached houses. 2 However, a one-story house would tend to be

smaller than the overall average floor area of all single-family detached

houses which includes multistory houses.

Table 4.1 describes the basic envelope component areas for the prototype house.

Table 4.2 provides the basic structural details of the various envelope components. Opaque wall construction before and after expansion of the wall thickness is based on 24-in stud centers. In effect, this increases the relative

cost of using 2 x 6-ln studs instead of 2 x 4-in studs because the increased

thickness of the wall framing is not offset by greater spacing between studs.

This conservative approach has been taken because in some local building codes

2 X 4-in studs on 24-ln centers are permissible.

^ S.R, Hastings, Three Proposed Typical House Designs for Energy Conservation

Research , NBSIR 77-1309, National Bureau of Standards, Washington, D.C.,

October 1977.

2 NAHB Research Foundation, "A National Survey of Characteristics and

Construction Practices for all Types of One-Family Homes," Rockville, MD,

February 1974.

31
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32

FRONT

ELEVATION

OFA

TYPICAL

RANCH

HOUSE
2840

TW

2840

DH

6068

SL

GL

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33

FLOOR

PLAN

OF

A

TYPICAL

RANCH

HOUSE
Table 4,1 Component Areas of 1200 Square-Foot

Prototype House

Area in Ft^

Ceiling

Windows

North Facing 4 13.8 ft2

South Facing 1 (3 20 ft2

Total

1

JL 12 ft2

Sliding Glass Door

(South Facing) 1 (3 40 ft^

Entry Door

Opaque Wall Area Insulated Stud Total

North Facing 181.3 ft2 63.6 f t2 244.9 ft2

East Facing 209.1 ft2 30.9 ft2 240.0 f t2

South Facing 189.4 ft2 58.6 ft2 248.0 f t2

West Facing 209.1 ft2 30.9 ft2 240.0 ft2

Total 788.9 ft2 184.0 ft2 972.9 ft2

1200.0

87.1

40.0

20.0

972.9

Floor

Total Envelope Area

1200.0

3520.0

34
Table 4.2 Basic Construction Details of Prototype House

1 . Roof

2 X 4-in roof trusses 24-in on center

1/2-in plywood deck

building paper

asphalt shingle roofing

2. Ceiling:

2 X 4-in ceiling joists, 24-in on center

1/2-in gypsum wallboard

3. Exterior wall:

3/8-in wood siding

1/2-in fiberboard sheathing, regular density

2 X 4-in studs, 24-in on center

polyethylene vapor barrier (4 mil)

1/2-in gypsum wallboard

4. Floor:

2 X 10-in floor joists, 24-in on center

3/4-in wood subfloor

5/8-in plywood floor

pad

carpet

5. Windows:

Premium quality wood double hung or slider

6. Exterior Entry Door:

Premium quality wood, 1-1/2-in thick (U = 0.49)

7. Sliding Glass Door:

Premium quality, wood frame

35
The glass-to-gross-wall area ratio is 11.4 percent. This ratio approaches the

minimum desirable glass area for the room area considered.^ The prototype

house has larger windows on the south face of the building, and the house is

oriented so that the longer walls face north and south. Windows have been

excluded from the side elevations. ^ This is a common practice if neighboring

houses are close and a lateral view is undesirable This orientation of the

building and the south-facing glass will be shown to be advantageous in section 6. The effects of alternative orientations for wall elevations and glass area will be examined as well in that section.

Although figure 4.2 provides the floor plan of this prototype house, it is

somewhat limited in usefulness because only the outside walls can be modeled

in the NBSLD computer program.^ This shortcoming has several effects on the

analysis

(1) the mass storage effect of the internal partitions is ignored,

(2) the modeling of radiation exchange among the interior envelope

surfaces is distorted,

(3) solar radiation transmitted through the windows must fall entirely

upon the interior envelope surfaces (i.e., floor, ceiling, and outside

walls) rather than upon interior partition surfaces, and

(4) thermal zoning of the rooms cannot be modeled.

The resulting effects on calculating heating and cooling requirements will be

discussed further in section 5.

Air infiltration rates are calculated in terms of air changes per hour and thus

are not directly associated with specific sources of leakage, such as windows and

doors. The air change rates used are based upon an empirical relationship demonstrated by Achenbach and Coblentz in a number of electrically heated houses.

^ S.R. Hastings, Three Proposed Typical House Designs .

^ Note that all rooms (except bathrooms) have windows large enough for

emergency egress.

^ S.R. Hastings, Three Proposed Typical House Designs .

^ Efforts are currently underway to resolve the problem of internal partitions

and thermal zoning in the NBSLD computer program. This is a difficult problem, however, since it requires running the load analysis program

simultaneously for each room and "coupling" the resulting loads.

^ P.R. Achenbach and C.W. Coblentz, "Field Measurements of Air Infiltration

in Ten Electrically Heated Houses," ASHRAE Transactions Vol. 69, American

Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc., New

York, pp. 358-365, 1963.

36
This relationship determines air changes per hour (AC) as a function of wind

speed (V) in miles per hour and inside-outside temperature differentials (AT)

in °F. This relationship, adapted for use in this report, is represented by

the equation

AC = 1.68 (0.15 + 0.013 V + 0.005 AT). (4-1)

The relationship is depicted graphically in figure 4.3 for a range of wind

speeds and temperature differentials. Note that the equation results in an air

change rate of approximately 1.0 at a 15 MPH wind speed and a AT of 50 °F, but

considerably less under more typical conditions. For example, at a 7.5 MPH

wind speed and a temperature differential of 25°F, the hourly air change rate

is approximately 0.63. The minimum rate of hourly air change allowed is 0.25.

The air change rate measured in the NBS Bowman House study ^ after the house was

caulked, weatherstripped , fully insulated, and fitted with storm windows was

1.0 when the AT was 50°F and wind speed was 15 MPH.

Lower air change rates have been measured in other houses under controlled

conditions. 2 However, such conditions do not generally include the effects of

such considerations as door openings and controlled ventilation of kitchens and

bathrooms. Thus, the infiltration rates based on equation (4-1) appear reasonable for actual occupancy. It would be highly desirable to evaluate the effectiveness of certain envelope modifications in reducing the rate of air infiltration; however, at present such data are not available. Therefore, this

report does not consider the increased use of sealants and tighter fitting

doors and windows.

Operational considerations have a significant effect on heating and cooling

loads and therefore must be specified. The following assumptions were made in

the computer analysis:

(1) Two adults and two children occupy the house year-round. Daily heat

release profiles for the occupants are shown in table 4.3 along with

heat release from lighting and equipment operation (including cooking,

bathing, dishwashing, refrigeration, etc.). Because of limitations

in the NBSLD computer program, these are assumed to be the same in

both summer and winter. These internal heat releases are shown

graphically in figure 4.4.

(2) During heating periods thermostat settings are assumed to be 68°F

between 7 a.m. and 11 p.m., with setback to 60°F between 11 p.m. and

7 a.m. During cooling periods the thermostat setting is 78°F. No

heating or cooling is required when the indoor temperature floats

between 68°F (60°F setback) and 78°F.

^ D.M. Burch and C.M. Hunt, Retrofitting an Existing Wood-Frame Residence

Energy Conservation—An Experimental Study , NBSIR 77-1274, National Bureau

of Standards, Washington, D.C., 1977.

O^ P.R. Achenbach and C.W. Coblentz, "Field Measurements of Air Infiltration."

37
iinOH U3d S39NVH3 HIV

38

INSIDE-OUTSIDE

TEMPERATURE

DIFFERENTIAL

(

F|
Table 4.3 Hourly Lighting, Equipment, and Occupant Heat

Release Schedule (Btu/hr, 1200 Ft^ House)

Occupant

Hour Lights Equipment Sensible Latent

1 0 717 1050 150

2 0 717 1050 150

3 0 717 1050 150

4 0 717 1050 150

5 0 717 1050 150

6 0 2025 1050 150

7 2130 2995 1050 150

8 2130 4008 960 240

9 49 2405 384 96

10 49 2574 384 96

11 49 2405 384 96

12 49 3712 384 96

13 49 2616 384 96

14 49 2025 384 96

15 49 2025 384 96

16 49 2151 662 166

17 49 2025 662 166

18 49 2742 960 240

19 1065 2953 960 240

20 1065 3417 960 240

21 2130 4219 960 240

22 2130 2616 960 240

23 2130 2953 960 240

24 2130 2025 1050 150

Source: U.S

Consumption

,

. Department of Housing

Single-Family Housing,

and Urban Development

Report No. HUD-HAl-2

, Residential Energy

(Prepared by Hittman

Associates

,

Columbia, Md Washingt;on, D.C. , 1973.

39
C»4

ir>

CM

O)

CO

CO

SUn0H-ilVM01l)l

J 1 1 I I

I I

I \ ±

O OO CO ^ CM

ISQNVSnOHi Nil n)S

40

HOUR

OF

DAY
(3) Windows and doors are assumed to be closed whenever the house is

being heated or cooled. Natural ventilation, or a whole-house fan,

is assumed to be used instead of mechanical air conditioning whenever the outdoor temperature is below 78®F. While this may not be

typical operating procedure for many homeowners, this assumption is

made because (a) it is consistent with energy-conserving operating

procedures; and (b) the point at which windows are closed and the

air conditioners turned on will vary widely depending on the individual homeowner's perception of comfort. As a result, the potential

negative effects of insulation on cooling loads, which can occur when the outdoor temperature is below the Indoor temperature, are avoided. If windows and doors are always kept shut, it is likely

that increased wall insulation levels and multiple glazing will

increase, rather than decrease, overall cooling requirements.

This study does not model the opening of windows to reduce Indoor temperatures

below 78 “F at night or early morning with the subsequent closing of windows in

anticipation of offsetting later air conditioning requirements. However, indoor

temperatures are allowed to float as high as 78® during heating periods before

windows are opened enough to offset potential air conditioning loads. This

buffer can alleviate potential heating loads as outdoor temperatures begin to

fall.

4.2 DESIGN MODIFICATIONS TO REDUCE SPACE HEATING AND COOLING REQUIREMENTS

This section outlines and discusses the design options evaluated in this study.

Only options which can be modeled satisfactorily with the NBSLD computer

program were evaluated.

4.2.1 Building Shape and Orientation

Building shape and orientation can have a significant impact on energy use because of the influence of solar and wind loads. Since NBSLD is not sensitive

to wind direction, this study examines orientation only with respect to solar

loads. This report also restricts its analysis of orientation effects to the

four major compass points. Relative heat losses and gains through the four

wall elevations are calculated over the actual load hours encountered. The

change in sensitivity to orientation as the building becomes better insulated

also is examined.

4.2.2 Window Orientation and Sizing

Under certain conditions windows can help offset both heating and cooling loads.

For example, properly managed south-facing windows can sometimes result in a net reduction in annual heating loads. Similarly, by opening windows to permit

cross ventilation, air conditioning loads can be reduced (provided, of course,

that the outdoor temperature and air quality are acceptable).

41
In this study, solar heat gains through windows are calculated only for the

north and south elevations since there are no windows on the ends of the house.

During the warmer months (May through September) solar gains through all windows are assumed to be reduced by 50 percent due to shading by exterior or interior means. Solar gain data are provided to adjust for further shading of

south-facing windows.

The effects of cross ventilation during those periods when it will eliminate

potential air conditioning loads are considered. However, the effects of window size and orientation on the maximum possible rate of natural ventilation

are not considered due to modeling limitations.

4.2.3 Insulation

Table 4.4 shows the alternative insulation resistances in the attic, interior

walls, and floor of the prototype house, as well as three levels of window glazing that are examined in this study. Table 4.4 also provides the resulting

U-values of the various envelope components affected.

The analysis assumes that the insulation is installed evenly throughout the

attic; in actual practice, however, higher insulation levels cannot be

Installed in perimeter areas where the roof is too close to the attic floor.

In general, raising the roof line to accommodate higher insulation levels in

these areas cannot be justified economically, unless a substantial roof

overhang is desired.

Structural modifications to the exterior walls are considered only to

accommodate greater insulation thicknesses than are possible with ordinary

construction. R-11 and R-13 insulation batts are assumed to fit between con- ventional 2 X 4-ln framing in exterior walls without compression. In order

to accommodate R-19 insulation batts (approximately 6 inches thick) into the

exterior wall, 2 x 6-in framing is used. However, since the actual thickness

of a 2 X 6-in stud is approximately 5.5 inches, the R-19 batt must be slightly

compressed, reducing its resistance to R-18.^

An alternative approach to increase the thermal performance of exterior walls

beyond R-13 is the use of extruded polystyrene sheathing in place of more com- monly used flberboard. Polystyrene sheathing is available in several thicknesses, ranging from 0.75 Inches to 2.0 inches. Because this sheathing covers

the entire opaque wall area, it greatly reduces the thermal bridging effect of

the studs in the wall construction. However, because of its poor structural

performance, use of this material generally requires some corner bracing, and

in actual practice, plywood sheathing is often substituted at the corners of the

house, reducing the overall applicability of the polystyrene sheathing.

The costs and steady-state U-values used in this report for the 2 x 6-in, 24-ln

on center wall with R-19 glass fiber batts and the 2 x 4-in, 24-in on center

1 Private communication with Owens Corning Fiberglas representative,

Granville, Ohio.

42
Table 4.4 Alternative Component Designs and Corresponding

U-Values (Winter Design)

Attic Walls Floors

Nominal

Resistance

U Nominal

Resistance

U Nominal

Resistance

U

R-0 0.5720 R-0 0.2180 R-0 0.2324

R-11 0.0844 R-11 0.0824 R-11 0.0675

R-19 0.0498 R-13 0.0756 R-19 0.0466

R-30 0.0321

i R-19 a 0.0577

R-38 0.0255 ^ R-23^ 0.0467

R-49 0.0200

Windows Door Sliding Glass Door

Description U Description U Description U

Single Pane 1.13 Prime Door 0.49 Single Pane 1.13

Storm Window

Over Single Pane 0.56

Prime Door

Plus Storm Door 0.33

Double Pane 0.58

Storm Window

Over Double Pane 0.36

^ Nominal 2 x 6-in studs provide 5.5-in cavity. R-19 glass fiber batt in 5.5-in

cavity compresses to R-18.

^ R-5 polystyrene sheathing is substituted for R-1.32 flberboard sheathing.

43
wall with R-13 glass fiber batts and R-5 (1-in) polystyrene sheathing are nearly

identical, although such costs may vary over time and in different locations.

Both systems are gaining increasing acceptance in the building community with

builders showing preference for one or the other based largely on their personal

experience. The 2 x 6-in stud wall tends to decrease the amount of available

floor space slightly. This can generally be compensated for by increasing the

outside dimensions of the house at relatively small cost.^ The 2 x 4-in, 24-in

on center wall with polystyrene sheathing might be considered unacceptable from

a structural integrity standpoint and thus the 2 x 4-in, 16-ln on center wall

is more likely to be used, offsetting its cost advantage over the 2 x 6-in,

24-ln on center wall. Thus, the 2 x 6-in, 24-in on center stud wall with R-19

insulation batts is used for thermal analysis of the envelope. However, because

both systems have relatively small mass and the same U-value, the thermal

performance of either wall is nearly identical.

In order to increase the thermal resistance of the wall beyond this level, R-5

polystyrene sheathing is used in conjunction with the 2 x 6-in frame walls,

giving an overall U-value of approximately 0.047. The derivation of the steadystate U-values for each wall system analyzed in this report is shown in

table 4.5.

4.2.4 Multiple Glazing

Multiple glazing is used to decrease thermal transmission losses through the

windows. Because storm windows have slightly better thermal performance

characteristics (U = 0.56 versus U = 0.58 to 0.69) and somewhat lower cost than

double-pane windows ($225 versus $255 for this house), they are used to provide

double glazing. (Superior infiltration abatement characteristics of storm

windows are not considered in this study but are likely to make them even more

cost effective.) In order to provide triple glazing, double-pane windows are used in conjunction with storm windows. In all cases, tight-fitting, selfstoring (triple track), metal-frame storm windows are assumed. No adjustment

for prime window sash is made as the windows are sized by glass area. Solar

transmission through single glazing is assumed to be 80 percent; through double

and triple glazing it is assumed to be 70 percent and 60 percent, respectively.

4.2.5 Doors

A tight-fitting, metal and glass storm door is used to reduce heat transmission

through the front door of the house. In actual practice it vjoxild be better to

replace the glass inserts in the storm door with screen inserts during the non- heating months. However, in the NBSLD analysis the glass inserts must be

modeled throughout the year. Infiltration abatement characteristics were not

considered since it is assumed that the prime door is tight fitting.

^ For the 1200 ft^ ranch house, this would require that the length of the

house be expanded by approximately 0.75 ft at a cost (including foundation,

flooring, wall, and roof) of approximately $100 (1979 dollars). Note that

this has no effect on the cost of inside construction since the inside area

is unchanged.

44
Table

4.5

Alternative

Wall

Construction

Methods

to

Increase

Insulation

Above

R-11 I

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43

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45

Does

not

include

adjustment

for

change

from

24-in

centers

to

16-in

centers

(most

conventional

construction

would

begin

with

16-in

centers).
The south-facing sliding glass door is upgraded by replacement with a double-glazed door having a 1/2-in air space.

4,2.6 Modification Cost Data

Table 4.6 lists the costs of the modifications outlined in table 4.5. They are based on data gathered in 1977 by the NAHB Research Foundation in a report contract to NBS entitled "Selected Cost Data on Residential Construction," These

data include overhead and profit factors and were adjusted to end-year 1979

dollars using a 30 percent cost inflation f actor. ^ Regional variations may be

appropriate, although these are generally less than 10 percent. Recent investigation reveals that the incremental cost of premium quality double-glazed windows and doors are often below the costs used in this report, due to greatly

increased production quantities in recent years. However, no adjustment was made to account for seal failure between glazings, which would require replacement in some cases, resulting in increased life-cycle costs. Storm doors will

generally not last as long as the other modifications considered. Thus one replacement storm door has been factored into the storm door cost shown in

table 4.6. A real discount rate of zero percent was used to discount the

future replacement cost ($75) in current dollars to present value so that the

year of replacement does not become critical to the analysis.

1 This factor represents inflation in the residential construction industry

from mid-1977 to end-year 1979, and is based on the Boeckh and Engineering

News-Record construction cost indexes. See U.S. Department of Commerce,

"Construction Review," Vol. 26, No, 1, January 1980.

46
Table 4.6 Envelope Modification Costs (1979)®

Total Incremental

Cost cost

Total Square Total Square

Area Foot Area Foot

1. Attic Insulation

(1200 ft^ gross)

R-11 $235 $0.20 $235 $0.20

R-19 345 0.29 110 0.09

R-30 515 0.43 170 0.14

R-38 625 0.52 110 0.09

R-49 795 0.66 170 0.14

2. Wall Insulation

(1120 ft^ gross)^

R-11 220 0.23 220 0.23

R-13 290 0.30 70 0.07

R-19 580 0.60 290 0.30

R-23 870 0.90 290 0.30

3. Floor Insulation

(1200 ft^ gross)

R-11 280 0.23 280 0.23

R-19 405 0.34 125 0.11

4. Windows

(87.1 ft2)

Storm Windows 225 2.58 225 2.58

Storm Windows and 480 5.51 255 2.93

double pane glass

(relative to single

pane)

5. Sliding Glass Door

(40 ft2)

Double Pane Glass

(relative to single

pane )

180 4.50 180 4.50

6. Door

(20 ft2)

Storm Door 150C 7.50 150 7.50

® Installed costs in new housing, including overhead and profit. Source:

NAHB Research Foundation contract report, "Selected Cost Data on Residential

Construction," 1977 updated to end-year 1979 costs using a cost adjustment

factor of 30 percent. (Adjustment factor based on construction cost indexes

for residential construction (Boeckh and Engineering News-Record).)

^ Costs for wall insulation are based on gross wall area of 1120 ft^ rather

than a net wall area of 973 ft^. Cost per square foot of actual net wall

area is therefore higher than nominal cost.

^ Storm door cost includes initial cost of $75 plus one replacement door at

$75.

47
5 . LOAD-ESTIMATING METHODOLOGY

Section 6 provides the actual analysis of the prototype ranch house and

component modifications described in the preceding chapter. An expanded output

version^ of the NBS Load Determination^ (NBSLD) program, was used to carry out

this analysis. The reasons for using this modified program and the assumptions

made are described in this chapter.

It has been well established that life-cycle cost analysis can play an important role in designing a building that has reduced energy requirements

over the long run. The usefulness of such an analysis is limited largely by

the availability of accurate thermal engineering data that relates the sensitivity of long-term heating and cooling requirements to changes in design parameters. For this analysis, it is especially important that the incremental

reduction in energy requirements resulting from design modifications be reasonably accurate in absolute terms. This is because life-cycle costs can only be

reduced through design modifications which have incremental benefits (in terms

of reduced present-value energy expenditures) greater than Incremental costs.

Under ideal circumstances, actual measured energy data would be preferred to

estimate the life-cycle costs of alternative building designs in different

climates. In practice, however, it is nearly impossible to use actual

measurements for the following reasons:

(1) Operational factors, such as window and door openings, thermostat

settings, internal heat release, solar gain, etc,, are likely to be

different from building to building.

(2) Identical houses in identical surroundings that are located in

different climatic zones are not likely to be found in order to

determine the effects of climate on building energy requirements.

(3) Climate patterns during different measurement periods may not be

comparable,

(4) It is Impractical to measure the individual effects of a wide range

of different conservation features, used in different combinations,

in different climates, and under different operational modes.

