NBSIR 76-1177

Comparison of ComputerPredicted and Observed Energy

Uses in a Multi-Family HighRise Apartment Building

James P. Barnett and Stanley T. Liu

Center for Building Technology

Institute for Applied Technology

National Bureau of Standards

Washington, D.C. 20234

June 1 977

Final Report

MODULAR INTEGRATED

dlmius UTILITY SYSTEMS

improving community utility services by supplying

electricity, heating, cooling, and water/ processing

liquid and solid wastes/ conserving energy and

natural resources/ minimizing environmental impact

Prepared for Department of Housing and Urban Deyelopment

Office of Policy Development and Research

Washington, D.C. 20410

NBSIR 76-1177

COMPARISON OF COMPUTERPREDICTED AND OBSERVED ENERGY

USES IN A MULTI-FAMILY HIGHRISE APARTMENT BUILDING

James P. Barnett and Stanley T. Liu

Center for Building Technology

Institute for Applied Technology

National Bureau of Standards

Washington, D.C. 20234

June 1977

Final Report

[MDSJmiUS

MODULAR INTEGRATED UTILITY SYSTEMS

improving community utility services by supplying

electricity, heating, cooling, and water/ processing

liquid and solid wastes/ conserving energy and

natural resources/ minimizing environmental impact

Prepared for Department of Housing and Urban Development

Office of Policy Development and Research

Washington, D.C. 20410

U S. DEPARTMENT OF COMMERCE, Juanita M. Kreps, Secretary

Dr. Sidney Harman, Under Secretary

Jordan J. Baruch, Assistant Secretary for Science and Technology

NATIONAL BUREAU OF STANDARDS, Ernest Ambler, Acting Director
'
FOREWORD

The Department of Housing and Urban Development (HUD) is conducting

the Modular Integrated Utility System (MIUS) Program to develop and demonstrate the technical, economic and institutional advantages of integrating the systems for providing all or several of the utility services for

a community. The utility services include electric power, heating and

cooling, potable water, liquid waste treatment and solid waste management.

The objective of the MIUS concept is to provide the desired utility ser- vices consistent with reduced use of critical natural resources, protection of the environment and minimization of cost. The program goal is to

foster, by effective development and demonstration, early implementation

of the integrated utility system concept by private or public organizations.

Under HUD direction, several agencies are participating in the HUDMIUS Program including the Energy Research and Development Administration,

Department of Defense, Environmental Protection Agency, Department of

Health, Education and Welfare, National Aeronautics and Space Administration, and National Bureau of Standards. The National Academy of Engineering has provided an independent assessment of the Program. Drafts of technical documents are reviewed by the agencies participating in the HUD-MIUS

Program. The draft of this publication received such a review and all com- ments were resolved with HUD.

i
Comparison of Computer-Predicted and Observed Energy

Uses in a Multi-Family High-Rise Apartment Building

by

James P. Barnett and Stanley T. Liu

ABSTRACT

A comparison has been made of the results of two computer programs,

the National Bureau of Standards Load Determination Program (NBSLD) and

the American Gas Association's E-CUBE Program, in predicting the energy

consumption of a multi-family high-rise apartment building located in

Omaha, Nebraska. Results are given on a monthly basis for the computed

energy values and compared with average monthly values of metered data

obtained over a five year period. Good agreement was found between the

energy consumptions predicted by the two different computer programs as well as between the predicted values and the metered data (less than 7%

difference on an annual basis).

Key Words: Building energy analysis; computerized energy

analysis; energy consumption; heating and cooling

loads

ii
TABLE OF CONTENTS

Page

1. Introduction 1

2. NBSLD - A Computer Program for Design Analysis 2

3. The E-CUBE Program 4

4. Building Description 4

5. Description of NBSLD Input Data 5

6. Results » 6

7. Conclusions 8

8. References 11

Appendix A. Air-Side Systems Simulation 15

Appendix B. Miscellaneous Correspondence 20

Appendix C. Summary of Building and System Information .... 24

Appendix D. Input Data for NBSLD 25

iii
*

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.

'

.
Comparison of Computer-Predicted and Observed Energy

Uses in a Multi-Family High-Rise Apartment Building

by

James P. Barnett and Stanley T. Liu

1. Introduction

The national concern with energy use and its related problems has

brought forth a large number of computer programs to estimate energy con- sumption in buildings. It is important that the adequacy of such com- puter simulations be determined since many of these programs will be:

1. used in the decision-making process which will determine

future energy policy in this country;

2. used by architects and engineers in designing future

buildings and in retrofitting existing ones.

At the request of the Department of Housing and Urban Development

(HUD), a study involving a computerized energy analysis on a 12-story,

118-apartment building built in 1965-1966 in Omaha, Nebraska has been

conducted at the National Bureau of Standards (NBS) by the Thermal Engineering Section of the Center for Building Technology. The study con- sisted of calculating the building energy consumption (gas and electricity) for a selected weather year by using the NBS computer program

NBSLD, and comparing the results with (1) those computed by the Northern

Natural Gas Company of Omaha under the sponsorship of the HUD regional

office at Omaha using the E-CUBE Program [1]*, and (2) the actual metered

5-year average energy consumption record of the building supplied by the

local housing authority. It should be pointed out that neither the determination of the validity of the underlying assumptions of E-CUBE nor the

verification of the correctness of this application of E-CUBE was an objective of this study. Rather, its purpose was to compare the results

of the two computer programs with the actual metered data, and with each

other. The present report documents the procedures and results of this

study.

This study is not the first attempt to verify energy consumption

predictions by comparison with metered data. Probably the best known

such study is the American Society of Heating, Refrigerating and AirConditioning Engineers’ (ASHRAE) "Project Crosscheck" [2]. In the first

phase of the ASHRAE project, five different energy analysis programs were

used to predict the heating and cooling loads of a hypothetical 20-story

building. This phase of the project served to evaluate the degree of

agreement among the five programs but not the accuracy of each individual

* Numbers in brackets indicate references listed on pages 13-14,
program. A second phase of the ASHRAE undertaking is to compare the

energy consumptions calculated by four different computer programs with

metered data on a four-story institutional building on the Ohio State

University Campus in Columbus, Ohio. The results of this second phase

should appear shortly as an ASHRAE publication.

The National Bureau of Standards computer program for heating and

cooling load calculations (NBSLD) has been verified by comparison with

experimental data from two separate research projects at NBS [3, 4], In

the first study [3], a small 20 ft by 20 ft by 10 ft (6.1 m by 6.1 m by

3 m) experimental masonry building was built within a large environmental

chamber where the temperature could be adjusted and controlled from -50 °F

(-45.5 °C) to +150 °F (+65.6 °C)

.

The building was then subjected to

typical diurnal exterior temperature fluctuations. The measured indoor

temperatures and/or heating loads agreed well (never differing by more

than 8%) with those predicted by NBSLD. In the latter study [4], a more

realistic living unit was used^-a four-bedroom, lightweight house that was completely furnished and had the activity of a six-member family simulated within. This house was also tested inside the environmental chamber where the outdoor conditions were controlled and precisely known.

The measured energy consumption data for controlled winter and summer operating conditions agreed very well with the computed values. For

example, the difference between the predicted and measured daily heating

energy requirements averaged 3.1%, with a maximum difference of 4.9%.

2. NBSLD - A Computer Program for Design Analysis

The NBSLD Program consists of various subroutines, for calculating

heat and energy transfer in structures [5], which are similar to those

recommended by the ASHRAE Task Group on Energy Requirements [6]

.

One

major extension of the program beyond the recommended ASHRAE TG procedure

is a subroutine (called RMTMP) , which allows the room air temperature to

float between two set points instead of following a prescribed temperature profile. The details of this subroutine are given in reference 5.

Figure 1 depicts the overall calculation sequence of NBSLD. The

phrases in the double lined boxes specify input data to be supplied

whereas those in single lined boxes indicate calculations to be performed.

The cycle indicators show how the computations must proceed through the rooms in a given building, and through the number of days for which the

calculations are performed. Detailed identification of the exact input

data required as well as the way in which they are prepared is given in

reference 5.