To avoid these problems, a load determination model is used which holds all

variables constant except those being analyzed. Such a model can be used to

evaluate heating and cooling loads in different climates under a range of

design and operational assumptions. However, steady-state load determination

models do not adequately estimate design or annual heating and cooling

^ S. R. Petersen and J. P, Barnett, Expanded NBSLD Output for Analysis of

Thermal Performance of Building Envelope Components , NBSIR 80-2076, National

Bureau of Standards, Washington, D.C., 1980.

^ T. Kusuda , NBSLD, The Computer Program for Heating and Cool?lng L oads .

48
requirements, especially if the annual requirements are based on heating and

cooling degree days (base 65 ®F), For this reason, a load determination model

that calculates the dynamic thermal response of a house and considers solar

gains, internal loads, air infiltration rates, and hour-by-hour weather data

typical of a given geographic location is needed. NBSLD, which meets all of

these requirements, was selected to provide the necessary heating and cooling

load data used in this report.

NBSLD was developed originally as a research tool to calculate accurately

heating and cooling loads in buildings. To meet the requirements of this

study, the program had to be modified because NBSLD in its original format

provided only total heating and cooling loads.

To better understand the effects of each of the building envelope components

on annual heating and cooling requirements, the actual sources of the heating

and cooling loads also had to be identified. This load source analysis allows

the designer to determine the extent to which heating and cooling loads are influenced by heat gains and losses through ceilings, walls, floors, windows,

doors, and infiltration, as well as the effects of solar gains and internally

generated heat. The effect of building orientation can be quantified directly

by observing the performance of the similar envelope components at different

compass orientations, without rotating the building. The mechanisms by which

the various envelope components lose or gain heat during actual heating and

cooling periods can be better understood and quantified as the design is

modified.

A printout of the expanded NBSLD output format (NBSLD-XO) with data for the

prototype single-family house, based on the Washington, D.C., Test Reference

Year (TRY) weather tape, is shown in table 5.1. This 1200 ft^ house is fitted

with R-19 attic Insulation, R-11 wall insulation, R-11 floor Insulation, and

storm windows. The columns above the component titles contain (1) an internal

identification number, (2) the compass orientation, where appropriate (0® = north), (3) the winter design U-value, and (4) the component area, in square

feet, where appropriate. The sources of monthly and annual heating requirements

(H and TH) are shown first, followed by the sources of monthly and annual cooling requirements (C and TC) , all in Btu. Positive numbers are heat gains;

negative numbers are heat losses. Note that cooling requirements and their sources are divided into two parts: (1) cooling requirements where the outdoor

temperature is greater than the indoor temperature (C+ and TC+) and those where

the outdoor temperature is less than the Indoor temperature (C- and TC-).^ The

final part of this NBSLD-XO output contains a summary of monthly and annual

heating and cooling hours, design heating and cooling loads, and total annual

heating and cooling requirements.

1 Cooling requirements for hours with outdoor temperatures below indoor

temperatures are not examined in this report as it is assumed that increased

ventilation is generally sufficient to satisfy occupant comfort criteria

during these periods.

49
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52
Table 5.1 (Continued)

MONTHLY MONTHLY MONTHLY MONTHLY

MONTH

HEATING

HOURS

COOLING

HOURS (+)

COOLING

HOURS(-)

LOAD

HOURS

1 713 0 0 713

2 569 0 0 569

3 529 0 0 529

4 246 55 20 321

5 63 114 30 207

6 312 42 358

7 (S’ 413 57 470

8 0 282 53 335

9 26 147 48 221

in 234 n 0 ?34

11 373 0 0 373

12 634 0 0 634

TilTALS 3391 L323 ^50 4964

MAX COOLING LOAD = 16279. MONTH = 6 DAY = 18 HOUR = 12

MAX HEAT ING LOAD = 2512T._M0NTH = 12 DAY = 12 HOUR = 7

total COOLING CONSUMPTION PER DAY = 0 . 3TU

I0TAL_H£AT_IMG_ CONSUMPTION PER DAY =:

. .115151 ..RTU

TOTAL COOLING CONSUMPTION FOR 1 ROOMS = -.12634+08 BTU

J0 T AL. HEA T I N G ..X 0 InISUMP.T I OM_FQR 1 ROOMS ~ .20087+08 RTU

53
Load components are calculated only during actual heating or cooling hours.

This is an important point because the number of heating or cooling hours may

change as the envelope design, occupancy schedule, or thermostat settings

change. This is particularly true of heating hours, which may change significantly as the overall thermal integrity of the building shell is improved.

For example, in Washington, D.C., the uninsulated prototype house with night

setback to 60°F has 4301 computed heating hours in the TRY year while the

superinsulated house with night setback has 2803 computed heating hours.

Cooling hours (i.e., the number of hours in which any cooling is required)

above the indoor thermostat setpoint change relatively little as the design is

changed, since Internal and solar loads must still be removed. For the same prototype house, the uninsulated case had 1322 cooling hours while the superinsulated case had 1323 hours. (The one-hour increase in cooling hours was

due to insulating the floor, which reduced the heat-sink effect of the

crawlspace .

)

NBSLD has been validated in several studies for its accuracy in calculating

heating and cooling loads in different buildings for a variety of climatic

conditions. Two studies on unoccupied structures'*^ that correlated calculated

and measured loads showed that NBSLD can closely simulate heating and cooling

loads under controlled conditions. A more recent, and more relevant, study was conducted by Cornell University on three occupied dwelling units in Twin Rivers,

N.J.^ This study Indicates that NBSLD accurately simulates the true thermal

performance of occupied buildings when the thermal enclosure and usage schedule

are defined accurately. In the study, actual weather data and usage schedules

were used in the NBSLD program. The correlations between predicted and measured

heating requirements, both in terms of hourly load data and cumulative energy

usage, were excellent. Two of the three cases were within one percent of the

measured data; the third deviated by less than ten percent.

NBSLD and its expanded output version appear to be the best available means for

calculating component performance in buildings. However, the programs still

have certain shortcomings, primarily related to their ability to model specific

envelope components. Particular deficiencies involve the thermal modeling of

^ See table 6.9.

B. Peavy, F. Powell, and D. Burch, Dynamic Thermal Peformance of an Experimental Masonry Building , BSS 45, National Bureau of Standards,

Washington, D.C., 1972.

o B. Peavy, D. Burch, F. Powell, and C.M. Hunt, Comparison of Measured and

Computer Predicted Thermal Peformance of a Four-Bedroom Wood-Frame Townhouse , BSS 57, National Bureau of Standards, Washington, D.C., 1973.

^ Roberts, Nall, Rogers, Greenburg, "Comparison of Computer-Predicted Thermal

Loads with Measured Data from Three Occupied Townhouses , " ASliR ' F: Transactions , Vol. 83, Part I, American Society of Heating, Refrigera ug and AirConditioning Engineers, Inc., New York, 1978.

54
attics, basements, slab floors, interior partitions and furnishings. As these

algorithms are improved in the future, NBSLD-XO will provide better estimates

of the thermal performance of these components.

Section 4.1 discussed the shortcomings of modeling only the exterior envelope

surfaces without internal partitions. Despite these shortcomings, internal

partitions were not included in the NBSLD analysis of the prototype house. In

order to model partition walls with NBSLD, the heating and cooling loads in

each partitioned area must be calculated separately with no exchange of surplus

heat or cooling between or among zones. This can seriously distort the total

heating and cooling loads for all partitioned areas. South-facing zones frequently will not require heating during mid-afternoon hours and often have

excess heat available. At the same time, north-facing zones will require heating that could be offset or eliminated if the excess heat in the south-facing

zones were made available. The annual total heating requirements for all zones will therefore be significantly greater than for the house modeled as one zone

(i.e., with no partitions). Moreover, as the overall building is better insulated, this distortion becomes larger since there will be more excess heat

available in the south-facing zones. On the other hand, the distortions due

to the lack of partition walls diminish as the overall envelope becomes better

Insulated. This is because the inside surface temperatures of the walls

approach room air temperature, much as would the internal partitions, so that

radiation exchange would be minimized. In order to reduce the distortion further, 90 percent of the direct solar gain through windows is assumed to fall on the floor, rather than the other Inside envelope surfaces. (The remaining

10 percent is spread evenly over the other inside surfaces.) This is a reasonable assumption since the floor generally is darker than the walls and ceiling

and therefore absorbs the majority of sunlight reflected by other surfaces.

(However, this may exaggerate the heating energy savings and especially the

cooling energy increases due to insulating the floor.) In general, modeling

the house with no partition walls will produce smaller errors in calculating

the effects of envelope modifications than modeling the house with thermally

uncoupled zones.

Prior to calculating the annual heating and cooling requirements of the house

at its different stages of modification, the hourly crawlspace temperatures for

the year were calculated using a separate NBSLD analysis. Indoor thermostat

set points were used as indoor temperatures for this analysis. (During those

hours when the indoor temperature floated between the set points, there was no heating or cooling load, so that the resulting crawlspace temperature in those

hours would be of little or no consequence in estimating the heating and cooling

requirements of the house.) The crawlspace was modeled as an enclosed,

vented area with two air changes per hour under winter design conditions.

55
6. THERMAL ANALYSIS AND PRIORITY RANKING OF ENVELOPE MODIFICATIONS

The expanded output version of the National Bureau of Standards Load

Determination program (NBSLD-XO) was used to determine the successive reductions in heating and cooling loads for the prototype ranch house as 15 component modifications were made sequentially to the envelope design. The analysis

was carried out for 14 cities. Most of these cities were selected because they

represent a broad range of climates in the continental United States. Several

cities were added to the initial selection to provide data for a parallel

research project and were included to enlarge the data sample.

Test Reference Year^ (TRY) weather tapes, which have been selected as the most

typical of average climate data available, were used to simulate hour-by-hour

weather data in these cities. Table 6.1 lists the cities, reference year used,

and number of heating and cooling degree days (base 65 °F) in the TRY weather

data for that 3'ear.

6.1 PRIORITY RANKING OF ENVELOPE MODIFICATIONS

To determine the sequence in which the envelope modifications are to be analyzed

in this report, a preliminary ranking of modifications, in order of decreasing

cost effectiveness, was made as shown in table 6.2. (The need for such a ranking procedure is discussed in section 3.2.4.) This ordering was established for

reductions in heating requirements only; these reductions were initially computed for the 1200 ft^ single-story house, based on TRY climate data for

Washington, D.C, Modification cost data are based on table 4.6. Since the

savings in heating requirements only were considered at this point, the cost

per unit of heating energy is not important in establishing the priority ordering of the modifications. However, energy costs are important in determining

the extent to which these modifications are actually cost-effective on a life-cycle basis.

The priority ordering shown in table 6.2 is quite similar for all the climate

regions examined in this report when only heating requirements are considered.

The only significant exception is for floor insulation. Relative to the other

modifications examined, floor Insulation tends to have less than proportional

effects in reducing heating requirements in the milder climates and more than

proportional effects in the colder climates. 2 A similar priority order was found when cooling requirements were examined with the following exceptions:

1 Stamper, E., "Weather Data," ASHRAE Journal , Feb. 1977, p. 47.

2 While this result is inherently logical, it may be somewhat exaggerated

because of the modeling procedure which places 90 percent of the direct

solar gain through windows on the floor. In colder climates, the sun will

be shining more during heating hours than in milder climates, where the

majority of heating is during non-daylight hours. Thus the inside floor

surface will tend to be warmer in the colder climates over a greater

percentage of the heating hours.

56
I

Table 6.1 14 Selected Cities, TRY

Used in Thermal Analysis

Reference Year, and Degree Days

TRY DEGREE DAYS (BASE 65°F)

LOCATION YEAR HEATING COOLING

Miami 1964 130 4176

Phoenix 1951 1571 3434

San Antonio 1960 1897 2739

Fort Worth 1975 2373 2495

t San Francisco 1974 3557 35

Sacramento 1962 3144 778

Atlanta 1975 2959 1359

Washington, D.C. 1957 4161 1482

Seattle 1960 5562 143

Kansas City 1968 5058 1485

Boston 1969 5781 667

Chicago (Midway) 1974 6103 731

Madison 1974 7311 454

Minneapolis 1970 8316 919

57
Table 6.2 Ranking of Modifications^

Rank Component Modification

TO FROM

AU ACost^

1 Attic insulation R-11 R-0 0.488 $235

2 Wall insulation R-11 R-0 0.136 220

3 Attic insulation R-19 R-11 0.035 110

4 Floor Insulation R-11 R-0 0.165 280

5 Window glazing Double Single 0.57 225

6 Attic insulation R-30 R-19 0.018 170

7 Floor Insulation R-19 R-11 0.021 125

8 Sliding glass door (glazing) Double Single 0.467 180

9 Wall insulation R-13 R-11 0.007 70

10 Attic insulation R-38 R-30 0.007 110

11 Wall insulation R-19 R-13 0.018 290

12 Window glazing Triple Double 0.200 255

13 Attic insulation R-49 R-38 0.006 170

14 Wall insulation R-23 R-18 0.011 290

15 Door Storm No Storm 0.160 150

^ Modifications are ranked in decreasing order of cost effectiveness in terms

of reducing annual heating requirements as determined in the NBSLD analysis,

^ From table 4.7. These costs are in end-year 1979 dollars.

58
(1) Floor insulation actually increased the cooling requirements because it

eliminated the heat-sink effect of the crawlspace during much or all of

the cooling season. Again, this effect may be somewhat exaggerated

because the NBSLD program used assumes that 90 percent of the direct solar

gain falls on the floor. However, it is clear that a ranking based only

on reductions in cooling requirements would eliminate floor insulation

entirely.

(2) The effectiveness of attic insulation relative to the wall and window

modifications increases slightly during cooling periods, while the relative effectiveness of multiple glazing decreases slightly in the milder

summer climates.

Ideally, the reductions in both heating and cooling requirements resulting

from each modification should be considered in the priority ranking process.

More precisely, the reduction in total life-cycle heating and cooling expenditures due to each modification should be the basis for the savings used in

their ranking. This means that both the relative costs of each type of energy

used and the relative efficiency of the heating and cooling equipment installed

should be evaluated. Thus, the proper ranking should be calculated separately

for each location considered; the resulting thermal analyses would be appropriate only for those energy costs and equipment efficiencies assumed. Because

a more generalized approach is needed to accomplish the goal of this report,

the ranking of all 15 modifications in the 14 locations is based only on reductions in annual heating requirements. It is important to point out that the

priority ranking of the modifications may change as the costs of the modifications change relative to one another. Changes in the ranking will significantly

affect the subsequent savings if there is a substantial amount of interdependence among the components being modified. The extent to which this may affect

the general conclusions of this report will be discussed at a later point in

this section.

6.2 RESULTS OF THERMAL ANALYSIS

6.2.1 Heating and Cooling Requirements

Table 6.3 provides the tabulation of the annual heating requirements calculated

for the prototype house, modified cumulatively as indicated in each of the 14

locations. HO designates the basic house with its uninsulated envelope. HI

through H15 represent 15 variations of the prototype house; each sequential

variation includes all previous envelope modifications plus one additional new

one. The 14 locations are listed in order of increasing heating requirements.

Annual heating requirements in seven of these locations are plotted against

corresponding cumulative conservation costs in figure 6.1 to demonstrate

visually the relationship between energy consumption and energy conservation

investment in those climates.

In order to reduce the number of computer runs needed to calculate the effect

of all 15 modifications in each of the 14 cities, the effects of some of the

modifications were determined by interpolation in most cases. The effects of

all 15 modifications were calculated individually in three locations: San

Antonio, Texas (mild winter, warm summer), Washington, D.C. (moderate winter

59
Table 6.3 Annual Heating Requirements by City and Cumulative

Modification Level (Million Btu)

House Modifications

Designator (Cumulative) City

Miami Phoenix San Antonio Fort Worth San Francisco

HO Base House 0.978 1A.16A 20.3A9 2A.886 26.930

HI R-11 Attic 0.5A2 8.A32 13.908 16.9A5 16.981

H2 R-11 Walls 0.335 5.A99 10.578 12.7A6 11.555

H3 R-19 Attic 0.278 A. 683 9.650 11.573 10.036

HA R-11 Floor 0.258 A.A38 8.A50 10.179 7.937

H5 DBL Window 0.197 3.527 7.000 8.A50 6.082

H6 R-30 Attic 0.17A 3.17A 6.A29 7.763 5.3A2

H7 R-19 Floor 0.169 3.057 6.19A 7.A50 A. 990

H8 Double SGD 0.1A5 2.69A 5.613 6.756 A.2A3

H9 R-13 Walls 0.138 2.578 5. A2A 6.527 3.997

HIO R-38 Attic 0.129 2.AA5 5.207 6.265 3.71A

Hll R-19 Walls 0.108 2.091 A. 651 5.619 3.111

HI 2 TPL Window 0.092 1.815 A.21A 5.110 2.635

H13 R-A9 Attic 0.086 1.705 A. 036 A. 901 2.AA1

H14 R-23 Walls 0.075 1.527 3.7A9 A. 563 2.127

H15 Storm Door 0.072 1.A68 3.655 A.A53 2.025

Sacramento Atlanta Washington Seattle Kansas City

HO Base House 31.A92 32.A76 50.155 66.A77 68.301

HI R-11 Attic 21.025 23.0AA 37.2A2 A9.3A2 52.2A6

H2 R-11 Walls 15.271 17.9A2 29.863 39.2A9 A2.86A

H3 R-19 Attic 13.659 16.51A 27.789 36.A52 A0.25A

HA R-11 Floor 11.668 1A.125 23.2A2 30.061 3A.905

H5 DBL Window 9.60A 11.952 20.087 25.618 30.813

H6 R-30 Attic 8.773 11.073 18.759 23.776 29.109

H7 R-19 Floor 8.350 10.610 17.826 22.A68 27.903

H8 Double SGD 7.518 9.733 16.537 20.632 26.218

H9 R-13 Walls 7.2A1 9.A39 16.088 19.997 25.63A

HIO R-38 Attic 6.922 9.102 15.570 19.272 2A.965

Hll R-19 Walls 6.126 8.259 1A.318 17.58A 23.339

H12 TPL Window 5.A93 7.588 13.299 16.183 21 .993

H13 R-A9 Attic 5.230 7.307 12.858 15.585 21.A17

HIA R-23 Walls A. 805 6.85A 12.1AA 1A.60A 20.A75

H15 Storm Door A. 667 6.708 11.918 1A.29A 20.177

Boston Chicago Madison Minneapolis

HO Base House 81.027 81.287 102. OAO 125.890

HI R-11 Attic 63.05A 62.638 79.7A5 100.560

H2 R-11 Walls 52.A05 51.533 66.110 8A.71A

H3 R-19 Attic A9.A61 A8.A70 62.395 80.AA0

HA R-11 Floor A1.698 A1.61A 5A.121 71.115

H5 DBL Window 36.672 36.653 A8.10A 63.97A

H6 R-30 Attic 3A.603 3A.609 A5.657 61.109

H7 R-19 Floor 33.127 33.151 A3. 895 59.026

H8 Double SGD 31.0A0 31.093 A1.377 56.010

H9 R-13 Walls 30.321 30.383 AO. 513 5A.982

HIO R-38 Attic 29.503 29.575 39.538 53.830

Hll R-19 Walls 27.62A 27.629 37.160 51.065

H12 TPL Window 26.050 25.99A 35.120 A8.6A8

H13 R-A9 Attic 25.383 2A.302 3A.269 A7.653

HIA R-23 Walls 2A.283 2A.159 32.8A6 A5.969

H15 Storm Door 23.935 23.798 32.396 A5.A37

60
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6.1

Annual

heating

requirements

as

reduced

by

energy

conserving

modifications

in

selected

cities

(1200

sq.

ft.

house)
and summer), and Minneapolis, Minn, (severe winter, mild summer). In the other

11 locations, NBSLD calculations were only made for the HO, H3, H4, HIO and H15

house variations. Estimates of the heating and cooling requirements for the

other ten variations in those locations were then interpolated between those

five points, using the complete data sets from the three cities as a guide.

This procedure appears to provide excellent results for estimating the effects

of all 15 modifications in all locations.

Table 6.4 provides the incremental reduction in annual heating requirements due

to each modification in each location examined, based on the differences between

the heating requirements shown in table 6.3. Except in the mildest climates,

the greatest reductions occur for the R-11 insulation in the attic, walls, and

floor and the double glazing. In the mildest climates, the floor insulation is

relatively less effective than in the remaining climates.

Table 6.5 provides the energy savings-to--cost ratio for each modification in

each location, where energy savings are expressed in terms of a 1,000 Btu reduction in annual heating requirements. This table demonstrates the relative

stability of the ranking of modifications in terms of decreasing savings-tocost ratios for each location. However, in the milder heating climates the

floor insulation modifications are ranked too high. (In fact it will be seen

that floor insulation should not be used in those climates if air conditioning

is used.)

Table 6.6 provides the tabulation of the annual cooling requirements for the

prototype house, modified cumulatively using the priority ordering established

in the analysis of the heating requirements. In all cases, the use of insulation in the floor Increases rather than reduces annual cooling requirements.

Annual cooling requirements in seven of these locations are plotted against

corresponding cumulative conservation costs in figure 6.2.

Table 6.7 provides the reduction or increase in annual cooling requirements due

to each modification in each location based on table 6.6. Table 6.8 provides

the energy savings-to-cost ratio for each modification in each location, where

energy savings are now expressed in terms of a 1,000 Btu reduction in annual

cooling requirements. R-11 insulation in the attic and walls is the most effective means of reducing cooling requirements here. Storm doors, which show the

least savings here, would be better utilized in the non-heating season if the

glass inserts were removed and replaced with screens. However, no estimate of

the savings due to this action can be reasonably calculated. The data in table

6.8 indicate the somewhat different priority ranking that would be given to the same modifications if only cooling savings were considered.