It is important to point out that the hour-by-hour heating and/or

cooling loads for a space as calculated by NBSLD represent the response

to the hourly fluctuation of the outdoor weather conditions. The loads

are calculated by solving a set of heat balance equations for the space

each and every hour; there are no scaling techniques used to arrive at

the loads. To permit NBSLD to predict energy consumption (i.e., the

2
L ULATION

Figure 1. Calculation Sequence of NBSLD
amount of energy consumed by a heating, ventilating and air-conditioning

(HVAC) system in satisfying the space heating and/or cooling load), a separate program had to be developed and added to simulate the HVAC system performance for this particular building. Details of the system

simulation are given in Appendix A.

3. The E-CUBE Program

In 1967, the Group to Advance Total Energy (GATE) contracted with

the Southwest Research Institute to develop the GATE Energy Analysis Program. This original version was very much simplified and was renamed

E-CUBE [1] , derived from the fact that the program is divided into three

general areas: Energy requirements, Equipment selection and Economic

comparisons. The economic portion of E-CUBE was not employed here.

The E-CUBE Program series utilizes as input the design heating and

cooling loads and base electrical loads. These values are projected

into hourly space loads resulting from given hourly outdoor weather data.

These projected hourly loads are calculated from the design values by a scaling procedure which takes into account the variations in dry-bulb and

dewpoint temperature, solar radiation, cloud cover, and building use and

operating schedule. The output of the first portion of the E-CUBE Program consists of hourly values for thermal and electrical loads, peak

thermal and electrical loads along with the time each occurred, and cumulative totals. The second portion of the E-CUBE Program (equipment selection) uses the loads generated by the first portion to determine the

energy consumptions of various types of HVAC systems. Up to four different plant systems can be evaluated by the E-CUBE Program in each run.

(See reference 1 for a more detailed description of the E-CUBE Program.)

The major difference between the E-CUBE Program and NBSLD is in their

procedures for heating and cooling load determination. While the former

accepts the design heating/cooling loads and modifies them in accordance

with a simple scaling procedure, the latter rigorously computes them every

hour. Both programs can account for the effects of thermostat setback

and periodic system shutdown, including the resulting thermal storage.

In addition, both programs allow the treatment of simultaneous heating

and cooling requirements.

4. Building Description

The building used in the present study (Kay-Jay Towers, Omaha Home

for the Elderly) is a 12-story, rectangular-shaped apartment complex with

the long axis running north to south. It is of brick and masonry cavity

wall type construction, with windows on the east and west sides covering

17% of the surface area on both sides. The 118 apartment units are located

above the ground floor. The ground floor is used for community spaces,

a mechanical equipment area, the manager’s office, and the manager's living quarters. The building contains a multi-zone air handling system with

an economizer cycle for heating and cooling of the ground floor space;

4
hot-water fan-coil units for the apartment units; a central, single-duct

forced-air system using 100% outside air for heating the second through

the twelfth-floor corridors with exhaust through the apartment units;

and window-type room air conditioners in one quarter of the apartments

for summer cooling. Space heating is supplied by two gas-fired, hotwater boilers, and the refrigeration equipment for the multi-zone system

consists of an electric-driven 15 kW compressor with air-cooled condenser

and direct-expansion cooling coil. Domestic hot water is supplied by

three 500,000 Btuh (146 kW) gas-fired hot-water heaters.

5. Description of NBSLD Input Data

As part of the input data for NBSLD a weather tape with hourly data

is needed. Ideally this tape should cover the same period, 1967-1971,

as the metered data. After 1965, however, the standard weather data

tapes give only information taken at 3-hour intervals, and so a pre-1965

tape had to be chosen. The period April 1960 to March 1961 was selected

as the test weather year by using the proposed ASHRAE procedure [7], The

E-CUBE procedure also uses weather year data which are not from the actual

metered period but were selected by a special GATE procedure. Therefore,

the weather data used by the NBSLD and E-CUBE Programs were not for the

same twelve months. Information concerning the equipment and building

operating schedules, and the indoor environmental conditions was furnished by the original design engineer, Raymond G. Alvine and Associates,

and the Northern Natural Gas Company, both of Omaha, Nebraska. They in

turn had obtained the data through the local housing authority and the

building manager (see Appendix B) . Building construction and HVAC system data were taken from the building design drawings (see Appendix C)

.

For the purpose of the computer analysis, the building was divided

into three zones —ground floor, west zone of the tower portion, and east

zone of the tower portion. This was the same procedure adopted by the

Northern Natural Gas Company in using the E-CUBE Program. The same occu- pancy and interior lighting schedules were used by both the E-CUBE and

NBSLD Programs, but the mechanical equipment simulation (e.g., boiler

efficiency) was to some degree different.

For the NBSLD study the amount of air infiltration into the building

(additional to that in-drawn by the mechanical ventilation) was estimated

by a separate computer program developed by the National Research Council

of Canada for high-rise buildings [8]

.

The E-CUBE analysis by the Northern

Natural Gas Company neglected the natural air infiltration in the heating

and cooling load computation.

The temperature and humidity settings used in the NBSLD calculation

are given in Appendix D,

5
6. Results

The monthly and yearly total consumptions of natural gas and electricity for the building from the metered data, the E-CUBE Program, and

the NBSLD Program, are given in Table 1.

The results for the cooling months (May-September) obtained by the

Northern Natural Gas Company using the E-CUBE Program, as compared with

the actual 5-year averaged metered data, show a large monthly deviation

in total gas consumption but a much smaller deviation (0 . 3%—9%) in total

electrical consumption. In the heating months (October-April) , the monthly

deviation was from 5% to 15% for total gas consumption, and from 0.7% to

13% for the total electrical consumption. The deviations in total yearly

consumption between the calculated and metered results were 0.5% for natural gas and 4.5% for electricity.

The comparison of the NBSLD calculated values and the actual 5-year

averaged metered data for the summer months shows a large monthly deviation in total gas consumption, with a smaller deviation in total electrical consumption (1.5%-9%). In the winter months, the deviation was from

7% to 26% for gas consumption and from 4.3% to 19% for electrical consumption. The deviations in total yearly consumption were 6.8% for gas and

6.1% for electricity.

It is seen from these results that the largest deviations in gas

consumptions occurred in the summer months, which had no space heating

requirements, so that demands were comprised entirely of domestic hotwater requirements. The domestic hot-water energy consumption was not

included in either the E-CUBE Program or the NBSLD Program, and was added

to the space heating energy requirement from an estimated load schedule

provided by the Northern Natural Gas Company. This also applied to the

electricity consumed for exterior lighting. (Schedules are listed in

Appendix D, page 30.)

A comparison of the results of the two computer programs (see Table

1) shows that they follow the same monthly trends for both gas and electrical consumptions and that the computed monthly energy consumptions

differed by less than 10% except for a difference of 14% for the February

gas consumptions. The reason the two programs have exactly the same monthly gas consumptions for June, July, and August, when space heating

requirements were absent, is that, as mentioned before, they used the same domestic hot-water schedule. The large percentage differences found

when comparing NBSLD and E-CUBE predicted gas usage to the actual gas

usage for September probably result from HVAC system operational procedures not made apparent to either NBS or the Northern Natural Gas Company.

Based on the results shown in Table 1, it is seen that both the

E-CUBE Program and the NBSLD Program gave results for yearly energy con- sumption that agreed quite well with the metered data.

6
Table

1.

Comparison

of

Metered

and

Predicted

Results

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Total

9,526

9,574

8,877

721,852

689,652

678,122
7. Conclusions

In comparing the energy consumptions predicted by the NBSLD and

E-CUBE Programs for this case study, there are three factors that could

cause differences (assuming both programs are correct in concept and

application)

1. weather data (NBSLD used a real weather year, E-CUBE used

a composite year)

2. HVAC system simulation (each program used its own);

3. air infiltration (NBSLD accounts for air infiltration and

E-CUBE does not)

The above three factors undoubtedly contributed to some differences in

the predicted results. However, since the results of the two programs

are in close agreement, either the discrepancies were very small or else

to a certain degree were self-compensating. It is possible to remove

the differences caused by factor 2 above from the predictions if one compares loads (requirements) rather than consumptions.