A second series of NBSLD analyses were made for Washington, D.C. in which the

priority order was established based on reductions in annual cooling requirements rather than annual heating requirements. The calculated savings due to

the subsequent modifications were similar to those using the priority ordering

62
Table 6,4 Reduction in AHR by City and Incremental Modification (Million Rtu)

Modifications City

Miami Phoenix San Antonio Fort Worth San Francisco

R-11 Attic 0.436 5.732 6.441 7.941 9.949

R-11 Walls 0.207 2.932 3.330 4.199 5.426

R-19 Attic 0.057 0.816 0.928 1.173 1.519

R-11 Floor 0.020 0.245 1.200 1.394 2.099

DEL Window 0.061 0.911 1.450 1.729 1.855

R-30 Attic 0.023 0.353 0.571 0.687 0.741

R-19 Floor 0.005 0.117 0.235 0.313 0.352

Double: SGD 0.024 0.363 0.581 0.695 0.746

R-13 Walls 0.007 0.116 0.189 0.228 0.246

R-38 Attic 0.009 0.133 0.217 0.262 0.283

R-19 Walls 0.021 0.354 0.556 0.646 0.603

TPL Window 0.016 0.276 0.437 0.510 0.475

R-49 Attic 0.006 0.110 0.178 0.209 0.194

R-23 Walls 0.010 0.178 0.287 0.337 0.314

Storm Door 0.003 0.059 0.094 0.110 0.102

Sacramento Atlanta Washington Seattle Kansas City

R-11 Attic 10.467 9.432 12.913 17.135 16.055

R-11 Walls 5.754 5.103 7.379 10.092 9.383

R-19 Attic 1.612 1.428 2.074 2.797 2.610

R-11 Floor 1.991 2.389 4.547 6.391 5.349

DEL Window 2.064 2.173 3.155 4.444 4.092

R-30 Attic 0.831 0.878 1.328 1.842 1.703

R-19 Floor 0.423 0.463 0.933 1.308 1.206

Double SGD 0.832 0.877 1.289 1.835 1.685

R-13 Walls 0.277 0.293 0.449 0.635 0.584

R-38 Attic 0.319 0.337 0.518 0.725 0.669

R-19 Walls 0.796 0.843 1.252 1.688 1.626

TPL Window 0.633 0.672 1.019 1.401 1.346

R-49 Attic 0.263 0.280 0.441 0.598 0.576

R-23 Walls 0.425 0.453 0.714 0.980 0.942

Storm Door 0.138 0.146 0.226 0.310 0.298

Boston Chicago Madison Minneapolis

R-11 Attic 17.973 18.649 22.295 25.330

R-11 Walls 10.650 11.105 13.635 15.846

R-19 Attic 2.944 3.063 3.715 4.274

R-11 Floor 7.763 6.856 8.274 9.325

DEL Window 5.026 4.961 6.017 7.141

R-30 Attic 2.069 2.044 2.447 2.865

R-19 Floor 1.477 1.458 1.762 2.083

Double SGD 2.086 2.058 2.518 3.016

R-13 Walls 0.719 0.710 0.863 1.028

R-38 Attic 0.818 0.808 0.976 1.152

R-19 V7alls 1.879 1.946 2.378 2.765

TPL Window 1.574 1.635 2.040 2.417

R-49 Attic 0.667 0.692 0.851 0.995

R-23 Walls 1.100 1.143 1.423 1.684

Storm Door 0.348 0.361 0.450 0.532

63
Table 6.5 Reduction in AHR (1000 Btu) per Dollar of Initial Cost by

City and Incremental Modification

Modification City

Miami Phoenix San Antonio

Fort Worth San Francis

R-11 Attic 1.86 24.39 27.41 33.79 42.34

R-11 Walls 0.94 13.33 15.14 19.09 24.66

R-19 Attic 0.52 7.42 8.44 10.66 13.81

R-11 Floor 0.07 0.88 4.29 4.98 7.50

DBL Window 0.27 4.05 6.44 7.68 8.24

R-30 Attic 0.14 2.07 3.36 4.04 4.36

R-19 Floor 0.04 0.98 1.88 2.50 2.82

Double! SGD 0.13 2.02 3.23 3.86 4.15

R-13 Walls 0.11 1.66 2.70 3.26 3.52

R-38 Attic 0.08 1.21 1.97 2.38 2.57

R-19 Walls 0.07 1.22 1.92 2.23 2.08

TPL Windov/ 0.06 1.08 1.71 2.00 1.86

R-49 Attic 0.04 0.65 1.05 1.23 1.14

R-23 Walls 0.03 0.61 0.99 1.16 1.08

Storm Door 0.02 0.39 0.63 0.73 0.68

Sacramento Atlanta Washington Seattle Kansas C

R-11 Attic 44.54 40.14 54.95 72.92 68.32

R-11 Walls 26.15 23.19 33.54 45.87 42.65

R-19 Attic 14.66 12.98 18.85 25.43 23.73

R-11 Floor 7.11 8.53 16.24 22.82 19.10

DBL Window 9.17 9.66 14.02 19.75 18.19

R-30 Attic 4.89 5.17 7.81 10.83 10.02

R-19 Floor 3.38 3.71 7.46 10.47 9.65

Double SGD 4.62 4.87 7.16 10.20 9.36

R-13 Walls 3.96 4.19 6.41 9.07 8.34

R-38 Attic 2.90 3.07 4.71 6.59 6.08

R-19 Walls 2.75 2.91 4.32 5.82 5.61

TRL Window 2.48 2.63 4.00 5.50 5.28

R-49 Attic 1.55 1.65 2.59 3.52 3.39

R-23 Walls 1.47 1.56 2.46 3.38 3.25

Storm Door 0.92 0.98 1.51 2.07 1.99

Boston Chicago Madison Minneapolis

R-11 Attic 76.48 79.36 94.87 107.79

R-11 Walls 48.41 50.48 61.98 72.03

R-19 Attic 26.76 27.84 33.77 38.85

R-11 Floor 27.72 24.49 29.55 33.30

DBL Window 22.34 22.05 26.74 31.74

R-30 Attic 12.17 12.02 14.40 16.85

R-19 Floor 11.81 11.66 14.10 16.66

Double SGD 11.59 11.43 13.99 16.76

R-13 Walls 10.27 10.14 12.33 14.69

R-38 Attic 7.44 7.35 8.87 10.47

R-19 Walls 6.48 6.71 8.20 9.53

TPL Window 6.17 6.41 8.00 9.48

R-49 Attic 3.93 4.07 5.00 5.85

R-23 Walls 3.79 3.94 4.91 5.81

Storm Door 2.32 2.41 3.00 3.55

64
Table 6.6 Annual Cooling Requirements by City and Cumulative Modification Level

(Million Btu)

House Modifications

Designator (Cumulative) City

Miami Phoenix San Antonio Fort Worth San Francisco

HO Base House 45.512 51.511 32.307 32.168 1.111

HI R-11 Attic 41.657 44.639 28.481 28.130 0.894

H2 R-11 Walls 38.922 37.564 25.774 25.209 0.731

H3 R-19 Attic 37.959 35.511 24,820 24.192 0.680

H4 R-11 Floor 39.508 36.688 25.769 25.091 0.842

H5 DBL Window 38.881 34.965 25.150 24.451 0.810

H6 R-30 Attic 38.228 34.060 24.501 23.790 0.781

H7 R-19 Floor 38.327 34.144 24.558 23.845 0.808

H8 Double SGD 37.961 33.194 24.196 23.471 0.785

H9 R-13 Walls 37.784 32.908 24.020 23.292 0.776

HIO R-38 Attic 37.515 32.533 23.753 23.020 0.764

Hll R-19 Walls 36.933 31.553 23.203 22.447 0.732

H12 TPL Window 36.459 30.388 22.768 21.984 0.706

H13 R-49 Attic 36.209 29.980 22.531 21.738 0.696

H14 R-23 Walls 35.978 29.565 22.314 21.511 0.690

HI 5 Storm Door 35.915 29.407 22.256 21.449 0.687

Sacramento Atlanta Washington Seattle Kansas City

HO Rase House 16.205 14.772 14.794 1.806 17.532

HI R-11 Attic 12.784 12.046 12.393 1.452 15.050

H2 R-11 Walls 10.461 10.413 10.914 1.191 13.510

H3 R-19 Attic 9.623 9.771 10.349 1.108 12.924

H4 R-11 Floor 10.983 10.601 11.466 1.350 14.158

H5 DBL Window 10.582 10.358 11.209 1.301 13.860

H6 R-30 Attic 10.077 10.015 10.834 1.256 13,443

H7 R-19 Floor 10.286 10.130 11.004 1.296 13.623

H8 Double SGD 10.046 9.978 10.847 1.260 13.441

H9 R-13 Walls 9.913 9.889 10.750 1.247 13.333

HIO R-38 Attic 9.705 9.748 10.596 1.228 13.162

Kll R-19 Walls 9.277 9.456 10.284 1.173 12.817

H12 TPL Window 8.970 9.261 10.080 1.129 12.585

HI 3 R-49 Attic 8.784 9.137 9.944 1.112 12.435

H14 R-23 Walls 8.618 9.028 9.824 1.100 12.302

HI 5 Storm Door 8.577 9.003 9.797 1.095 12.271

Boston Chicago Madison Minneapolis

HO Base House 5.124 6.658 5.928 9.490

HI R-11 Attic 4.385 5.499 4.956 7.936

H2 R-11 Walls 3.857 4.702 4.277 6.905

H3 R-19 Attic 3.684 4.430 4.049 6.540

H4 R-11 Floor 4.279 5.088 4.651 7.513

H5 DBL Window 4.174 4.948 4.531 7.321

H6 R-30 Attic 4.064 4.791 4.404 7.082

H7 R-19 Floor 4.158 4.895 4.499 7.236

H8 Double SGD 4.084 4.798 4.415 7.109

H9 R-13 Walls 4.052 4.754 4.378 7.044

HIO R-38 Attic 4.007 4.690 4.326 6.946

Hll R-19 Walls 3.894 4.533 4.192 6.724

H12 TPL Window 3.805 4.414 4.090 6.565

H13 R-49 Attic 3.767 4.358 4.043 6.479

H14 R-23 Walls 3.738 4.313 4.012 6.407

H15 Storm Door 3.728 4 . 300 4.000 6.388

65
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CUMULATIVE

MODIFICATION

COSTS 1

1979

DOLLARS |
Table 6,7 Reduction in ACR by City and Incremental Modification (Million Rtu)

Modification City

Miami Phoenix San Antonio Fort Worth San Francisco

R-11 Attic 3.855 6.872 3.826 4.039 0.217

R-11 Walls 2.736 7.076 2.707 2.921 0.163

R-19 Attic 0.963 2.053 0.954 1.017 0.051

R-11 Floor -1.549 -1.177 -0.949 -0.899 -0.162

DEL Window 0.627 1.723 0.619 0.641 0.032

R-30 Attic 0.653 0.905 0.649 0.661 0.029

R-19 Floor -0.099 -0.084 -0.057 -0.055 -0.027

Double SGD 0.366 0.951 0.362 0.374 0.024

R-13 Walls 0.177 0.286 0.176 0.180 0.009

R-38 Attic 0.269 0.375 0.267 0.272 0.012

R-19 Walls 0.582 0.980 0.550 0.573 0.032

TPL Window 0.473 1.166 0.435 0.462 0.026

R-49 Attic 0.251 0.408 0.237 0.247 0.009

R-23 Walls 0.231 0.415 0.217 0.227 0.007

Storm Door 0.063 0.157 0.058 0.062 0.003

Sacramento Atlanta Washington Seattle Kansas City

R-11 Attic 3.421 2.726 2.401 0.354 2.482

R-11 Walls 2.323 1.633 1.479 0.262 1.540

R-19 Attic 0.838 0.642 0.565 0.083 0.586

R-11 Floor -1.360 -0.830 -1.117 -0.242 -1.234

DBL Window 0.401 0.243 0.257 0.049 0.299

R-30 Attic 0.506 0.342 0.375 0.046 0.417

R-19 Floor -0.209 -0.115 -0.170 -0.041 -0.180

Double SGD 0.240 0.152 0.157 0.036 0.181

R-13 Walls 0.133 0.090 0.097 0.014 0.108

R-38 Attic 0.208 0.141 0.154 0.019 0.171

R-19 Walls 0.428 0.292 0.312 0.055 0.345

TPL Window 0.307 0.195 0.204 0.045 0.232

R-49 Attic 0.186 0.124 0.136 0.017 0.150

R-23 Walls 0.167 0.108 0.120 0.012 0.133

Storm Door 0.041 0.025 0.027 0.005 0.031

Boston Chicago Madison Minneapolis

R-11 Attic 0.739 1.159 0.972 1.554

R-11 Walls 0.528 0.797 0.679 1.031

R-19 Attic 0.173 0.272 0.228 0.365

R-11 Floor -0.595 -0.658 -0.602 -0.973

DBL Window 0.105 0.140 0.120 0.192

R-30 Attic 0.110 0.156 0.128 0.239

R-19 Floor -0.094 -0.104 -0.095 -0.154

Double SGD 0.075 0.097 0.084 0.127

R-13 Walls 0.032 0.044 0.037 0.065

R-38 Attic 0.045 0.064 0.052 0.098

R-19 Walls 0.113 0.157 0.134 0.222

TPL Window 0.089 0.119 0.102 0.159

R-49 Attic 0.038 0.056 0.047 0.086

R-23 Walls 0.029 0.045 0.031 0.019

Storm Door 0.010 0.013 0.012 0.072

67
Table

Modification

6.8 Reduction in ACR (1000

by City and Incremental

Btu) per Dollar

Modification

City

of Initial Cost

Miami Phoenix San Antonio Fort Worth San Francisco

R-11 Attic 16.40 29.24 16.28 17.19 0.92

R-11 Walls 12.43 32.16 12.30 13.28 0.74

R-19 Attic 8.75 18.66 8.67 9.24 0.46

R-11 Floor -5.53 -4.20 -3.39 -3.21 -0.58

DEL Window 2.78 7.66 2.75 2.85 0.14

R-30 Attic 3.84 5.32 3.82 3.89 0.17

R-19 Floor -0.79 -0.68 -0.46 -0.44 -0.22

Double SGD 2.03 5.28 2.01 2.08 0.13

R-13 Walls 2.53 4.08 2.51 2.57 0.13

R-38 Attic 2.44 3.41 2.43 2.47 0.11

R-19 Walls 2.01 3.38 1.90 1.98 0.11

TPL Window 1.86 4.57 1.71 1.81 0.10

R-49 Attic 1.47 2.40 1.39 1.45 0.06

R-23 Walls 0.80 1.43 0.75 0.78 0.02

Storm Door 0.42 1.05 0.39 0.41 0.02

Sacramento Atlanta Washington Seattle Kansas City

R-11 Attic 14.56 11.60 10.22 1.50 10.56

R-11 Walls 10.56 7.42 6.72 1.19 7.00

R-19 Attic 7.62 5.84 5.14 0.75 5.33

R-11 Floor -4,86 -2.96 -3.99 -0.86 -4.41

DEL Window 1.78 1.08 1.14 0.22 1.33

R-30 Attic 2.97 2.01 2.21 0.27 2.45

R-19 Floor -1,67 -0.92 -1.36 -0.32 -1.44

Double SGD 1.33 0.84 0.87 0.20 1.01

R-13 Walls 1.90 1.28 1.39 0.20 1.55

R-38 Attic 1.89 1.28 1.40 0.17 1.56

R-19 Walls 1.48 1.01 1.08 0.19 1.19

TPL Window 1.20 0.77 0.80 0.18 0.91

R-49 Attic 1.09 0.73 0.80 0.10 0.88

R-23 Walls 0.57 0.37 0.41 0.04 0.46

Storm Door 0.27

Eoston

0.17

Chicago

0.18

Madison

0.03

Minneapolis

0.20

R-11 Attic 3.15 4.93 4.14 6.61

R-11 Walls 2.40 3.62 3.09 4.69

R-19 Attic 1,58 2.47 2.07 3.32

R-11 Floor -2.12 -2.35 -2.15 -3.47

DEL Window 0.47 0.62 0.53 0.85

R-30 Attic 0.64 0.92 0.75 1.41

R-19 Floor -0.75 -0.83 -0.76 -1.23

Double SGD 0,42 0.54 0.47 0.71

R-13 Walls 0.45 0.63 0.53 0.93

R-38 Attic 0.41 0.58 0.47 0.89

R-19 Walls 0.39 0.54 0.46 0.77

TPL Window 0,35 0.47 0.40 0.62

R-49 Attic 0.22 0.33 0.28 0.51

R-23 Walls 0.10 0.15 0.11 0.25

Storm Door 0.06 0.09 0.08 0.13

68
for heating savings, except that floor insulation is not used.^ As a result,

the ranking based on reductions in heating requirements alone can be used with

considerable confidence.

Tables 6.9 and 6.10 show the number of annual hours during which heating and

cooling loads, respectively, actually occurred in the NBSLD calculations.

Heating hours are shown for five variations of the basic prototype house (HO,

H3 , H4, HIO, and H15, the five variations actually modeled with NBSLD in all

14 locations examined). Cooling hours where the outdoor temperature is greater

than or equal to the thermostat setpoint (tQ t^^) vary insignificantly as the

envelope is upgraded. Improvements in the thermal integrity of the envelope

significantly reduce the number of hours during which space heating requirements occur. This is because the balance point, that is, the outdoor temperature below which heating is required, is reduced as the rate of heat loss from

the envelope is reduced while solar and internal heat gains are held constant.

Approximate balance points have been calculated and these are discussed in

section 7.

Economic analyses to determine optimal combinations of design modifications

will be discussed in section 8. The remainder of this section outlines some

of the other factors that might influence the envelope design and operation,

based on the NBSLD analyses made for this report.

6.2,2 Maximum Hourly Heating and Cooling Loads

Tables 6.11 and 6,12 provide the calculated maximum hourly heating (with night

setback) and cooling loads respectively for the base case (HO) and four modified variations (H3, H4 , HlO, H15) of the prototype house for the 14 locations

examined. These are the maximum hourly loads corresponding to the annual

heating and cooling requirements shown in tables 6.3 and 6.6. Figures 6,3 and

6.4 demonstrate, in graphic form, the relationship between maximum heating and

cooling loads, respectively, and the overall level of energy conservation

investment in the building envelope. Note that the range of maximum loads is

significantly less than the range of annual heating and cooling requirements,

particularly for the latter.

Although the modifications considered significantly affect maximum heating and

cooling requirements, the Incremental effects are relatively small as the less

cost-effective measures are implemented. Moreover, in the majority of cases,

space heating and cooling equipment capacities do not vary enough to take

advantage of small reductions in design loads. If a decrease in the maximum

load allows the use of smaller equipment at a cost savings to the building

user, this should be considered in a benefit-cost analysis in incremental

envelope modifications.

^ The removal of floor Insulation from the ordering of modifications tended to

result in somewhat smaller heating savings due to the subsequent modification

of the other envelope components in the NBSLD simulations. However, the

validity of this result is questionable due to the nature of the radiation

exchange algorithm in NBSLD, the lack of interior partitions, and the

modeling of direct solar radiation on the floor.

69
Table 6.9 Annual Heating Hours Calculated for 1200 Ft^ House in

Selected Cities with Night Setback^

City

Heating Hours

House Variation

HO H3 H4 HIO H15

Miami 205 91 89 58 34

Phoenix 2084 1264 1239 879 637

San Antonio 2344 1821 1730 1438 1241

Fort Worth 2665 2133 1977 1580 1335

San Francisco 4925 3452 3055 2032 1345

Sacramento 4156 3076 2878 2260 1831

Atlanta 3181 2615 2411 2006 1761

Washington, D.C. 4301 3849 3553 3110 2803

Seattle 6634 6065 5634 4826 4312

Kansas City 4284 3893 3653 3297 3049

Boston 5288 4941 4598 4197 3912

Chicago 5144 4797 4534 4158 3880

Madison 5678 N/A 5101 4720 4448

Minneapolis 5492 5264 5060 4766 4593

^ Based on NBSLD analysis, TRY weather data, and the operational profile

outlined in section 4.1.

70
Table 6.10 Annual Cooling Hours Calculated for 1200 Ft^ House

in Selected Cities^

Cooling Hours

City House Variation

HO H3 - H15

Miami 4040 4050

Phoenix 3136 3140

San Antonio 2477 2478

Fort Worth 2374 2376

San Francisco 94 94

Sacramento 1104 1104

Atlanta 1102 1102

Washington, D.C. 1322 1323

Seattle 164 164

Kansas City 1455 1459

Boston 507 508

Chicago 605 605

Madison 583 583

Minneapolis 841 841

^ Based on NBSLD analysis, TRY weather data, and the operational profile

outlined in section 4.1.

71
The relationship between annual heating requirements and maximum hourly heating

loads is plotted in figure 6.5, based on the data presented in tables 6.3 and

6.11. The relationships are shown as linear to facilitate plotting of the

data. In fact, there tends to be a high degree of linearity between the two

variables, with some tendency to jump downward at the point where the floor

insulation is added. In addition, for those cities in the lower left corner of

the figure, there tends to be some curvature toward the origin. Data for the

cities of Seattle, San Francisco, and Boston all lie significantly above the

general trend, indicating that the maximum heating loads for those cities are significantly lower than for other cities that have the same annual heating

requirements. This is expected since the winter climate in these three cities

is moderated by the nearby ocean.

In general, there is a significant, but non-proportional, relationship between

maximum heating requirements and annual heating requirements. A reduction in

annual heating requirements is accompanied by a less than proportional decrease

in maximum heating load. This implies that properly sized heating equipment

will have relatively more part-load operating time as the overall envelope

becomes better insulated, since the average hourly heating load (even after

adjusting for the decrease in the number of heating hours) decreases faster

than the maximum heating load. Vfhen the part-load operating efficiency of the

heating equipment is less than the full-load efficiency, the seasonal performance of the equipment probably will be reduced. As a result, the actual

energy savings resulting from the envelope modifications may be somewhat less

than proportional to the reduction in heating requirements.

The relationship between annual cooling requirements (to > tj^) and maximum

cooling loads is plotted in figure 6.6. Again the relationships are shown as linear although, in fact, there tends to be some kinking at the point where

floor insulation is added. From this figure, it can be seen that the ratio of

annual cooling requirements to maximum cooling load tends to vary to a much

greater extent than does the ratio of annual heating requirements to the

maximum heating load.

The general relationship between annual cooling requirements and maximum

cooling loads is also significant. A reduction in annual cooling requirements

is accompanied by a greater than proportional decrease in design cooling load.

This implies that properly-sized cooling equipment will have relatively less

part-load operating time as the overall envelope becomes better insulated,

especially where mechanical cooling is not used when the outdoor temperature

is below the maximum allowable indoor temperature. This reduction in partload operating time probably will Increase the potential for energy savings

resulting from the envelope modifications.

6.2.3 Window and Wall Design by Orientation

The expanded output version of the NBSLD program used in this report provides

data on the thermal performance of each of the envelope components that contributes to the heating and cooling loads of the prototype house. These data provide calculated heat gains and losses through the inside surface of the envelope

during actual heating and cooling hours, integrated over the entire year. Such

72
Table 6.11 Maximum Heating Loads for Selected Prototype

Variations by City (Btu/hr)

PROTOTYPE VARIATION

With Night Setback

HO H3 H4 HIO H15

Miami 19825 10855 10105 7179 5684

Phoenix 26200 14387 13856 10369 8438

San Antonio 32015 19886 18609 14317 12218

Fort Worth 35210 22658 21315 16754 14789

San Francisco 21025 13109 11887 9213 7665

Sacramento 33562 22197 20733 16379 14353

Atlanta 38233 23898 22431 17688 15181

Washington 43417 29439 27525 22100 19498

Seattle 31252 20282 19174 15027 13143

Kansas City 57087 38171 36443 29728 26038

Boston 48421 32816 30647 24684 21769

Chicago 56600 37698 35569 28917 25489

Madison 66725 45350 42743 35133 31192

Minneapolis 76538 53101 49953 41414 37011

Table 6.12 Maximum Cooling Loads for Selected Prototype

Variations by City (Btu/hr)

TV PROTOTYPE VARIATION

HO H3 H4 HIO H15

Miami 29553 20205 21520 19828 18735

Phoenix 39166 20965 22273 22352 20964

San Antonio 29192 18236 19601 17647 16495

Fort Worth 34952 19216 21080 18818 17325

San Francisco 20022 12366 16519 15137 13920

Sacramento 33426 16848 17324 15601 14321

Atlanta 30423 15601 18418 16359 14832

Washington 31089 15838 16687 14603 13217

Seattle 25029 13946 15362 13293 11908

Kansas City 29243 18703 19535 17671 16519

Boston 21456 14979 16127 14506 13517

Chicago 29849 16295 17805 15703 14343

Madison 24451 16100 16802 14854 13714

Minneapolis 23773 18432 19387 15190 14037

73
BOSTON

WASHINGTON

O.C.

I M/nial 0V01 9NI1V3H WnNIXVW

CUMULATIVE

MODIFICATION

COSTS 1

1979

DOLLARS ]

Figure

6.3

Maximum

heating

load

as

reduced

by

energy

conserving

modifications

in

selected

cities

(with

night

setback)
H14

H15

CO

C«J

uo

( M/n^a ) QV01 9NI1003 NHNIXVN

tr> CM

&cc

•H>

Ol

vD

0)U

3

5C

•H

tc-i

75

CUMULATIVE

MODIFICATION

COSTS 1

1979

DOLLARS |
MINNEAPOLIS

ocn CM ^ O)

Ooo CD m CO

o<N

I nis NOmiW I SlN3W3ainD3d 9NI1V3H IVRNNV

6

MAXIMUM

HEATING

LOAD |

Btu/hour |

Figure

6.5

Annual

heating

requirements

as

a

function

of

maximum

heating

loads

(1200

ft^

house)
00

C9

c

cue

0)

Su •HD

O"

OJ

s-< GO

GO C C 'H

'H *—

1—

O

oo

o

o

a

G

Oa

•HX

TOe

vO

OJ

V-i TO00

I m NomiN I SiN3N3Uin03il 9Nn003 IVHNNV

77

loads

(1200

ft

house)
information is useful in the envelope design process, especially with respect

to making choices between wall and window area and between north and south wall

exposures vis-a-vis east and west wall exposures. The usefulness of this com- ponent performance data is somewhat limited because of the small internal mass simulated by the NBSLD program. Nevertheless, the resulting data can provide

some insight into the thermal processes occurring during the heating and cooling

periods of small buildings.

Tables 6.13 and 6.14 provide data from the NBSLD calculations on the conductive

heat losses, solar gains, and the ratio of gains to losses through south-facing

glass integrated over all heating load hours. For those cases in which the

heat gain-to-loss ratio is greater than one, it may be assumed that an increase

in the area of south-facing windows will result in a reduction in annual heating requirements. The effects of smaller and larger south-facing window areas will be discussed below.

The v/indow heat loss and heat gain data shown in table 6.13 were calculated for

the H4 house, which included R-19 attic, R-11 wall and R-11 floor Insulation

and single glazing throughout. In all cases, Btu losses during actual heating

hours are substantially greater than Btu gains, indicating that larger windows

on the southern exposure without a corresponding reduction in window area on

the other exposures would tend to increase heating loads unless the thermal

storage capacity of the interior was increased substantially to benefit from excess heat in hours when no load exists.

Table 6.14 provides the conductive heat losses and solar gains through

south-facing windows in the HlO house. The HIO house includes R-38 attic, R-11

wall, and R-19 floor insulation, and has double glazing throughout. In this

case, the ratios indicate that larger, south-facing double-glazed windows can reduce heating requirements in the majority of locations, especially in the

colder climates where a greater proportion of total heating hours occur during

daylight. Even greater reductions could be expected if the house had a substantial thermal storage capacity.

Table 6.15 provides the annual heating requirements for the same (HlO) house

modified with 25 percent smaller and 25 percent larger south-facing glass areas. There is a good correlation between changes in heating requirements and the

corresponding ratio of gains to losses from table 6,15, It appears that a 25

percent increase in south-facing window area would reduce heating requirements

if the ratio of gains to losses is greater than about 1,05. This indicates

that not all of the solar gain is useful in offsetting conductive heat losses

through the window; some of the beneficial effects of solar gains may be partially offset by an increase in conductive heat losses through the other

envelope components.

Tables 6.13-6,15 were calculated based on the assumption that the thermostat

was set back 8°F at night to 60°F. When the thermostat is not set back, substantially more heat loss will occur during the night hours, reducing the

gain-to-loss ratio below unity in most cases.

78
Table 6,13 Annual South-Facing Window^ Heat Transfer (1000 Rtu/ft^)

During Heating Load Hours: House H4

Conduction Solar

City Loss Gain Gain/Loss

Miami 1.6 1.0 0.60

Phoenix 23.5 9.3 0.40

San Antonio 39.5 25.2 0.64

Fort Worth 46.8 33.6 0.72

San Francisco 51.3 22.0 0.43

Sacramento 56.4 32.0 0.57

Atlanta 61.2 46.5 0.76

Washington 89.2 62.0 0.69

Seattle 124.4 71.8 0.58

Kansas City 116.4 85.0 0.73

Boston 141.3 111.4 0.79

Chicago 140.4 98.8 0.70

Madison 168.5 109.5 0.65

Minneapolis 199.1 125.7 0.63

^ Window IJ = 1.13, shading coefficient == 0.8.

Table 6.14 Annual South-Facing Window^ Heat Transfer (1000 Btu/ft2)

During Heating Load Hours: House HIO

Conduction Solar

City Loss Gain Gain/Loss

Miami 0.6 0.7 1 .05

Phoenix f).8 5.6 0.57

San Antonio 17.9 17.7 0.99

Fort V/orth 20.6 20.7 1.00

San Francisco 18.8 9.9 0.53

Sacramento 25.7 21.1 0.82

Atlanta 27.9 30.2 1.08

Washington 43.2 44.1 1.02

Seattle 58.6 51.5 0.88

Kansas City 57.6 65.3 1.14

Boston 68.0 84.8 1.25

Chicago 70.2 77.5 1.10

Madison 85.6 86.9 1.01

Minneapolis 101.2 101.2 1.00

^ Window U = 0.56, shading coefficient = 0.7.

79
Table 6.15 Effect of Change in South-Facing Glass Area on Annual Heating

Requirements: House HlO^

Annual Heating Requirements

(Million Btu)

City Change in Glass Area

Gain-loss

ratio for

base housed

-25% 0 +25%

Miami 0.128 0.129 0.131 1.05

Phoenix 2.365 2.445 2.546 0.57

San Antonio 5.206 5.207 5.240 0.99

Fort Worth 6.335 6.265 6.277 1.00

San Francisco 3.622 3.714 3.868 0.53

Sacramento 6.879 6.922 7.021 0.82

Atlanta 9.212 9.102 9.080 1.08

Washington, DC 15.649 15.570 15.574 1.02

Seattle 19.201 19.272 19.430 0.88

Kansas City 25.142 24.965 24.887 1.14

Boston 29.875 29.503 29.231 1.25

Chicago 29.736 29.575 29.505 1.10

Minneapolis 53.836 53.830 53.902 1.00

^ Base design has 72 ft^ of south-facing glass.

^ From table 6.16.

80
Table 6.16 Annual South-Facing Window^ Heat Transfer (1000 Btu/ft^)

During Cooling Hours: House HIO

Conduction Solar

City Gain Gain Total Gain

Miand 4.3 62.3 66.6

Phoenix 14.4 61.3 75.7

San Antonio 6.5 34.4 40.9

Fort Worth 5.9 39.4 45.3

San Francisco 0.0 4.3 4.3

Sacramento 3.0 26.8 29.8

Atlanta 0.9 19.7 20.6

Washington 2.5 18.1 20.6

Seattle 0.3 3.7 4.0

Kansas City 3.0 23.5 26.5

Boston 0.8 9.6 10.4

Chicago 0.9 11.5 12.4

Madison 0.7 9.5 10.2

Minneapolis 1.6 16.8 18.4

3 Window U = 0.56, shading coefficient = 0.35.

81
Increasing the area of south-facing windows may also affect cooling requirements

and these effects must be considered before such a design change is adopted.

Table 6.16 provides the annual conduction and solar gains per square foot of

south-facing glass area during cooling hours for the HIO house (U = 0.56,

shading coefficient = 0.35). These data can be adjusted to reflect other

effective shading coefficients and U-values to compute the effects of southfacing window modifications on annual cooling requirements. Increased solar

gains during cooling hours may partially offset or completely negate the

advantages of larger south-facing windows during the heating season. Therefore, the net dollar savings in combined heating and cooling costs must be

computed in order to determine whether larger or smaller windows are desirable

from an economic standpoint.

In addition to the above discussion regarding window sizing, these factors

should also be considered:

(1) All the above calculations were made based on the assumption that

windows were not covered nor otherwise modified at night. Selective

window management, such as insulated shutters, drapes, or shades,

used at night to reduce conductive heat losses, would likely make

south-facing windows more beneficial in terms of net gains during

heating hours.

(2) The calculations assume that solar gains through v/indows are circulated to offset potential or real heating loads in any part of

the house. This prevents the overheating of rooms on the south exposure while heating is required in rooms on the north exposure. If

solar gains are not circulated, they may not be as useful as assumed

in this analysis.

(3) The data in tables 6.13 through 6.16 are based on TRY climate records

for the years indicated in table 6.1, which may not be good long-term

indicators of specific climate parameters such as cloud cover and

actual solar gain.

(4) This report examined south-facing windows only because they are the ones most likely to provide net thermal benefits during the heating

season. Since the benefits of increased south-facing windows were marginal at best, it is reasonable to conclude that increases in eastwest-, or north-facing windows will increase annual heating requirements. Moreover, the solar gains on the east and west exposures during cooling hours will likely result in a further decrease in the net

annual thermal performance of windows oriented in those directions.

(5) This report does not consider the beneficial aspects of windows

other than their thermal performance. Factors such as aesthetics (for

example, an appealing view) and the possible advantages of daylighting

1 See S. R. Hastings, Window Design Strategies to Conserve Energy
resulting from larger windows should be considered before deciding on

the optimal window size.l

Component performance data can also be useful in determining the effects of wall

orientation in the building design process. Table 6.17 shows that the ratio of

total heat loss on the east and west exposures to the total heat loss on the

north and south exposures (normalized by area) is nearly unity for each location

examined. This implies that any change in building orientation (while leaving

window orientation and size unchanged) would have little or no effect on annual

heating requirements. (Only the HIO variation is shown because the relative

effects of wall orientation are not significantly changed as the envelope insulation is increased. The prototype house examined is oriented with the longer

walls (40 ft) facing north and south and the shorter walls (30 ft) facing east

and west. It appears that a square-shaped house (34.64 ft on each side) having

the same floor space (1200 ft2) with minimum possible wall area (1108.5 ft2

instead of 1120 ft2) would be optimal in terms of reduced heating requirements

since the benefits from longer north and south facing walls are insignificant.

Table 6.17 also shows the ratio of north wall heat loss to south wall heat loss.

The data suggest that significantly more heat is lost from the north wall relative to the south wall during heating hours, which may justify the use of more insulation in the north wall. On the other hand, heat loss through the east and

west walls during heating load hours appears to be nearly identical in all cases.

Table 6.18 shows wall heat gains by orientation during cooling load hours when

the outdoor temperature is greater than 78°F. During these cooling load hours,

the total heat gain per unit area is significantly greater for the east and west

wall exposures than for the north and south exposures in all locations except

San Francisco. (San Francisco has almost no annual cooling requirements.) In

addition, any sizable roof overhang on the south side would reduce heat gains

through that wall even further. Thus, in the majority of cases, the additional

heat gain on the east and west walls is high enough to warrant (from a cooling

requirement standpoint) somewhat longer walls on the north and south exposures

and correspondingly shorter walls on the east and west exposures, even if this

increases total wall area slightly for a given floor area. Hov;ever, practical

design and living considerations and the Increase in total wall area will

likely limit the extent to which an Increase in the NS/EW ratio will reduce

annual cooling requirements.

In determining the optimal wall configuration for a house with respect to shape

and orientation, it appears that total surface area is the primary consideration for heating requirements, while a significant bias towards longer walls on

the north and south exposure is warranted for cooling. Thus, the selection of

shape depends largely on whether heating or cooling costs dominate, while selection of major orientation generally favors north and south exposures unless

there are no cooling requirements at all.

1 See T. Kusuda and B. Collins, Simplified Analysis of Thermal and Lighting

Characteristics of Windows: Two Case Studies , BSS 109, National Bureau of

Standards, Washington, D.C., 1978.

83
Although the lot size, shape, and orientation will usually dictate the size,

shape, and orientation of a house, orientation can still be an important design

consideration. The shape of the envelope itself may be somewhat restricted,

but the orientation and size of the windows and the location of the daytime

activity centers within (i.e., kitchen, dining and family room) close to the sources of solar and internal heat gains in winter can have a significant

effect on the energy requirements for space heating and dayligViting

6.2.4 Relative Sources of Envelope Heat Loss and Heat Gain

The expanded version of the NBSLD computer program allows the user to identify

the sources of heat loss and heat gain that make up annual heating and cooling

requirements. Such data may be of considerable interest to the designer. However, the space available to report these sources is limited and thus only a brief summary is presented.

Table 6.19 shows the relative sources of envelope heat loss during hours V7hen

heating loads exist. Data are shown for three cities — San Antonio (mild

winter; warm summer), Washington, D.C. (moderate winter and summer), and

Minneapolis (severe winter, mild summer) — and for four versions of the prototype house — HO, H4 , HlO, and H15 — to demonstrate how the relative make-up

of heating and cooling requirements change as the thermal conductance of the

various envelope components is reduced.

It is interesting to note that as the envelope is upgraded, infiltration losses

rise from less than one-quarter to more than one-half of the total loss. (The

rate of infiltrations is not changed in the analysis.)

Table 6.20 shows the relative sources of envelope heat gain during hours when

cooling loads ( to _> t^) exist for the same locations and house variations.

Both conductive and radiative heat gains are considered, as well as internal

loads from lights, equipment and people. (The floor is excluded here because

it is not a source of heat gain but instead acts as a heat sink.) Solar gains

and internal loads together make up about 40 percent of the annual cooling

requirements in the uninsulated house (HO) and about 55 to 65 percent of the

annual cooling requirements in the superinsulated house (Hl5).

Table 6.21 provides the annual latent cooling requirements ( tQ >_ tj^)

corresponding to the total annual cooling requirements of table 6.6. (These

are needed in order to compute the sensible cooling requirements that are discussed in section 7.) These latent cooling requirements remain virtually constant as the envelope modifications are made because the number of cooling

hours (tp >_ tj^) remains constant.

6.2.5 Effect of House Size on Component Performance

The effects of envelope size on component performance and the corresponding

design considerations were not explicitly calculated in this report. However,

since envelope heat losses and gains are approximately proportional to the surface area of the envelope components, weighted by the component U-values, one can expect heating and cooling requirements per square foot of floor area to

84
Table 6.17 Annual Wall Heat Losses During Heating Hours (1000 Btu/ft^):

House HIO With Night Setback

City N+S E+W E+W/ N+S N/S E/W

Washington 10.73 10.77 1.00 1.21 1.00

San Antonio 4.42 4.38 0.99 1.15 0.98

Sacramento 6.32 6.41 1.01 1.25 0.96

Phoenix 2.38 2.33 0.98 1.14 0.99

Minneapolis 25.31 25.52 1.01 1.17 0.99

Fort Worth 4.89 4.81 0.98 1.19 0.99

Chicago 17.12 17.30 1.01 1.22 0.99

Boston 16.33 16.45 1.01 1.19 1.01

Atlanta 6.79 6.56 0.97 1.13 1.00

Seattle 14.98 15.02 1.00 1.17 0.99

Miami 0.18 0.18 0.96 1.09 1.00

Kansas City 13.97 14.12 1.01 1.21 0.99

San Francisco 4.33 4.11 0.97 1.20 1.94

Madison 21.19 81.35 1.01 1.20 0.99

Table 6.18 Annual

House

City

Wall Heat

HIO

N+S

Gains During

E+W

Cooling Hours (1000 Btu/ft2)

E+W/N+S N/S E/W

Washington 1.71 2.47 1.45 0.52 1.05

San Antonio 3.21 4.48 1.40 0.64 0.97

Sacramento 2.44 3.11 1.28 0.45 0.98

Phoenix 7.93 10.20 1.29 0.59 1.06

Minneapolis 1.08 1.49 1.38 0.39 0.99

Fort Worth 3.58 4.83 1.36 0.61 1.11

Chicago 0.76 1.04 1.37 0.39 1.09

Boston 0.51 0.67 1.31 0.40 1.01

Atlanta 1.35 2.22 1.64 0.43 1 .08

Seattle 0.28 0.37 1.30 0.37 0.88

Miami 3.40 4.79 1.41 0.56 1.20

Kansas City 1.99 2.70 1.35 0.51 0.97

San Francisco 0.17 0.17 0.98 0.45 0.86

Madison 0.79 1.01 1.35 0.14 1.00

85
Table 6.19 Relative Sources of Heat Loss During Heating Hours

COMPONENT (ft2) Percent of Total Heat Loss

San Antonio Prototype Variation

HO H4 HIO H15

Ceiling (1200) 37.1 9.8 7.6 6.9

Walls (972.9) 20.5 24.3 17.8 14.8

Glass (127.1)1 16.1 26.2 19.3 16.6

Door (20) 1.1 1.8 2.6 2.0

Floor (1200) 2.3 4.9 5.6 6.7

Infiltration 22.9 33.0 47.1 53.0

Total 100 % 100 % 100 % 100 %

Washington, D.C. Prototype Variation

HO H4 HIO HI 5

Ceiling (1200) 33.0 10.5 7.2 6.7

Walls (972.9) 19.7 14.0 17.6 11.8

Glass (129.1)1 14.7 27.2 17.9 15.9

Door (20) 1.0 1.9 2.4 1.9

Floor (1200) 8.5 9.4 8.9 10.6

Infiltration 22.9 37.0 45.9 53.1

Total 100 % 100 % 100.% 100 %

Minneapolis Prototype Variation

HO H4 HIO HI 5

Ceiling (1200) 30.3 9.4 6.4 5.8

''alls (D72 .9) 19.6 13.1 15.3 10.8

Glass (129.1)1 14.2 25.2 16.3 14.1

Door (20) 1.0 1.2 2.2 1.6

Floor (1200) 7.8 8.6 8.2 9.5

Infiltration 27.2 42.0 51.7 58.3

Total 100 % 100 % 100 % 100 %

1 Data for glass losses do not include solar gains.

86
Table 6.20 Relative Sources of Heat Gain During Cooling Hours (to >. t^:

Component (ft2) Percent of Total Heat Gain

San Antonio Prototype Variation

HO H4 HIO HI 5

Ceiling (1200) 25.8 8.8 5.2 4.6

Walls (972.9)

Glass (127.1)

13.7 7.5 7.8 4.7

Conductive 2.3 5.4 3.5 3.0

Solar 11.1 14.9 14.2 13.9

Door (20) 0.4 0.7 . 0.8 0.6

Infiltration 19.5 26.3 28.7 30.7

Internal Loads 27.0 36.5 39.8 42.5

Total 100 % 100 % 100 % 100 %

Washington, D.C. Prototype Variation

hO H4 HIO H15

Ceiling (1200) 31.4 10.8 6.2 5.6

Walls (972.9)

Glass (127.1)

14.8 8.8 13.3 6.8

Conductive 1.2 4.2 2.8 2.6

Solar 11.6 16.7 15.3 15.6

Door (20) 0.4 0.7 0.8 0.6

Infiltration 12.0 17.4 18.2 20.3

Internal Loads 28.6 41.3 43.3 48.3

Total 100 % 100 % 100 % 100 %

Minneapolis Prototype Variation

HO H4 HIO H15

Ceiling (1200) 30.3 10.3 5.7 5.4

Walls (972.9)

Glass (127.1)

15.2 8.2 9.0 5.8

Conductive 1.2 4.0 9.8 2.4

Solar 15.3 22.2 19.6 21.1

Door (20) 0.4 0.7 0.7 0.6

Infiltration 11.4 16.5 16.7 19.6

Internal Loads 26.2 37.9 38.4 45.0

Total 100 % 100 % 100 % 100 %

87
Table 6.21 Latent Cooling Requirements for All House Variations^

Latent Cooling Requirements

City (Million Btu)

Miami 12.257

Phoenix 1.378

San Antonio 5.144

Fort Worth 4.446

San Francisco 0.0

Sacramento 0.0

Atlanta 2.057

Washington, D.C. 1.533

Seattle 0.0

Kansas City 2.804

Boston 0.677

Chicago 0.547

Madison 0.607

Minneapolis 0.913

^ This table of latent cooling requirements corresponds to the total

cooling requirements sho\-m in table 6.6. Note that these latent

cooling requirements remain constant as the modifications to the

envelope are incorporated.

88
decrease as the floor space is increased. This is because the building

surf ace-to-volume ratio decreases with increases in floor area. However,

heat loss and heat gain per unit surface area, by component, will vary very

little, regardless of the house size. This implies that the design guidelines for each component also remain constant.

In fact, the analysis is not as simple as implied here. One critical factor in

such an analysis is the number of heating and cooling load hours incurred as a function of the envelope size. Energy savings can only be realized during hours

in which there are heating or cooling loads. If the ratio of net envelope heat

losses to internal and solar heat gains decreases as the overall house size is

increased, the balance point of the house for heating will decrease and the number of heating hours will decrease correspondingly. This will reduce the potential energy savings resulting from any envelope modification as the house size

is Increased. However, it is not realistic to assume that solar and internal

gains will increase proportionally with the square footage of the floor space.

Internal heat gains are most likely a function of family size, with some downward bias as family size grows because of fixed internal heat sources such

as pilot lights, lighting, and, to some extent, cooking and refrigeration.

Moreover, family size has not been shown to increase proportionally with an increase in floor space in single-family housing.

Thus, an assumption that heating and cooling hours remain relatively constant

regardless of house size (within the limits of single-family housing) is not

unrealistic. In essence, this would require that solar and internal heat gains

increase as a function of the increase in envelope surface area rather than in

floor area. Because the number of cooling load hours (tg t^^) remains relatively constant regardless of the overall integrity of the envelope, the savings calculated per square foot of envelope area will remain essentially

constant regardless of house size and internal heat release.

Thus, the optimal insulation levels calculated in this report for a 1200 ft2,

one-story house can be generally applied to similar housing regardless of size.

However, a two-story house with the same floor area as a one-story house may

have fewer heating hours annually because of its more compact nature and, as a result, reductions in heating requirements per square foot of envelope area due

to modifications to the building envelope may be slightly less than those calculated for a one-story house, (The heat gains during those marginal heating

hours eliminated make up only a small proportion of the total heat gain during

the heating seasons.)

89
7. ADJUSTMENTS FOR CLIMATE VARIATIONS

7.1 INTERPOLATION OF ANNUAL HEATING AND COOLING REQUIREMENTS

The 14 locations used in this report have heating and cooling seasons representative of the wide range of climates in the continental TTnited States.

However, the ability to estimate annual heating and cooling requirements in

other locations and for better representations of long-term climatic conditions

in the 14-city sample is quite important. Even more important here is the ability to estimate the effects of conservation measures in reducing annual heating

and cooling requirements throughout the United States. Heating and cooling

degree day data have often been used for both these purposes, especially for

residential buildings. This section examines the usefulness of this degree day

data for interpolating heating and cooling requirements for other climates based

on NBSLD analysis for the 14 locations discussed in section 6.

Linear regression analysis was used to determine the best relationship (in a least-squares sense) between annual heating and cooling requirements and annual

heating and cooling degree days (HDD and CDD) , calculated at different base temperatures. In addition, annual cooling requirements were correlated with annual

cooling degree hours (CDH) to determine whether a better estimator of cooling

requirements could be found.

Traditionally, heating and cooling degree days have been calculated using a base

temperature of 65°F. However, as explained in section 3, the appropriate balance

point at which space heating or cooling is required is likely to change as the

building becomes better insulated, or tighter from a thermal performance standpoint. This is especially true for heating requirements, since solar gains and

internal heat generation are able to offset a greater percentage of the heat

losses as the envelope becomes better insulated. Thus, the appropriate base

temperature for calculating heating degree days falls as the building becomes

better insulated or as internal or solar gains are increased.

Table 7.1 provides HDD data computed from the Test Reference Year (TRY) tapes

used in the NBSLD analysis for the 14 cities. These data are calculated for

base temperatures decreasing at 2.5°F intervals from 65° to 42.5°F. A number

of linear regression analyses were run for the 14 cities to determine which

degree day base provided the best correlation between TRY heating degree days

and the annual heating requirements calculated in section 6. The results of

those analyses are shown in table 7.2. The best-fit heating-degree-day base

ranged from 57.5°F for the uninsulated house to 50.0°F for the superinsulated

(Hl5) house. The rate of infiltration, solar gain, and internal heat generation are constant in all cases. Thus, the change in balance point is due

entirely to the reduction in the rate of conductive heat loss through the

building envelope.

While the HO (uninsulated) house balance point of 57.5°F is significantly lower

than the base 65°F traditionally used, -it must be remembered that the indoor

temperature during heating periods was kept at 68 °F during the waking hours

and 60°F during sleeping hours, substantially below the 70°-75°F daily range

that was common at the time when the 65°F base was established. Moreover, the

90
Table 7.1 TRY Heating Degree Days to Selected Bases

Heating Degree Day Base (®F)

City 65.0 62.5 60.0 57.5 55.0

Miami 130 79 48 27 15

Phoenix 1571 1193 963 607 404

San Antonio 1897 1562 1257 994 758

Fort Worth 2373 1983 1636 1327 1048

San Francisco 3557 2702 1930 1300 813

Sacramento 3144 2578 2072 1627 1243

Atlanta 2959 2500 2080 1698 1370

Washington, DC 4161 3616 3106 2629 2184

Seattle 5562 4738 3944 3211 2553

Kansas City 5058 4507 4007 3541 3114

Boston 5781 5129 4524 3956 3441

Chicago 6103 5451 4852 4292 3768

Madison 7311 6611 5952 5341 4765

Minneapolis 8316 7689 7083 6500 5934

City 52.5 50.0 47.5 45.0 42.5

Miami 9 4 2 0 0

Phoenix 258 150 69 28 6

San Antonio 558 383 245 138 69

Fort Worth 793 563 373 228 129

San Francisco 440 206 90 37 10

Sacramento 922 649 436 277 164

Atlanta 1078 821 600 417 273

Washington, DC 1785 1428 1111 827 590

Seattle 1984 1494 1071 719 461

Kansas City 2709 2342 2004 1695 1409

Boston 2958 2524 2123 1743 1402

Chicago 3283 2834 2414 2014 1640

Madison 4230 3735 3263 2810 2391

Minneapolis 5391 4875 4395 3938 3496

91
Table 7.2 Best Linear

and Annual

Regression Results:

Heating Requirements

Heating Degree Days

Regression Equation Standard

House HDD Deviation

Variation Base Constant Slope r2 of Residuals

HO 57.5°F 1.065 0.0192 0.997 1.85

H4 55.0°F -1.488 0.0193 0.996 1.33

HIO 52.5°F -0.956 0.0098 0.995 1.06

H15 50.0°F -0.350 0.0091 0.995 0.93

92
prototype house has less leakage due to air infiltration than most existing

houses. Window areas for the prototype are also somewhat less than average.

Figure 7.1 shows the HDD data for both base 65°F and'55°F (HDD55 and HDD55 ) and

the corresponding annual heating requirements of the H4 envelope variation

(R-19 attic, R-11 wall and R-11 floor insulation, single glazing) for the 14

cities. The heating requirements fall noticeably closer to the HDD55 regression line than the HDD55 line. Moreover, the HDD55 regression line is much

closer to the zero intercept, making it a much better predictor of annual heating requirements in milder climates such as San Francisco and Miami. This high

degree of correlation implies that HDD data can be used with some confidence to

interpolate annual heating requirements for other climates, provided that the

appropriate degree day base is known. Degree day data for a wide range of calculation bases can be obtained from the National Climatic Center.! Maps of the

United States showing heating degree days calculated at four different bases

are provided in appendix D.

In contrast to the acceptance of heating degree days as an aid for calculating

annual heating requirements, cooling degree days (CDD) have not been as generally accepted for calculating annual cooling requirements. The most Important

reason for the lack of acceptance is that CDD do not adequately reflect the

differences in solar gains and internal heat generation from house to house,

which together make up a substantial portion of the total cooling load. In

addition, CDD do not reflect the range of daily temperature variation nor the

magnitude of the latent cooling load.

Although the usefulness of CDD is limited, they may serve as a reasonable

basis for interpolating cooling energy requirements for the same house operated

in the same manner between locations with known cooling requirements and CDD.

Moreover, if only sensible cooling requirements are to be estimated, one would

expect a higher estimating reliability because the poor correlation between wet

bulb temperatures and CDD is avoided. Sensible cooling requirements can be calculated by subtracting the latent cooling requirements reported in table 6.21

from the total cooling requirements reported in table 6 . 6 .

Table 7.3 provides CDD data calculated from the TRY tapes used in the NBSLD

analyses for the 14 cities. The CDD data are calculated at 2.5°F intervals

from 65° to 80°F. Several linear regressions were made for the 14 cities to

determine which temperature base best correlated CDD with annual sensible

cooling requirements (to t^). The results of those analyses are shown in

table 7.4.

Figure 7.2 shows a plot of the CDD data at bases 65° and 72.5°F and the

corresponding sensible cooling loads (to t^) for the H4 house in the 14

cities. Although the overall fit is good for the CDD base 72.5°F data, there

is still considerable variation from the regression line, especially for

! U.S. Department of Commerce, National Oceanic and Atmospheric Administration,

Environmental Data Service, National Climatic Center, "Degree Days to

Selected Bases," Ashville, N.C. 28801, (no date).

93
HDD

I

I T r

CDoor^cDioiifro<M W* VmP WP

I n;g N0I11IW I SlNaMSUinOSU 9NI1V3H IVnNNV

94

Figure

7.1

Annual

heating

requirements

as

a

function

of

HDD

and

HDD

(H4

house)
Table 7.3 TRY Cooling Degree Days to Selected Bases

Cooling Degree Day Base (°F)

City 65.0 67.5 70.0 72.5 75.0 77.5 80.0

Miami 4176 3333 2522 1769 1117 615 283

Phoenix 3434 2934 2471 2037 1651 1293 968

San Antonio 2739 2195 1708 1265 877 545 286

Fort Worth 2495 2014 1580 1194 962 575 332

San Francisco 35 13 4 1 0 0 0

Sacramento 779 504 298 161 77 32 12

Atlanta 1359 956 614 324 132 34 2 Washington, D. C. 1482 1142 830 566 344 174 72

Seattle 143 95 59 31 15 7 3

Kansas City 1485 1154 868 628 421 259 133

Boston 667 467 310 193 104 45 15

Chicago 731 507 319 186 99 49 23

Madison 454 285 165 92 55 29 11

Minneapolis 919 658 451 282 156 73 28

Table 7.4 Best Linear

and Annual

Regression Results: Cooling Degree Days

Sensible Cooling Requirements

House

Variation

CDD

Base

Regression Equation

Constant Slope r2

Standard

Deviation

of Residuals

HO 75°F 4.57 0.0268 0.941 3.28

H4 72.5“F 2.405 0.0151 0.959 2.03

HIO 72.5“F 2.214 0.0136 0.964 1.69

H15 72.5°F 1.91 0.0125 0.969 1.44

95
I ma Homiw I siN3N3ainD3d onhooo 3iaisN3s

96

Figure

7.2

Annual

sensible

cooling

requirements

as

a

function

of

CDD^^

and

CDD

^25

house)
Sacramento, a city with a relatively high daily temperature range in the summer. Note also that the CDD72.5 line does not pass as close to the zero intercept as does the CDD65 line.

An alternative approach to CDD for interpolation purposes is to use cooling

degree hours (CDH) calculated from the TRY tapes used in the NBSLD analysis.

This has the advantage of representing average hourly data rather than average

dally data, which would likely be more accurate where the variation in daily

temperature is significant. Table 7.5 provides CDH data as calculated from the

TRY tapes. The CDH data are calculated at 2.5°F intervals from 65° to 80°F.

Several linear regressions were made for the 14 cities to determine which

calculation base best correlated CDH with annual, sensible cooling requirements

(to t^). The results of those analyses are shown in table 7.6. These results

are significantly better than those for the CDD data, although the best-fit CDH

calculation bases are the same as those for CDD. The coefficient of determination (r2) is close to 1.0 and the standard deviation of the residuals is low

relative to that for the CDD analysis. Figure 7.3 provides a plot of the CDH

data base 65°F and base 72.5°F and the corresponding sensible cooling loads

(Iq t^) for the H4 house in 14 cities.

It appears that CDH data can provide a reliable basis for interpolating sensible

cooling requirements, provided that the envelope design and orientation, infiltration rate, and internal heat gains are held constant. While CDH data are not as readily available as CDD data, they can be calculated from "bin" data

which are available for a large number of cities from the National Climatic

Center.

Latent cooling requirements correlate poorly with CDD and CDH data and therefore

must be estimated separately. However, sensible cooling load data are sufficient for the analysis of changes to the building envelope which modify conductive and solar heat gains. These modifications will have little or no effect

on latent cooling loads, since the number of cooling load hours (to t^) and

infiltration rates remain virtually constant at all levels of thermal integrity.

7.2 INTERPOLATION OF CHANGES IN ANNUAL HEATING AND COOLING REQUIREMNTS

The use of degree day and degree hour data for interpolating heating and cooling

requirements for locations other than the 14 TRY locations examined greatly

extends the value of the data presented in section 6. However, it is necessary

to estimate the reduction in heating and cooling requirements resulting from

envelope modifications (rather than the requirements themselves) to provide

quantitative data for economic analysis. Since the balance point may change as

^ Data for individual cities are published in "Summary of Hourly Observations"

available from the National Climatic Center, Asheville, N.C. 28801. A sum- mary of bin data for approximately 140 cities is also available from the same source, although in unpublished form. The methodology used in this

report for calculating cooling degree hours data from bin data is reported

in appendix C.

97
Table 7.5 TRY Cooling Degree Hours to Selected Bases

Cooling Degree Hour Base (°F)

City 65.0 67.5 70.0 72.5 75.0 77.5 80.0

Miami 101655 81754 62806 45535 30348 18559 9975

Phoenix 90743 78429 67138 56960 47746 39474 32065

San Antonio 69687 56831 45088 34806 25979 18949 13476

Fort Worth 64527 53053 42427 32980 24761 18141 12853

San Francisco 4357 2726 1659 1059 682 416 214

Sacramento 31104 25295 20332 16188 12632 9639 7114

Atlanta 36104 26632 18665 12722 8264 5075 2694

Washington, D.C. 37585 29680 22729 16826 12025 9328 5381

Seattle 6482 4707 3348 2326 1575 1051 686

Kansas City 39554 31575 24577 18601 13546 9493 6277

Boston 18260 13363 9452 6458 4222 2716 1656

Chicago 20776 15418 11027 7669 5124 3292 2047

Madison 15911 11668 8330 5851 3934 2485 1458

Minneapolis 25397 19679 14721 10801 7654 5254 3406

Table 7.6 Best Linear Regression Results: Cooling ! and Annual Sensible Cooling RequirementsDegree Hours

Regression Equation Standard

House CDH Deviation

Variation Base Constant Slope r2 of Residuals

HO 75°F 1.133 1.04x10"3 0.993 1.15

H4 72.5°F 0.146 0.609x10“3 0.998 0.49

HIO 72.5°F 0.210 0.546x10-3 0.998 0.36

HI 5 72.5°F 0.090 0.501x10-3 0.998 0.36

98
I nia NOmiN I SiN3N3ain03)l SMIOOO 3iaiSN3S

99

Figure

7.3

Annual

sensible

cooling

requirements

as

a

function

of

CHD,^

and

CHD_,„

_

(H4

house)

0

j

7

/

. j
the envelope is modified, the reduction in heating or cooling requirements

may not correlate well with degree days or degree hours calculated at either

the pre-modification or post-modification balance point. In addition, the

change in the number of degree days or degree hours between different balance

points is not proportional for each location.

Regression analyses were made for three major variations of the basic house

(HO to H4, H4 to HIO, and HIO to H15), with the change in heating and sensible

cooling requirements correlated with the number of heating degree days and

cooling degree hours, respectively, over the range of calculation bases shown

in tables 7.1 and 7.5. The best correlations are shown in tables 7.7 and 7.8

for heating and cooling, respectively.

It is important to note that in table 7.7 the best degree-day-base correlation

for reductions in heating requirements is significantly higher than the best

degree-day-base correlation for the heating requirements themselves. The best

correlation was found to be 62.5°F for the first group of modifications (HO to

H4) and 60°F for the subsequent modifications. This implies that in developing

recommendations for optimal levels of conservation in envelope design, the best

heating degree day base is approximately 5°F to 7.5°F higher than that base

most appropriate for estimating actual heating requirements.

Similarly, table 7.8 shows the cooling degree hour base which correlates most

closely with reductions in sensible cooling requirements (tQ This base

temperature is significantly higher than the base temperature which correlated

most closely with absolute cooling requirements shown in table 7.6, This

implies that recommendations for energy conservation modifications aimed at

reducing cooling requirements above the themostat setpoint should be based on cooling degree hours calculated at approximately the thermostat setpoint (78°F).

Generalized data bases for estimating reductions in annual heating and cooling

requirements, by climate zone, are shown in tables 7,9 and 7.10, respectively.

In table 7.9, the reductions in annual heating requirements (AAHR) in Btu per

square foot of component area for each of the 15 modifications, are shown as a function of HDD5o» (Heating degree days calculated at base 60°F are used rather

than the traditional 65°F base because it provides a better basis for estimating AAHR. A map of HDD^q bands for the United States is shown in appendix C.)

The reductions shown in table 7.9 are based on linear regression equations,

using HDDgQ in all cases, but are adjusted manually below 1000 HDD^q in order

to provide better estimates in the low end.

In table 7.10, the reductions in annual cooling requirements (AACR), in Btu per

square foot of component area for the same modifications, are shown as a function of CDH77 ^ 5

. (^®^77,5 data for 41 locations in the United States have

been calculated and are provided in table C-1 of appendix C.) The AACR data

shown in table 7.10 were calculated based on regression equations estimated

using CDD 77^5 cases. (Note that no cooling savings are estimated in

regions with less than 2000 CDH since central air conditioning is seldom used

in those regions.)

100
Table 7.7 Best Linear Regression Results: Heating Degree Days

and Reductions in Annual Heating Requirements

Change HDD

Base

Regression Equation

Constant Slope r2

Standard

Deviation

of Residuals

HO to H4 62. 5F 0.729 7.20x10“3 0.997 0.835

H4 to Hll 60. OF -0.103 2.50x10-3 0.993 0.426

Hll to H15 60. OF -0.141 1.22x10-3 0.994 0.186

Table 7 .8 Best

and

Linear Regression Results: Cooling Degree Hours

Reductions in Annual Cooling Requirements

Change CDH

Base

Regression Equation

Constant Slope r2

Standard

Deviation

of Residuals

HO to H4 77. 5F 0.438 3.56x10-'^ 0.959 0.755

H4 to HIO 77. 5F 0.077 1.04x10“'^ 0.991 0.101

Hll to H15 77. 5F 0.219 0.74x10"'^ 0.960 0.154

101
Table

7.9

Incremental

Reduction

in

AHR

(1000

Btu/Ft )

by

Modification

and

HDD^q

Heating

Degree

Days

(Base

60°F)

CN

m vO to 00 NO CO ON o CvJ m v£i 00 t-H rv. I-H CO o n£> CM o ON CO r-* CM CJN o • 0 0 0 0 0 0 0 0 0 o^ CO o CO CN o CVJ CM

00 CO nC o CM 00 CM o CM f-H o CO CO o CM vD CM o 00 o o vO 00 i-H On vD CM CO CTn o 0 0 0 0 0 0 0 0 0 0 00 CM O 00 CO »-H <Tn CN

CO CM vO ON C3N 00 00 NO CO o o m CO CO NO 00 CM CM o 00 NO C3N 00 <r o 00 o 0 0 0 0 0 0 0 0 0 0 -H CO CM C o NO CM 00

C^J

00 o 00 NO 00 CO CM CM o vO m o CO On "d- o o^ 00 ON o 0 0 0 0 0 0 0 0 0 0 vD 00 CO CM o o o CM *-H

f*H

On 00 CJN 00 NO o CO UO to CTn On m m in i-H NO o r—

vO nD LO C3N

O CM 00 o 0 0 0 0 0 0 0 0 0 0 LO vD CM O o o CM I-H m f—

On 00 vO 00 in CM 00 o ON o to o NO 00 o CN) LO NO NO CTn m o 0 0 0 0 0

•<r CO CVJ r-H o c CTn o o

On

>d* NO 00 NO 00 ON o o o in ^H 'O’ m CO o 1-H ON o NO o CO CN CO NO o 0 0 0 0 . . 0 0 0 0 . CO o o o O o CO o o 00 tn m ON m CM CM On o CO 00 o CM CO <JN UO CO f-H o vO ^H CM CM CM CM 00 o o 0 0 0 . . . . . . 0 0 n! f—* o o O m o o o CM O

UO CO CTN -d- CO ON CO o o\ CJN m CO o CTN o ON UO o NO CO 1-H ON f-H ^H o 0 . . 0 0 0 0 . 0 0 f-H <3* o o o o o o O o o O CTn 00 m UO o- c CTn 00 00 o ON CO f— o o vD o CM O CO o m 0 0 0 . . 0 . 0 « 0 . CM O o o o I-H o o o O o c d c o o o CO c o •H •H •H CO 3 o •H 4-1 CTN o 00 CTN rH U ^H CO ON CO 3 4-1 ^H ON O

•Hu CC ^H CO CO iH CO 1-H CM o cd f-H o 0

4-1

u r—

1 1 1 1 cii CO iH 1 1 1 1 o rH 1 1 H3 o

cx <3 3 pci Pi Pi 3 Pi pc! Pi rH 3 pi Pi 3 o Cfi CO Fih CO *rl T3 c 3 3 3 M M M 3

102

DBLGLZ

6.30

12.184

23.964

35.744

47.525

59.305

71.086

82.866

94.646

106.427

TPLGLZ

1.75

3.356

7.394

11.432

15.470

19.508

23.546

27.584

31.622

35.660

DBLSGD

5.10

10.404

21.252

32.100

42.948

53.796

64.644

75.492

86.340

97.189

STMDR

1.75

3.151

7.048

10.945

14.841

18.738

22.635

26.531

30.428

34.325
Table

7,10

Incremental

Reduction

In

ACR

(1000

Btu/Ft^)

by

Modification

and

CDH oo 00 CM in o IS. 00 o CO e^ o m CO r-H

O o f'H CO CO C3S 00 m OS IS o in CO o o

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f—

CM

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•—

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f'H o o o o —

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CO CJS CO o u i-H CJS > o o O CO

Q

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CO CO 'St 1—1 t|) f'H f—

f—1 CM

O 3 o o hJ 4-3 4J s

•U +J tH

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103
The data in tables 7.9 and 7.10 will serve as the principal focus of the

life-cycle cost analysis in the following section. They have been adjusted to

a square foot basis in order to make them more useful in developing general

guidelines for insulating single-family housing. In addition, they have been

grouped by component in order to facilitate subsequent analysis. However, it

should be kept in mind that the data were developed in a sequential ordering

according to a generally decreasing savings-to-cost relationship.

104
8. LIFE-CYCLE COST ANALYSIS OF SELECTED ENVELOPE MODIFICATIONS

Section 3 outlined an economic framework for determining the optimal thermal

envelope configuration for residential buildings. In particular, that section

stressed the need to calculate marginal, or incremental, dollar savings and

costs of additional modifications to the building envelope in present value,

life-cycle terras in order to determine an optimal envelope design. In sections

6 and 7 , incremental reductions in annual heating and cooling requirements were

calculated for 15 envelope component modifications. In this section, the incremental present-value, life-cycle dollar savings and corresponding costs are com- puted for each of these modifications in order to determine the extent to

which those modifications should therefore be incorporated into the building

envelope design. The solution, of course, is dependent on a number of factors,

including climate, energy prices, heating and cooling system conversion efficiencies, the costs of the modifications, the useful lifetime expectancy for

the building envelope, and the discount rate used to convert future costs or savings to present value.

8.1 dALCULATION OF PRESENT-VALUE , LIFE-CYCLE SAVINGS

The reductions in annual heating and cooling requirements calculated in sections

6 and 7 can be converted into incremental present-value, life-cycle dollar

savings as follows:

where

AAHRj^

(Pj^ UPWjfe) +

AACRj^

he

(P^, UPW*) (8-1)

ASi = the incremental present-value, life-cycle dollar savings

attributable to the ith envelope design modification,

AAHR^ = the reduction in annual heating requirements attributable

to the 1 th modification,

AACRi = the reduction in annual cooling requirements attributable

to the 1 th modification,!

X] = seasonal equipment efficiency or seasonal coefficient of

performance (COP),

P = energy price (in the same units as AAHR and AACR)

,

UPW* = modified uniform present worth factor (to relate future dollar

savings to present value), and subscripts.

! An increase in annual cooling requirements is expressed in terms of a negative reduction.

2 For a heat pump COP = SEER/3.143 Btuh/W, where SEER = seasonal energy

efficiency ratio (Btuh/W).

105
h = heating, and

c = cooling.

Equation (8-1) can be reduced to

A Si = Fj (AAHRi) + F2 (AACRi)

Ph UPWft

where Fi = , and

’^h P^ UPW*

(8-2)

(8-3)

(8-4)

This is convenient for calculation purposes because Fj and F2 are assumed to

remain constant as the overall envelope is thermally upgraded. (This implicitly

assumes that all modifications considered have the same useful life as that of

the building envelope; this may require some adjustment to the cost of some modifications in order to prolong their lives; e.g. storm doors.) Fj^ and F2

will sometimes be referred to as heating and cooling index numbers, respectively,

in the remainder of this report.

Table A-3 in appendix A provides UPW* factors for a range of discount rates,

energy price escalation rates, and lifetime assumptions that are frequently

used in the life-cycle cost analysis of buildings. Table A-4 provides the cost

per million Btu output to the conditioned space by the heating equipment for

gas, oil, and electricity as a function of unit prices and heating system

efficiencies.! Table A-5 provides the cost per million Btu output by the air

conditioning system as a function of electricity prices and the seasonal

coefficient of performance (SCOP).

F]^ and F2 can be calculated by multiplying the appropriate UPW* factor and

the cost per million Btu output for heating or cooling, respectively. For

example, A-3 shov/s that for an envelope life of 30 years, an annual rate of

energy price increase (real) of 4 percent, and a (real) discount rate of 4

percent, the UPW* is 30. Table A-4 shows that at $0.40 per therm and 70 percent seasonal efficiency, the cost per million Btu output to the conditioned

space is $5.71. Fj is therefore equal to (30 x $5.71/milllon Btu) $171.30 per

million Btu. This is, in essence, the present value of one million Btu of

heating energy saved each year over 30 years. Assuming that electricity costs

are currently $0,048 per kWh and are expected to increase annually at a real

rate of 2 percent, and that the seasonal COP for the air conditioner is 2.35,

the UPW* from table A-3 equals 22.5 and the cost per million Btu delivered from

table A-5 equals $5.96. Thus, F2 equals (22.5 x $5. 96/million Btu) $134.10 per

million Btu. In a geographic region having 4000 HDD^q and 7500 001177^5, the

! The heating system efficiency should be estimated in terms of seasonal

performance and should include distribution losses (e.g., from ductwork).

2 SCOP = Seasonal Energy Efficiency Ratio (in Btuh/W)/3.413 Btuh/W.

106
the AAHR for R-11 attic insulation (relative to R-0) is 0.0133 million Btu per

square foot and the AACR for R-11 attic insulation is 0.002 million Btu per

square foot. Thus the present-value, life-cycle savings are equal to $2.55

($171 .3/million Btu x 0.0133 million Btu + $134. 10/million Btu x 0.002 million

Btu) per square foot of attic area.

A general format for calculating incremental savings for the i-^ modification

(A Si) is shown in table 8.1. Once the Fj and F 2 values are known for a given

house in a given location, the incremental savings can be easily calculated

based on this procedure. These incremental savings are potentially useful to

the builder/buyer because they can be used to determine the maximum cost for

any modification that can be economically justified on a life-cycle cost basis.

Localized tables of incremental savings could be produced for builders and

buyers to use in the design process, sensitive to local climate factors,

energy costs, and equipment efficiencies.

8.2 CALCULATION OF PRESENT-VALUE , LIFE-CYCLE COSTS

In order to determine an optimal combination of envelope design modifications

to reduce design energy requirements, incremental dollar savings must be compared with corresponding incremental modification costs. The major component

of that incremental cost is the additional purchase cost of a new home.^ In

fact, economic analyses of energy conservation modifications seldom go beyond

this initial cost. However, the other cost components discussed briefly in

section 3 may be of some importance, depending upon the assumptions of the user. For example, replacement costs at specified intervals may be considered

necessary for some modifications (e.g., storm doors) in order to bring them

up to the same life expectancy used for the envelope in the analysis of incremental life-cycle savings. Increased maintenance and repair costs for the

modifications considered in this report are not expected to be significant.

However, for other modifications (e.g., weatherstripping) these costs may be

significant and thus these costs should be considered in a general methodology.

Replacement, maintenance and repair costs should all be converted to presentvalue terms using the appropriate equations from table 3.1.

If the increased cost of a house due to energy conservation modifications is

to be financed as part of the mortgage, adjustments can be made to determine

the present value of the mortgage payments and the present value of the income

tax savings due to interest pa5mients. Table A-1 in appendix A provides the

present value of the mortgage pa3mients for a range of discount rates, interest

rates, and repayment period, based on equal monthly payments throughout the

loan life. Table A-2 in appendix A provides the corresponding present-value

of interest payments made, discounted from the end of the year. Thus the tax

savings can be calculated as the product of the owner’s Income tax bracket

and the present-value of interest payments. For example, with a 12 percent

(nominal) discount rate and a 30-year mortgage at 10 percent (nominal) Interest

1 This increased purchase cost should include not only the nominal purchase

price but any Increase in closing costs as well.

107
Table 8.1 Calculation Procedures for Incremental Savings

(Savings per square foot of surface area)

A. Calculate Fj (heating)

(1) Price per million Btu output (from table A-4)

TD

(2) Modified Uniform Present Worth Factor (from table A-3)

T2T

= , X , = ^ , rn (2 j T35

B. Calculate F 2 (cooling)

(4) Price per million Btu output (from table A-5)

(5) Modified Uniform Present Worth Factor (from table A-3)

(5)

(6) F2 X ,

(4) (5) (6)

C. Calculate AS^

(7) AAHR^ (from table 7.9)

(7)

(8) AACR-f (from table 7.10)

( 8 )

(9) ASi = X + ^ ^

(3) (7) (6) (8) (9)

108
rate,l the present value of the mortgage pa3nnents for an additional $1000

borrowed is $894 (from table A-1), The corresponding present value of the

interest payments is $725 (from table A-2). In a 25 percent tax bracket, this

equates to a present-value tax savings of $181 (0.25x$725). Thus, the effective

present-value cost of borrowing $1000 is $713 ($894-181) in this example.

(Table A-1 shows how to find the real discount rate equivalent to the nominal

discount rates used. For a general inflation rate of 10 percent, a nominal

discount rate of 12 percent is approximately equivalent to a real discount rate

of 2 percent.)

In addition, the present value of increased property taxes and insurance costs

should be added to the cost of each modification. These costs should be calculated over the same lifetime used in calculating the life-cycle energy savings.

Appendix B describes a methodology for calculating these costs. Table B-1 in

appendix B provides factors which can be multiplied by the increased purchase

cost of a house due to energy conservation modifications in order to estimate

the present value of both property tax and insurance costs. These factors are based on the owner's discount rate, annual property tax and Insurance rates

(per dollar of actual building value), and the projected annual rate of energy

price increase over the building life used in the life-cycle cost analysis.

For example, for a building life of 30 years, a (real) discount rate of 2

percent, a (real) rate of energy price increase of 2 percent, and net property

tax rate2 plus insurance rate of 2 percent, the present value factor is 0.33.

Thus for an energy conservation modification which adds $1000 to the price of

a house, the present value of the additional property taxes and insurance

costs is estimated to be $330 (0,33 x $1000). It should be noted that, while

this factor is consistent with life-cycle cost assumptions, it may overstate

the actual change in assessment for tax and insurance purposes computed by the assessor.

It is difficult to make general conclusions about the effects of mortgage

payment adjustments and property tax and insurance cost adjustments to the

increase in initial purchase cost because of the wide variation in the variables needed to calculate these effects. In the examples shown above, where

the present-value cost of repaying $1000 over 30 years is $713 and the additional present-value property taxes and insurance cost per $1000 additional

house cost is $330, the net effect of these two adjustments is insignificant

since they nearly cancel out. The use of a real discount rate greater than 2

percent will result in a net present-value conservation cost less than the

$1000 initial cost, while the use of a lower discount rate will result in a higher present-value cost than $1000, where the other variables are held the

^ An annual inflation rate of 10 percent is assumed in reconciling the

nominal nature of the mortgage interest rate with the real nature of the

discount rate.

2 The net property tax rate is the rate adjusted for income tax savings.

Thus in a 20 percent tax bracket, a 2.5 percent property tax rate is equivalent to a 2 percent (2,5 x (1-0.2) net rate. Effective residential tax rates

for selected cities are shown, in table B-2 in appendix B.

109
same. However, a higher tax bracket will reduce the net present-value cost; a higher interest rate will increase the net present-value cost; a higher property

tax rate will Increase the net present-value cost. In many cases these adjustments may add complexities to the economic analysis that are not justified

from the average homeowner's standpoint because of the uncertainties involved.

A general format for calculating incremental costs for the i^^ energy

conservation modification is shown in table 8.2. When the total incremental

present-value cost for the i^^ modification has been calculated, it can be

compared with the incremental present-value savings (calculated in table 8 . 1 ) for the corresponding modification. All Incremental modifications with

incremental savings greater than or equal to incremental costs are included in

the optimal envelope configuration.

8.3 CALCULATION OF OPTIMAL ENVELOPE COMPONENT MODIFICATIONS

Given the incremental savings and costs for the modifications considered, the

optimal level of modification to any building envelope component analyzed can be

found by incorporating all modifications with incremental savings greater than

or equal to incremental costs into the component specifications. Table 8.3

shows an example of this decision process for the six components analyzed in

sections 6 and 7. This example is based on a location with 4000 HDD^q and

7500 CDH77 , 5

. The cost data is from table 4.6, unadjusted for replacement,

maintenance, repair, or present value of mortgage payments, interest tax savings

property tax and insurance costs. A heating index (Fj) of 200 is used, corresponding to natural gas heating at $0.46 per therm, 70 percent seasonal furnace

efficiency, and a modified uniform present worth factor (UPW*) of 30. (See

table 8.4 for other equivalent assumptions that result in an Fj of 200. Table

A-3 in appendix A provides the assumptions that equate to a UPW* of 30.) A

cooling index (F2

) of 200 is used, corresponding to central electric air con- ditioning with a seasonal COP of 2.35 (SEER = 8.0), a price per kWh of $0,053,

and a UPW* of 30. (See table 8.5 for other equivalent assumptions that result

in an F2 of 200.) The modifications with asterisks in table 8.3 represent the

optimal level of thermal improvement for each component of the building envelope

No further improvement will produce incremental savings large enough to amortize

the additional costs incurred.

Based on these same costs, the optimal level of thermal improvement for each

of these same components has been calculated for a wide range of climates and

heating and cooling index numbers (Fj^ and F2 , respectively). Table 8.6 shows

the optimal levels calculated for heating only (i.e., air conditioning is not

used) in six heating degree day (base 60°F) regions and for five values of Fj,

ranging from 100 to 500. Several alternative assumptions which equate to each

Fj^ value used are shown in table 8.4. Table 8.7 shows the optimal levels calculated for both heating and cooling savings in six combined HDD^q and CDH 77^5

regions. (While these combined regions are representative of the general relationship between HDD50 and CDH77 , 5 , there is significant variation between

these two variables, so that they do not include all regions of the United

States.) Five combinations of Fj and F 2 values are shown. However, there is no fixed relationship between Fj and F2 ; these are meant to be representative

only. Several alternative assumptions which equate to each F

2 value used are shown in table 8.5.

110
Table 8.2 Calculation Procedures for Incremental Costs

A. Calculation of Net Present-Value Purchase Costs

(1) Additional Purchase Cost Due to i^^ Modification

( 1 )

(2) Percent Down Payment

( 2 )

(3) Amount Financed = v (1“ ) =

(1) (2) (3)

(4) Present Value of Mortgage Payments per $1000 Borrowed

(from table A-1)

(4)

(5) Present Value of Mortgage Payments _ / 1000 =

(3) (4)

(6) Present Value of Interest Payments per $1000

Borrowed (from table A-2)

(5)

W

(7)

Income Tax Bracket

Tt)

(8)

Present Value of Tax Savings From Interest

X X / 1000 =

(5) (T) ~J7) TsT

(9)

Net Present Value of Purchase Cost for i^^ Modification

[ X 1 + _ - _ =

TT) (T5 Tel T8l m

B. Calculation of Replacement, Maintenance and Repair Costs

(10) Present Value of Replacement Costs (use equation (3-1)

to discount future costs to present value)

rr^

(11) Annually Recurring Maintenance and Repair Costs

(first year)

rrrr

111
Table 8.2 (Continued)

(12) Uniform Present Worth Factor for (11) (use

equation (3-2) to find factor)

TTIF

(13) Present-Value, Life-Cycle Maintenance and Repair Costs

(annually recurring)

OT) "" 02) 03)

(14) Present Value of Non-Annually Recurring Maintenance and

Repair Costs (use equation (3-1) to discount future costs

to present value)

O^

(15) Total Present Value, Life-Cycle Replacement, Maintenance,

and Repair Costs for i^^ Modification

05)

C. Estimate of Property Tax and Insurance Costs

(16) Property Tax and Insurance Cost Factor

ri6)

(17) Present Value, Life-Cycle Property Taxes and Insurance

Costs for i^^ Modification

(1)

X

(16)

D. Total Incremental Cost for i^^ Modification (AC^^)

08) 4- + =

(9) 05 ) 07 )

(17)

(18)

112
Table

8.3

Example

Solution

of

Optimal

Component

Modifications

4J CM

05 J-l O< </y

0) ^ m

tjOCM S-' ^ C -u

v£> -H <4-1 + N-/ >

-^

rt </> /-s CO CO < w oo o o o CM

LO

mX o w 0£ o U X o II <! sf <

II

X0m \ ptH . CM O 4J O <4-1 vO

01

X 3

(U 05 ^ u 4-1 05 CO <I PQ

«0 PQ

w <

CQ V—' COO

05 o

05 o 3 CM

cd

O o X II

(U 0) CM

OJ (U ft! o Ui o

bO bO o

05 0) Q Q o CO

X

tao bO

O

C

C CM

X

•H •H < 4-1 r—1

II rt o

<u o X u /—\

CM

4-1 CM

X ^ 3

CM <J 4-1 w < PQ COOi-H V—'

4-1 33GOaSou

O ov ov CO

CM

O o CM . . • . • . o o

</> o o o o

in CO CN CO o in CO CM . . • • • . CO o o o O CM

0>

O vO CM CM C^

CO -H o O

O CM ..... . o o o o o o

1^ vD CM CO CO

VO <7v OV CM cn OV CM 1—1 <r • . . . • • o O o o

CO ^ 0^ Mf

vO >d- CM ^ O 0^ ..... . CM O O O O '-H COcjN 00 rH 00

CTi VO o 40 r-H CM —< -cr m vj- ..... . CO CM <—• O O OV o c

•H

O

4J *H

nj 4-1 rH to 0 .H U :3 C CD M CM

CJ ^C •H ^CTvOOOON iH ^

4J i-Ht-HCOCO'<J- t—l 1—1 4J I I I I I (0 I <: ccjoipipiios: & (Hi

h«.

OO CO 1-1

O CO CO CM ^ ... . . o o o o o o CM vo

1—4 CM 1-H ... . . o o o o o

CM CO VD CM O O O —I o ... . . o o o o oI I —I vO CM O O CO CM OV O rH CO r**^ • • • • • o o o o oI I

CM CO ov CM OV

1-H CO 1—1 OV I—I

... . . o o o o o

crm CM 00 ov

O mT vO 00 vD

vO vO Ov lO CTv ... . . 0^0 «sr o

tio

•H bO

4-> 3

to •H

1—1 N 3 3

05 I—1 3 O M s * 3 •JC o

CO CJv CO

O T3 CM O 3 1 1 1 rH 1 1 •H X X X X X X 12 . • CO

00 CO o o m <yv m in . . • . CM CM <}

00 cn r-- in a> • • • • o m a^ CN

CO 00

vO 00 o . • « • o o o o

CJV o CO

vO CM

1—1 CNJ o . • • • CO CN o

CJV ov

m o in a^ . • • • ov m 00 CN m o 00

CMin '0- o^ . . •

r>.

m CM 3 3 3 N 3 3 iH 3

rH o O o O

JC 1 bO-K

Q 3 3 3 3 3

rH rH iH •H

O S

JQ

a 33O

H 3 •H 3 •H Q O O O iH 4-1 o H (2 CO CO • . m vO

113

Indicates

that

optimal

envelope

configuration

includes

this

modification
Table 8.4 Representative Assumptions for Selected Values of Fj (Heating)

Heating

Energy

Energy

Price/Unit

Seasonal

Efficiency UPW*

100 Gas $0. 23/therm 0.70 30

Electric 0.011/kWh 1.00 30

Electric 0.017/kWh 1.50a 30

Electric 0.023/kWh 2.00a 30

200 Gas $0.46/ therm 0.70 30

Oil 0.65/gallon 0.70 30

Electric 0.023/kWh 1.00 30

Electric 0.035/kWh 1.50a 30

Electric 0.046/kWh 2.00^ 30

300 Gas $0.69/ therm 0.70 30

Oil 0.98/gallon 0.70 30

Electric 0.034/kWh 1.00 30

Electric 0.051/kWh 1.50^ 30

Electric 0.068/kWh 2.00^ 30

400 Gas $0.92/therm 0.70 30

Oil $1 . 31/gallon 0.70 30

Electric 0.045/kWh 1.00 30

Electric 0.068/kWh 1.50^ 30

Electric 0.090/kWh 2.00^ 30

500 Oil $1. 64/gallon 0.70 30

Electric $0.057/kWh 1.00 30

Electric 0.086/kWh 1.50^ 30

Electric 0.114/kWh 2.00^ 30

^ Heat Pump Heating Seasonal Performance Factor (HSPF)

114
Table 8.5 Representative Assumptions for Selected Values of F

2 (Cooling)

Price/kWh Seasonal Efficiency

^2 (for cooling) C0P“ SEER‘S UPW*

100 $0,020 1.75 6 30

$0,027 2.35 8 30

$0,033 2.90 10 30

200 $0,040 1.75 6 30

$0,053 2.35 8 30

$0,067 2.90 10 30

300 $0,060 1.75 6 30

$0,080 2.35 8 30

$0,100 2.90 10 30

^ COP = Coefficient of Performance

^ SEER = Seasonal Energy Efficiency Ratio

115
Table 8.6 Optimal Component Specifications for Selected

Values of (Heating Only)^

Heating Degree Days (Base 60°F)^

Fi Component 1,000 2,000 3,000 4,000 6,000 8,000

Attic R-11 R-19 R-19 R-30 R-30 R-38

Wall R-11 R-11 R-11 R-11 R-13 R-19

100 Floor R-0 R-0 R-11 R-11 R-19 R-19

Windows Single Single Double Double Double Triple

Sliding Glass Door Single Single Single Single Double Double

Storm Door no no no no no no

Attic R-19 R-30 R-30 R-38 R-49 R-49

Wall R-11 R-11 R-13 R-19 R-19 R-23

200 Floor R-0 R-11 R-19 R-19 R-19 R-19

Windows Single Double Double Triple Triple Triple

Sliding Glass Door Single Single Double Double Double Double

Storm Door no no no no no no

Attic R-19 R-30 R-38 R-49 R-49 R-49

Wall R-11 R-13 R-19 R-19 R-23 R-23

300 Floor R-11 R-19 R-19 R-19 R-19 R-19

Windows Double Double Triple Triple Triple Triple

Sliding Glass Door Single Double Double Double Double Double

Storm Door no no no no no yes

400

Attic

Wall

Floor

Windows

Sliding Glass Door

Storm Door

R-30

R-11

R-11

Double

Single

no

R-38

R-19

R-19

Triple

Double

no

R-49

R-19

R-19

Triple

Double

no

R-49

R-23

R-19

Triple

Double

no

R-49

R-23

R-19

Triple

Double

yes

R-49

R-23

R-19

Triple

Double

yes

Attic R-30 R-38 R-49 R-49 R-49 R-49

Wall R-13 R-19 R-23 R-23 R-23 R-23

500 Floor R-11 R-19 R-19 R-19 R-19 R-19

Windows Double Triple Triple Triple Triple Triple

Sliding Glass Door Double Double Double Double Double Double

Storm Door no no no no yes yes

^ Based on incremental modification cost shown in table 4.6 and reductions in AHR

shown in table 7.9.

^ See HDD^q map in appendix C.

116
Table 8.7 Optimal Component Specifications for Selected Values of

Fj and F

2 (Heating and Cooling)^

Heating Degree Days (Base 60 OF)b

1,000 2,000 3,000 4,000 6,000 8,000

Fi/F7 Component

Cooling Degree Hours (Base 77.5°F)c

20,000 15,000 10,000 7,500 5,000 2,500

Attic R-30 R-30 R-30 R-30 R-38 R-38

Wall R-11 R-11 R-13 R-13 R-19 R-19

100/200 Floor R-0 R-0 R-0 R-11 R-19 R-19

Windows Double Double Double Double Double Triple

Sliding Glass Door Single Single Single Double Double Double

Storm Door no no no no no no

Attic R-30 R-38 R-38 R-38 R-49 R-49

Wall R-13 R-13 R-19 R-19 R-23 R-23

200/200 Floor R-0 R-0 R-19 R-19 R-19 R-19

Windows Double Double Triple Triple Triple Triple

Sliding Glass Door Single Double Double Double Double Double

Storm Door no no no no no no

Attic R-38 R-38 R-38 R-49 R-49 R-49

Wall R-13 R-19 R-19 R-23 R-23 R-23

300/200 Floor R-0 R-19 R-19 R-19 R-19 R-19

Windows Double Triple Triple Triple Triple Triple

Sliding Glass Door Double Double Double Double Double Double

Storm Door no no no no no yes

Attic R-38 R-38 R-49 R-49 R-49 R-49

Wall R-13 R-19 R-23 R-23 R-23 R-23

400/200 Floor R-0 R-19 R-19 R-19 R-19 R-19

Windows Double Triple Triple Triple Triple Triple

Sliding Glass Door Double Double Double Double Double Double

Storm Door no no no no yes yes

Attic R-38 R-49 R-49 R-49 R-49

1 R-49

Wall R-19 R-19 R-23 R-23 R-23 R-23

500/300 Floor R-0 R-19 R-19 R-19 R-19 R-19

Windows Triple Triple Triple Triple Triple Triple

Sliding Glass Door Double Double Double Double Double Double

Storm Door no no no no yes yes

^ Based on incremental modification costs shown in table 4.5, reductions in AHR shown in

table 7.9, and reductions in ACR shown in table 7 .10.

See HDD^q map in appendix C.

c See CDH for selected cities in table C-1 of appendix C.

/ / • 5

117
Tables 8.6 and 8.7 provide an interesting data base for making some general

observations about the optimal level of conservation modifications to building

envelope components for single-family housing.

(1) A minimum of R-30 attic insulation appears to be cost-justified in all

houses having central air conditioning. Even without central air conditioning, R-30 attic insulation is justified in all but the mildest heating

climates at current (1980) energy prices. R-49 attic insulation, the

highest level examined in this report, becomes cost effective in more

than half of the United States when oil or electric resistance heating is

used at typical 1980 energy prices.

(2) A minimum of R-11 wall insulation appears to be cost effective for

wood-frame walls in all regions of the country. In more than half the

country R-19 and R-23 levels are optimal on a life-cycle basis unless

heating fuel costs are very low (e.g. less than $0.25 per therm for gas).

(3) Floor insulation over unheated crawlspaces is not cost effective in regions

dominated by air conditioning requirements unless heating costs are very

high relative cooling costs. However, in most of the United States, R-19

floor insulation over unheated crawlspaces can be economically justified

unless heating costs are very low.

(4) Double glazing appears to be cost effective in all but the mildest

climates with low heating energy costs. Triple glazing becomes cost

effective in most of the United States, with even moderate energy costs.

(5) Double glazing on sliding glass doors in cost effective in most regions

of the United States except when heating energy costs are very low.

(6) Storm doors are not likely to be cost effective outside of the coldest

regions of the United States unless fuel prices are very high. However,

if most of the cost of the storm door can be attributed to additional

security and to its screen door function during the summer months, this

option is likely to be cost justified in other regions as well.

118
9. SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS FOR FURTHER RESEARCH

9 . 1 SUMMARY

The purpose of this report was to investigate, in a systematic manner, the

extent to which energy conservation modifications to the envelope design of

single-family housing can be cost justified. A life-cycle, benefit-cost model

was outlined and economic decision-making criteria were formulated to determine

the minimum-life-cycle-cost envelope design. The interdependent relationships

between and within building components were examined. A priority ranking methodology was described and used to calculate reductions in heating and cooling

requirements due to component modifications in 14 geographic locations. These

reductions were then correlated with corresponding heating degree days and cooling degree hours in order to provide a basis for estimating energy savings in

any location in the United States. A method for calculating optimal component

configurations was outlined and optimal configurations were developed for a wide range of climate data and energy prices.

This report represents a significant advance over previous work of a similar

nature because the heating and cooling requirements and reductions in those

requirements were estimated using a dynamic load determination program, NBSLD,

instead of steady-state methods and aggregate climatic data. Actual hourly

climatic data for each location examined were utilized. In addition, the

thermal interdependence among the envelope components was considered to a greater degree than in previous reports. Results of the thermal analysis were reported in considerable detail, including annual heating and cooling requirements, design heating and cooling loads, annual heating and cooling hours

corresponding to changes in the envelope design, and heat gain and loss through

south-facing windows and walls of the four major orientations during heating

and cooling hours.

In addition, a methodology for adjusting present-value modification cost data

for mortgage pa)nnents, property taxes and insurance costs over the time horizon

was presented.

9.2 CONCLUSIONS

A number of significant conclusions can be derived from this report.

(1) Optimal envelope design configurations vary over a wide range depending

on climate, energy costs, and modification costs. For example, optimal

attic Insulation resistances in houses with electric heat and central

air conditioning range from R-30 in Miami to R-49 or more in Minneapolis.

If only heating reductions are considered, optimal attic Insulation

levels may be less than R-11 in the mildest winter regions of the

United States (e.g., southern Florida).

(2) Increasing the size of south-facing, double-glazed windows in a well-insulated house, without corresponding decreases in window area

on the other walls, will reduce heating loads in very few locations

unless substantial Internal mass is available and/or window management

119
techniques such as theraal shutters are used to reduce heat losses

during periods when the sun is not shining. A night setback of the

thermostat during heating periods will increase the relative benefits

of large south-facing windows compared to a uniform day-night

thermostat setting.

(3) The compass orientation of a house appears to have little effect on

its heating requirements except for the orientation of its windows.

Instead the total opaque wall surface area is more important. However, the orientation of the house significantly affects cooling

requirements: north- and south-facing together walls are considerably

more energy efficient than those facing east and west. Orientation

of windows and daily living areas away from the north side and toward

the south side of the house appears to have more effect on reducing

annual heating requirements than the actual orientation of the house.

Because the north-facing wall loses significantly more heat than the

south-facing wall, consideration should be given to improving its

thermal characteristics relative to those of the other walls in

locations where heating loads predominate.

(4) Modified heating degree day and cooling degree hour data can provide

a useful and relatively accurate means of interpolating heating and

cooling (sensible) requirements to other locations based on more precise calculations in known climates. In addition, this modified data

can be used to correct the results based on Test Reference Year (TRY)

climatic data, in order to better reflect long-term climatic trends.

(5) Reductions in annual heating requirements are generally more than

proportional to reductions in design loads. Thus, methodologies which

base reductions in heating requirements on reductions in design loads

will underestimate the potential savings from envelope design modifications. The opposite is true for reductions in annual cooling requirements, where they tend to be significantly less than proportional to

design loads. This lack of direct proportionality may have significant

implications with respect to equipment sizing and part-load operations.

9.3 RECOMMENDATIONS FOR FURTHER RESEARCH

This report provides a new insight into the economic and thermal aspects of

energy conservation in new housing design. However, a number of important

issues require further research. These can be divided into two categories;

(A) technical issues, and (B) economic issues.

(A) Technical issues relate to the ability to better quantify the effects of

design changes on annual energy requirements. These include:

(1) Refinements to NBSLD (and similar load-estimating programs) to improve

algorithms and data bases related to

(a) attic temperatures.

120
(b) the effects of heat absorption on heat transfer through

architectural glass,

(c) the thermal coupling of zones within a building,

(d) the modeling of internal mass without distorting envelope

component specifications,

(e) radiation exchange modeling,

(f) the simulation of window management techniques, (i.e.,

changes in shading and conduction on an hourly, daily,

and seasonal basis),

(g) ground temperature data and heat transfer calculation through

floors and walls below grade, and

(h) daylighting and its impact on lighting energy use in buildings.

(2) Estimates of actual energy requirements based on the part-load

efficiencies of heating and cooling equipment,

(3) Improved analysis of passive solar measures,

(4) Improved data on the effects of envelope modifications to reduce air

infiltration, and

(5) The effects of insulation and mass in reducing heating and cooling

requirements in masonry wall buildings.

(B) Economic issues are related to the determination of optimal building

designs with respect to space heating and cooling. These Include;

(1) More empirical analysis into life-cycle cost-related decision

criteria for new home purchasers,

(2) The simultaneous determination of optimal envelope and equipment

efficiencies

,

(3) Improved modification cost data estimated on a regional basis,

(4) Improvements in the priority ranking process when better

information on componnent Interdependence can be produced.

^ The effects of mass and insulation in walls are examined in S. Petersen,

K. Barnes, and B. Peavy, Determining Cost-Effective Insulation Levels for

Masonry and Wood-Frame Walls in New Single-Family Housing , BSS-134, National

Bureau of Standards, Washington, D.C., August 1981.

121
(5) Further analysis to demonstrate the viability of economic analysis in

the establishment of "energy budget" data that can serve as economically justified, performance-oriented guidelines for new single-family

housing design, and

(6) Improved projections of future energy costs that will enable the user

to better project the dollar value of annual energy savings over the

life of the building.

122
REFERENCES

1. Achenbach, P. R. and Coblentz, C. W. , "Field Measurements of Air Infiltration

in Ten Electrically Heated Houses," ASHRAE Transactions 69, 1963.

2. "A National Survey of Characteristics and Construction Practices for all

Types of One-Family Homes." National Association of Home Builders Research

Foundation, Rockville, MD., February 1974.

3. ASHRAE Handbook of Fundamentals , American Society of Heating, Refrigerating

and Air-Conditioning Engineers, New York, 1972.

4. Burch, D. M. and Hunt, C. M., Retrofitting an Existing Wood-Frame Residence

for Energy Conservation—An Experimental Study , National Bureau of Standards,

NBSIR 77-1274, 1977.

5. "Conventional Electric Heat Pumps and Other Systems: Comparison of Seasonal

Performance Factors on an Onsite Basis," Heat Pump Technology , Gordian

Associates, Inc., New York, July 1977.

6. Data Resources, Inc., Energy Review , Lexington, MA, Winter 1980-81.

7. Hastings, S. R. , Three Proposed Typical House Designs for Energy Conservation

Research , National Bureau of Standards NBSIR 77-1309, October 1977.

8. Hastings, S. R. , Window Design Strategies to Conserve Energy , National

Bureau of Standards BSS-104, 1977.

9. Jacobs, M. and Petersen, S., "Making the Most of Your Energy Dollars in

Home Heating and Cooling," NBS Consumer Information Series 8, National

Bureau of Standards, Washington, D.C., 1975.

10. Kusuda, T. and Collins, B., Simplified Analysis of Thermal and Lighting

Characteristics of Windows: Two Case Stud^ies, National Bureau of Standards

BSS-109, 1978

11. Kusuda, T. , NBSLD, The Computer Program for Heating and Cooling Loads in

Buildings , National Bureau of Standards BSS-69, 1976.

12. Kusuda, T. , NBSLD, The Computer Program for Heating and Cooling Loads in

Buildings , (Revised) NBSIR-Draft Report, National Bureau of Standards,

Washington, D.C., April 1981.

13. Marshall, H. and Ruegg, R. , Simplified Energy Design Economics , SP 544,

National Bureau of Standards, Washington, D.C., 1980.

14. Moyers, John C., The Value of Thermal Insulation in Residential Construction:

Economics and the Conservation of Energy , U.S. Atomic Energy Commission,

Oak Ridge National Laboratory, 1971.

15. National Climatic Center, "Summary of Hourly Observations," Asheville, N.C.

(no date).

123
16. Nelson, L. W., "Reducing Fuel Consumption with Night Setback," ASHRAE

Journal, American Society of Heating, Refrigerating, and Air-Conditioning

Engineers, Inc., New York, August 1973.

17. Peavy, B., Burch, D. , Powell, F., and Hunt, C. M. , Comparison of Measured

and Computer Predicted Thermal Performance of a Four-Bedroom Wood-Frame

Townhouse, BSS 57, National Bureau of Standards, Washington, D.C., 1973.

18. Peavy, B., Powell, F., and Burch, D., Dynamic Thermal Performance of an Experimental Masonry Building , BSS 45, National Bureau of Standard,

Washington, D.C., 1972.

19. Petersen, S., Barnes, K. , and Peavy, B., Determining Cost-Effective

Insulation Levels for Masonry and Wood-Frame Walls in New Single-Family

Housing , BSS 134, National Bureau of Standards, Washington, D.C., 1981.

20. Petersen, S. R. , and Barnett, J. P., Expanded NBSLD Output for Analysis of

Thermal Performance of Building Envelope Components , NBSIR 80-2076, National

Bureau of Standards, Washington, D.C., 1980.

21. Petersen, S. R., Retrofitting Existing Housing for Energy Conservation; An

Economic Analysis, BSS-64, National Bureau of Standards, Washington, D.C.,

1974.

22 . Residential Energy Consumption, Single Family Housing (Final Report) , (HUD-PDR-29-2) , Hittman Associates , Inc . , Columbia, MD., 1975.

23. Roberts, Nall, Rodgers, Greenburg , "Comparison of Computer-Predicted,

Thermal Loads with Measured Data from Three Occupied Townhouses," ASHRAE

Transactions , Vol. 83, Part I, American Society of Heating, Refrigerating,

and Air-Conditioning Engineers, Inc., New York, 1978.

24. Ruegg, R. , Petersen, S., and Marshall, H. , Recommended Practice for

Measuring Life-Cycle Costs of Building Systems , NBSIR 80-2040, National

Bureau of Standards, Washington, D.C., 1980.

25. "Selected Cost Data on Residential Construction." National Association of

Home Builders, Research Foundation, 1977.

26. Stamper, E., "Weather Data," ASHRAE Journal , February 1977.

27. "Thermal Environmental Conditions for Human Occupancy," ASHRAE Standard

55-74, American Society of Heating, Refrigerating and Air-Conditioning

Engineers, Inc., New York, 1974.

28. U.S. Bureau of the Census, Statistical Abstract of the United States; 1979

(100th edition), Washington, D.C., 1979.

29. U.S. Department of Commerce, "Construction Review," Vol. 26, No. 1, January

1980.

124
30. U.S. Department of Commerce, National Oceanic and Atmospheric

Administration, Environmental Data Service, National Climatic Center,

"Degree Days to Selected Bases," Asheville, NC. (no date).

31. U.S. Department of Housing and Urban Development, Residential Energy

Consumption, Single-Family Housing , Report No. HUD-HAl-2 (Prepared by

Hittman Associates, Columbia, MD) , Washington, D.C., 1973.

125
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APPENDIX A

SELECTED FACTORS FOR LIFE-CYCLE COST ANALYSIS

A-1
Table A-1 . Present Value of Mortgage Payments per $1000 Borrowed^

(Monthly payments discounted from time of payment)

Annual

Discount Rate Mortgage Life Annual Interest Rate (Nominal)

( Nominal )° (years) 9% 10% 11% 12% 13% 14% 15% 16% 17% 18%

20 961 1030 1102 1176 1251 1328 1406 1485 1566 1648

10%b 25 955 1034 1116 1199 1284 1370 1458 1547 1637 1727

30 951 1037 1126 1216 1308 1401 1495 1590 1685 1782

20 850 912 975 1040 1107 1175 1244 1314 1386 1458

12% 25 832 901 972 1045 1119 1194 1270 1348 1426 1505

30 820 894 970 1048 1127 1207 1288 1370 1452 1535

20 760 815 872 930 989 1050 1112 1175 1239 1303

14% 25 735 796 859 923 988 1055 1123 1191 1260 1330

30 718 784 850 919 988 1058 1129 1201 1273 1346

20 686 736 787 839 893 948 1004 1060 1118 1176

16% 25 658 712 768 826 884 944 1004 1065 1127 1189

30 639 697 756 817 879 941 1004 1068 1132 1197

20 572 614 657 700 745 791 838 885 933 982

20% 25 542 587 633 681 729 778 828 878 929 981

30 523 571 619 669 720 771 822 875 927 980

^ Calculation Procedure: P.V. Mortgage Pa5niients = L i/12(l + i./\2)

(1 + i/12)^2n _ 1 where L = initial loan amount,

i = annual interest rate,

^m ~ monthly discount rate = (1 +d)^^^^ - 1, and

d = annual discount rate, and

n = loan life in years.

Mortgage payments are calculated and discounted on a monthly basis.

d^(l + d„)^^^ m m

^ The real annual discount rate (d’) equivalent to the nominal discount rate (d) for

any given general inflation rate (G) can be computed as

d' = ^ + d _ 1,

1 + G

Conversely, the nominal discount rate equivalent to the real discount rate for any

given general inflation rate can be computed as

d = (1 + d') (1 + G) - 1.

For example, a 2 percent discount rate and a 10 percent rate of general inflation

result in a 12.2 percent nominal discount rate (1.02 x 1.10 -1 = 0.122).

A-2
Table A-2. Present Value of Interest Payments per $1000 Borrowed^

(Discounted from end of year)

Discount Rate

( Nominal )1> Mortgage Life

(years)

Interest Rate (Nominal)

9% 10% 11% 12% 13% 14% 15% 16% 17% 18%

20 596 672 750 829 909 990 1072 1155 1239 1323

10% 25 677 763 851 939 1029 1119 1210 1302 1393 1486

30 738 831 925 1020 1116 1211 1308 1404 1500 1597

20 537 605 674 744 815 888 960 1034 1108 1182

12% 25 600 675 752 829 907 986 1065 1145 1224 1304

30 645 725 806 888 970 1052 1135 1217 1300 1382

14%

20

25

30

487

536

517

548

603

641

610

671

712

673

739

783

737

808

855

802

878

926

867

947

998

932

1017

1070

998

1088

1142

1065

1158

1214

20 445 500 556 613 671 729 788 847 906 966

16% 25 484 544 605 666 727 789 851 913 976 1038

30 511 573 636 699 762 825 889 952 1016 1079

20 377 423 470 518 566 614 663 712 761 811

20% 25 404 453 502 552 602 653 703 754 805 856

30 420 471 522 572 623 675 726 777 828 879

A Calculation Procedure: P*V, Interest Payments = y

where + i2(j-l)) = L(k-1 + 12(j-l))(l - P,

12 . l2

’ ^(k+12(j-D)

k=l

(1 + d)^

1 = annual Interest rate,

Lq = initial loan amount,

L(k + 12(j-l)) “ remaining principal at end of month (k + 12(j-l)),

P = uniform monthly payment,

d = discount rate, and

n = loan life in years.

In closed fom, the P.V. of interest paymenst, discounted from the end of the year, can be calculated as

P.V.

Interest

where

= Lo [12'CRF*UPW - - 1)(1

Payments 1/12

CRF = (1/12)(1 + l/12)12n/((i + i/l2)12n _ i)

_i (1

(1 + ±niv^ dl (1 + dl)"

)]

UPW = ((1 + d)n - l)/(<l(l+d)n)

dl = [(1 + d)/(l + 1/12)12] - 1

b See footnote b on table A-1

A-3
Table A-3. Modified Uniform Present Worth Factors (UPW*)

Rate of Fuel

Discount Rate Price Increase

0 %

2 %

4%

0 % 6%

8%

10%

12%

0%

2 %

4%

2 % 6%

8%

10%

12%

0%

2 %

4%

4% 6%

8%

10 %

12 %

0%

2 %

4%

6 % 6%

8%

10%

12%

0%

2 %

4%

10 % 6%

8%

10 %

- 12 %

Building Lifetime (years)

20 25 30 35 40

20.0 25.0 30.0 35.0 40.0

24.8 32.7 41.4 51.0 61.6

31.0 43.3 58.3 76.6 98.8

39.0 58.2 83.8 118.1 164.0

49.4 79.0 122.3 186.1 279.8

63.0 108.2 180.9 298.1 486.9

80.7 149.3 270.3 483.5 859.1

20 25 30 35 40

16.4 19.5 22.4 25.0 27.4

20.0 25.0 30.0 35.0 40.0

24.7 32.5 41.1 50.6 61.1

30.7 42.8 57.5 75.3 96.9

38.5 57.1 82.0 115.1 159.1

48.5 77.1 118.7 179.5 268.1

61.5 104.9 174.0 284.5 460.8

20 25 30 35 40

13.6 15.6 17.3 18.7 19.8

16.4 19.6 22.5 25.2 27.5

20.0 25.0 30.0 35.0 40.0

24.6 32.3 40.9 50.2 60.5

30.4 42.4 56.8 74.2 95.2

38.0 56.2 80.3 112.2 154.5

47.6 75.3 115.3 173.3 257.3

20 25 30 35 40

11.5 12.8 13.8 14.5 15.0

13.7 15.8 17.5 18.9 20.0

16.5 19.7 22.6 25.3 27.7

20.0 25.0 30.0 35.0 40.0

24.5 32.2 40.6 49.9 60.1

30.2 41.9 56.0 73.0 93.5

37.5 55.3 78.7 109.6 150.2

20 25 30 35 40

8.5 9.1 9.4 9.6 9.8

9.9 10.8 11.4 11.8 12.1

11.7 13.1 14.1 14.9 15.5

13.9 16.0 17.8 19.3 20.5

16.6 19.9 22.9 25.6 28.1

20.0 25.0 30.0 35.0 40.0

24.3 31.9 40.1 49.2 59.1

A-4
Table A-4. Unit Energy Prices (Metered) and Corresponding Price per

Million Btu Output from Furnace

A. Price per Million Btu Metered (Pt^/ph) for Selected Fuel Types

Fuel

Type

Price

Unit Unit; Energy Price ($)

G3.S therm 0.20 0.30 0.40 0.60 0.80 1.00 1.20 1.50 1.80 2.20

Oil gallon 0.28 0.42 0.56 0.84 1.12 1.40 1.68 2.10 2.52 3.08

Elec . kWh 0.007 0.010 1.014 0.021 0.027 0.034 0.041 0.051 0.061 0.075

$/Million

Btu

(metered)

2.00 3.00 4.00 6.00 8.00 10.00 12.00 15.00 18.00 22.00

B. Price per Million Btu Output for Selected Furnace Efficiencies

Price per Million Btu Metered (Pj^/ph)

2.00 3.00 4.00 6.00 8.00 10.00 12.00 15.00 18.00 22.00

Furnace

Efficiency^

0.6 3.33 5.00 6.67 10.00 13.33 16.67 20.00 25.00 30.00 36.67

0.7 2.86 4.29 5.71 8.57 11.43 14.29 17.14 21.43 25.71 31.43

0.8 2.56 3.75 5.00 7.50 10.00 12.56 15.00 18.75 22.50 27.50

0.9 2.22 3.33 4.44 6.67 8.89 11.11 13.33 16.67 20.00 24.44

1.0 2.00 3.00 4.00 6.00 8.00 10.00 12.00 15.00 18.00 22.00

1.4 1.43 2.14 2.86 4.49 5.71 7.14 8.57 10.71 12.86 15.71

1.6 1.25 1.88 2.50 3.75 5.00 6.25 7.50 9.38 11.25 13.75

1.8 1.11 1.67 2.22 3.33 4.44 5.56 6.67 8.33 10.00 12.22

2.0 1.00 1.50 2.00 3.00 4.00 5.00 6.00 7.50 9.00 11.00

2.2 0.91 1.36 1.82 2.73 3.64 4.55 5.45 6.82 8.18 10.00

^ Efficiencies greater than 1,0 are for heat pumps.

A-5
Table A-5. Selected kWh Prices and Equivalent Price per Million Btu Output

for Selected Central Air Conditioner (CAC) Efficiencies

Metered kWh Price

$0,021 $0,034 $0,048 $0,061 $0,075 $0,089

Equivalent Input Cost per Million Btu

$6.00 $10.00 $14.00 $18.00 $22.00 $26.00

CAC Efficiency Equivalent Output Cost per Million Btu

(Price per Million Btu for Selected CAC Efficiencies)

COP SEER

1.75 6 3.43 5.71 8.00 10.29 12.57 14.86

2.05 7 2.93 4.88 6.83 8.78 10.73 12.68

2.35 8 2.55 4.26 5.96 7.66 9.36 11.06

2.65 9 2.26 3.77 5.28 6.79 8.30 9.81

2.95 10 2.03 3.39 4.75 6.10 7.46 8.81

3.20 11 1.87 3.13 4.38 5.63 6.88 8.13

A-6
APPENDIX B

ESTIMATING PRESENT-VALUE LIFE-CYCLE TAX AND INSURANCE COSTS

In general, improvements in the design of a building to reduce its energy

consumption requirements can be expected to increase the value of that building.

Such an increase in value is essential to the life-cycle-cost concept if the

building is to be sold during its useful life. Estimates of the increase in

value are important, even if the building is not sold, because future property

tax liabilities and insurance premium will be based on estimated property

values in the years to come. These additional costs should be considered in a complete evaluation of the incremental costs of energy conservation improvements

on a life cycle basis.

In a life-cycle cost context, the increase in building value due to energy

conservation improvement at any given point in time is equal to the net discounted value of future energy savings over the remaining lifetime of the con- servation improvement, or to the replacement cost of that improvement, whichever

is lower. However, the net discounted value of the remaining energy savings is

not simply the discounted sum of the future dollar reduction in fuel bills.

Future tax and insurance costs which are incurred because of the increased

building value must be considered as well in that they reduce the net present

value of the remaining energy savings.

Tax liabilities and insurance premiums payable at the beginning of years i (Tj[

and 1^) can be stated as:

R-p = property tax rate,

Rj = insurance premium rate,

NPVESp = net present value at the beginning of year i of energy

savings over the remaining life of the building, and

Cp = replacement cost at beginning of year i.

Both R>p and Rp are assumed to be constant over the life of the building. Taxes

and insurance liabilities are assumed to be payable at the beginning of each

period and are calculated using energy and replacement costs at that same time.

Total present-value, life-cycle property tax and Insurance premium (TI) can

thus be expressed as

Tp = MIN (Rp. • NPVESp, R-j. • Cp) (B-1)

and Ip = MIN (Rp • NPVESp, Rp • Cp) (B-2)

where

L

TI = Z MIN[R • NPVES. R • C. ]/(l + D)^“^

• 1 ^ ^

9 (B-3)

B-1
where R = R-p + Rx>

D = the real discount rate, and

L = the expected useful lifetime.

It is assumed that the replacement cost at any given time is equal to the

additional construction cost in constant dollar terms. However, for some modifications (as with walls of increased thickness) this will not be the case and thus replacement costs will be understated.

In order to calculate (R • NPVESj[), a recursive system of equations must be

established. That is, the taxes and insurance costs that are incurred in one year depend on the taxes and costs Incurred in the next. Thus the calculation

procedure must begin with the last year of the expected useful life and work

backwards to the first year. Taxes and insurance costs can be estimated in

this manner for each year over the useful life. This recursive system of

equations reduces to a manageable form that can be calculated on a computer

without great difficulty.

Beginning with year L, tax and insurance costs (incurred at the beginning of

the year) can be calculated as follows;

where Sq = average annual energy savings valued in current dollars at beginning

of year 1

Working backwards for each year L, L-1 , L-2 , . , ,, 1, a generalized form

appears

R • NPVESp^ = Sq • R (B-4)

(1 + P)^~^ _ (1 + P)^~^

R • NPVES^^i = Sq 1 + R (1 + R)2

1 + D

(1 + P)^~^ _ (1 + P)^~^

R • NPVESl_j^ = Sq (1 + R)^^

~ (1 + R)

(1 + D)^

+ (1 + P)^ ^ - (1

+ (1 +

p)L-k-l . (1_+_P)^^'

1 + R

1 + R

(B-5)

or, where i = L - k.

R • NPVESjl = Sq • Z j”i

L

(1 + P)j ^ _ (1 + P)j ^

(1 + R)j-i (1 + R)j-i+l (B-7)

(1+D)^"^

R • NPVESi = So

RO + . E aJ-1 , (1 + R)2 1 j=i

(B,8)

B-2
where 1 + P and

, (1 + R)(l + D)

R • NPVES^ = Sq • R(1 + D)^"^ • (1 + R)^“^

a^-1-aL

1 - A

(B.9)

This procedure permits the calculation of the present value of life-cycle

property tax and insurance premiums based on the increased value of the building due to its energy conservation features. However, no generalized factors

for estimating tax and insurance costs as a function of increased construction

cost (or sales price) can be established because the ratio of dollar energy

savings to increased construction costs varies widely from modification to

modification.

In the economic analysis of energy conservation improvements, the critical

point of evaluation is where the ratio of incremental savings to incremental

costs (adjusted for tax and insurance liabilities) is equal to one. Given

such a constant ratio, a generalized factor can be established which is useful

in determining whether a given conservation improvement has a benefit/cost

ratio greater than unity. That is, if the ratio of savings to cost is still

greater than unity after adjustment for taxes and insurance, the modification

is assumed to be cost effective. Thus, a factor to adjust for taxes and insurance, based on the assumption that net incremental savings must be at least

equal to net Incremental costs in order to be cost effective, will serve as a check to assure cost effectiveness consistent with the general assumptions

made. Table B-1 provides such adjustment factors for a range of net tax rates

and insurance rates, lifetimes, real energy price escalation rates, and real

discount rates. Interpolation can be used to find factors for intermediate

values of these variables. Increasing first costs by this factor will provide

an adjusted cost for comparison with present-value savings.

It should be recognized that these factors will likely overstate the actual

increase in property taxes over the life of the building because energy conservation modifications are frequently not considered in the assessed value of a house. However, if assessed values are based on the selling price of a house,

and that selling price reflects the true value of its energy conservation

features, these factors will serve as reasonable estimators.

B-3
Table B-1 Present Value Factors for Estimating Future Property

Taxes and Insurance Costs^

Energy Price Net Tax Rate

Discount Rate Building Life Increase Rate Plus Insurance Rate , (Real, %) (Years) (Real, %) 1% 2% 3% 4%

0 20 0 .11 .22 .32 .40

2 .11 .23 .34 .42

4 .12 .24 .36 .45

30 0 .16 .34 .50 .61

2 .17 .36 .54 .66

4 .19 .39 .58 .71

40 0 .22 .46 .70 .84

2 .24 .52 .79 .93

4 .27 .57 .86 1.02

2 20 0 .10 .21 .31 .39

2 .11 .22 .33 .41

4 .11 .23 .35 .44

30 0 .15 .31 .46 .57

2 .16 .33 .51 .62

4 .17 .36 .56 .68

40 0 .19 .40 .62 .77

2 .22 .46 .71 .87

4 .24 .50 .76 .96

4 20 0 .10 .20 .30 .37

2 .10 .21 .32 .40

4 .11 .22 .34 .42

30 0 .13 .28 .42 .53

2 .14 .31 .47 .59

4 .16 .33 .50 .64

40 0 .17 .34 .52 .70

2 .19 .38 .58 .77

4 .20 .39 .59 .79

6 20 0 .09 .19 .28 .36

2 .10 .20 .30 .38

4 .10 .21 .32 .41

30 0 .12 .24 .38 .50

2 .13 .27 .41 .54

4 .14 .28 .42 .56

40 0 .14 .29 .44 .59

2 .15 .31 .46 .62

4 .16 .31 .47 .62

10 20 0 .08 .16 .25 .33

2 .08 .17 .26 .34

4 .09 .18 .27 .36

30 0 .10 .20 .30 .40

2 .10 .20 .30 .41

4 .10 .20 .31 .41

40 0 .10 .21 .32 .42

2 .11 .21 .32 .43

4 .11 .21 .32 .43

^ Multiply present value factor by first cost to esjtimate present value of

increased property taxes and insurance over the specified building life.

^ Net tax rate is the property tax rate as applied to the actual house value

and adjusted for income tax credit. (For example, in the 20 percent tax

bracket a 2.5 percent property tax rate becomes 2 percent (=2.5 X (1-.2) .)

B-4
Table B-2. Residential Property Tax Rates in Selected Large Cities: 1977

Effective Tax Rate per $100

City of Actual Value

Boston $7.84

Indianapolis 4.23

Detroit 3.71

Milwaukee 3.59

Philadelphia 3.09

Los Angeles 2.94

San Francisco 2.80

Baltimore 2.76

Dallas 2.68

San Antonio 2.48

San Jose 2.46

Houston 2.44

Atlanta 1 2.39

Pittsburgh ' 2.36

St. Louis 2.14

San Diego 2.13

Cleveland 1.97

Memphis 1.94

New York City 1.93

Washington, D.C. 1.80

Seattle 1.76

Phoenix 1.73

Chicago 1.71

Jacksonville 1.67

Kansas City, Mo. 1.35

Nashville 1.28

Columbus , Ohio 1.27

Denver 1.16

New Orleans 0.96

Honolulu 0.82

Source: U.S. Bureau of the Census, Statistical Abstract of the

United States: 1979 ( 100th edition), Washington, D.C.,

1979, Table 508, p. 312.

B-5

APPENDIX C

LONG-TERM HEATING DEGREE-DAY MAPS AND COOLING DEGREE HOUR DATA

C-1
NORMAL

SEASONAL

HEATING

DEGREE

DAYS

-

BASE

65

C-2
normal

seasonal

heating

degree

pays

-

BASE

60

C-3
NORMAL

SEASONAL

HEATING

DEGREE

DAYSBASE

55 ti-i oLOm

0;

C/D C3 CQI

C/D

CCJ o

OJ0/

S-l bC

OD Q

acC

•Hu

ccj 0/

CCD Co

cn

C3a

COeo

cnI CJ)

QJ

5c

•H

tti

C-4
C-5
Table C-1. Long Term Cooling Degree Hour Data for Selected Cities and

Calculation Basest

CDH72.5 CDH75 CDH77.5

CITY

Albany, NY 7500 5100 3400

Albuquerque , NM 19600 14800 10800

Atlanta, GA 20700 14800 10300

Bakersfield, CA 33600 26800 21000

Baltimore, MD 14200 10100 6900

Boston, MA 7500 5100 3300

Chicago, IL 12500 8900 6200

Columbus , OH 12400 8800 6000

Dallas, TX 41600 32900 25500

Denver, CO 11200 8100 5700

Des Moines, lA 12500 9000 6200

Detroit, MI 9000 6100 4000

El Paso, TX 35000 27300 20900

Fort Worth ,TX 37400 29300 22400

Indianapolis, IN 12300 8600 5700

Kansas City, KS 23500 17900 13200

Little Rock, AR 28200 21400 15700

Los Angeles, CA 4000 2200 1200

Louisville, KY 19200 14100 10000

Madison, WI 8400 5800 3800

Memphis , TN 27200 20500 15100

Miami , OH 44500 30800 19800

Milwaukee , WI 6400 4300 2700

Minneapolis, MN 8700 6000 3900

New Orleans , LA 31300 22100 14900

New York, NY 44500 30800 19800

Oklahoma City, OK 25200 19300 14400

Philadelphia, PA 12600 8700 5800

Phoenix, AZ 60600 50600 41700

Pittsburgh, PA 7300 4700 2800

Richmond , VA 17600 12800 9100

Sacramento , CA 17300 13400 10200

Salt Lake City, UT 16000 12300 9200

San Antonio , CA 39400 30100 22400

San Diego , CA 4300 2300 1200

San Francisco , CA 1300 800 500

Savannah , GA 26200 18800 13100

Seattle, WA 1800 1100 700

Tampa , FL 35000 24500 16300

Topeka, KS 20600 15600 11600

Washington, DC 16100 11400 7800

^ Source: Calculated from National Climatic Center Summary Sheets

"Frequency of Hourly Temperatures” See Attachment C-1 for

calculations methodology.

C-6
Attachment C-1 . Methodology Used to Calculate Cooling Degree Hours

Cooling degree hours for any seleccted base temperature can be calculated

directly using

M

Z (i - B)Fi,

i=B+l

where B = base temperature

M = maximum outdoor temperature

= frequency of hourly temperature i

in average year.

If frequency of hourly temperatures is only available in 5°F temperature

intervals, Tj^ (e.g. , T^5_7 q, ...), Fj; can be approximated using the

following relationships:

Fi = 0.4(Ti_5^i_i/5) + 0.6(Ti^i+4/5)

Fi = 0.2(Ti_5^i_i/5) + 0.8(Ti^i+4/5)

^i+2 = Ti^i+4/5

Fi+3 = 0.8(Ti,i+4/5) + 0.2(Ti+5^i+9/5)

Fi+4 = 0.6(Ti^i+4/5) + 0.4(Ti+5^i+9/5)

C-7
NBS-114A (REV. 2-80

U.S. DEPT. OF COMM.

BIBLIOGRAPHIC DATA

1. PUBLICATION OR

REPORT NO.

2. Performing Organ. Report No. 3. Publication Date

SHEET (See instructions) 81-2380 August 1981

4. TITLE AND SUBTITLE

Economics and Energy Conservation in the Design of New Single-Family Housing

5. AUTHOR(S)

Stephen R. Petersen

6. PERFORMING ORGANIZATION (If joint or other than NBS, see instructions) 7. Contract/Grant No. national bureau of STANDARDS

DEPARTMENT OF COMMERCE 8. Type of Report & Period Covered

WASHINGTON, D.C. 20234 Final

9. SPONSORING ORGANIZATION NAME AND COMPLETE ADDRESS (Street. City, State, ZIP)

The Department of Energy and

The Department of Housing and Urban Development

Washington, D.C.

10. SUPPLEMENTARY NOTES

!

[221 Document describes a computer program; SF-185, FIPS Software Summary, is attached.

11. ABSTRACT (A 200-word or less factual summary of most significant information. If document includes a significant

I bibliography or literature survey, mention it here)

This report investigates the extent to which certain energy conservation modifications

to the envelope design of a new, single-family house are economically justified for a wide range of climates and projected energy costs. The report provides background

information on those factors that give rise to space heating and cooling loads in

buildings and examines in greater detail than in previous reports the thermal i '-Tr- dependencies within and among envelope components that can greatly affect heatii , and

cooling loads. Economic criteria for determining a minimum life-cycle cost builuing

envelope design are formulated and a priority-ranking method is developed to assist

j in the calculation of these designs. An expanded version of the NBS Load DeterminaI tion Program is used to calculate the annual heating and cooling requirements and

maximum heating and cooling loads for a 1200 square foot, wood-frame house having a wide range of thermal improvements in 14 geographic locations. The report also provides

a methodology for interpolating these results to climatic conditions other than the

14 analyzed. The analysis demonstrates that the optimal envelope design configuration

varies over a wide range depending on climate, energy costs, and modification costs.

12. KEY WORDS (Six to twelve entries; alphabetical order; capitalize only proper names; and separate key words by semicolon s) Architecture; building design; cost-benefit analysis; economics; energy conservation;

housing; Insulation; space heating and cooling costs; space heating and cooling

requirements

13. AVAILABILITY

[l^Unlimited

1 1 For Official Distribution. Do Not Release to NTIS

Order From Superintendent of Documents, U.S. Government Printing Office, Washington, D.C.

20402.

Order From National Technical Information Service (NTIS), Springfield, VA. 22161

14. NO. OF

PRINTED PAGES

159

15. Price

15.00

USCOMM-DC 6043-P80
.\v\*»