A comparison between the predictions of the E-CUBE and the NBSLD

Program on the overall space heating requirements for all building zones showed very close agreement (1.4%-6.2%) during the prime heating months

(November through March) . Comparison of cooling requirements could only

be made for the first floor since E-CUBE results for cooling requirements

of other zones were not available. Comparison of predicted cooling re- quirements for the first floor showed a large difference (5%-30%) between

the two programs (see Tables 2 and 3*) . The lower cooling requirements

predicted by NBSLD may have been due to the differences in the way the

two programs model thermal storage in the building materials. NBSLD uses

the response factor method whereas E-CUBE uses a single building (zone) mass and specific heat to simulate thermal storage in a building (zone).

The fact that the results for total electrical consumptions were in close

agreement (0.5%-5%), suggests that the cooling loads for the total building were in close agreement.

It should be pointed out that this study compares energy consumptions calculated for particular weather years by the NBSLD and E-CUBE

Programs to an average energy consumption value for a 5-year period. If

the year period used by the respective programs is typical of the actual

5-year period, then this would cause little error in the computed results

on the other hand, if the weather year used in the calculations is not

Note that Table 2 contains both space/equipment loads and energy consumption. Columns 2-7 are load values. Columns 8 and 9 are energy

consumptions and are computed by dividing the values in columns 2-7 by

either efficiencies or COP's (see Appendix D) and then summing them.

Table 3 contains only load values.

8
Table

2.

NBSLD

Predicted

Loads

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10
representative of the real data, this would be a source of error. Figure

2 is a plot of the heating degree days for the metered period (average

monthly value for the 5-year period) and for the NBSLD weather data for

the primary heating months, November through April. Figure 2 shows that

the NBSLD weather data has somewhat underestimated the heating degree

days in the actual data (except for April) , particularly in the months

of January and February. Therefore, one would expect the NBSLD gas con- sumptions for this period to be less than the metered ones. However,

Table 1 shows that this is not the case. The NBSLD predicted value for

November is almost exactly equal to the metered value; the NBSLD predicted

value for December is actually greater than the metered one; and it is

only in the months of January, February, and March that the NBSLD-predicted values are substantially less than the metered ones. This anomaly

is illustrated more vividly in Figure 3, where the monthly gas consumptions (November-April) are plotted against the heating degree days. It

is seen from Figure 3 that the energy consumption per degree day remains

relatively constant for the NBSLD values. This is as it should be since

the program does not give more weight to some heating degree days than

others (percent cloud cover, wind velocity, and sun angle have an effect

on energy consumption also, but there was no significant monthly difference in these variables during the heating season between the NBSLD

weather year and the actual 5-year period). However, Figure 3 also shows

the metered data to have a trend of increasing energy consumption per

degree day as the winter season progresses. Whether this observed trend

is real or caused by erroneous data is unclear at this time.

Since the energy consumption for this case was closely related to

the space load, the calculation of energy consumption for this building

was really a test of how well the NBSLD and E-CUBE Programs calculated

space thermal load. This may not be the case for many commercial buildings where the complexity of the HVAC system performance is a major factor affecting energy consumption. The results of this study indicate

that both NBSLD and the E-CUBE Programs reliably predict energy consumption for a building which is dominated by loads due to thermal transfer

through its exterior shell (skin sensitive) and which also has an ex- tremely simple HVAC system. These results should, however, not be construed to mean these two programs would necessarily be as accurate for

a building with a more complicated HVAC system. In the case of NBSLD,

since it is only a load program, it is obvious that a new system simulation routine would have to be developed to calculate energy consumption

for a different HVAC system.

11
1600

1 400

1200

1000

800

600

400

200

0

1 1 1 1 1 \ * METERED WEATHER DATA(5 YR. AVG)

A NBSLD WEATHER DATA

*

&

*

A

1

0 11 12 1 2. 3 4

MONTH (NOVEMBER—APRIL)

Figure 2. Heating Degree Days as a Function of Month

12

*0
1800

1600

1400

1200

1000

800

600

400

200

0

T i i

1 f

1 r * METERED DATA(5 YR. AVG)

* NBSLD PREDICTED VALUES

February

4^ January

A December

X March * December

^ February

A March

November A 5K November

* April

A April

1 1 1 1 I I L 200 400 600 800 1200

MONTHLY HEATING DEGREE DAYS

Figure 3. Monthly Gas Consumption as a Function of Heating Degree Days

January

16C

13
8.

References

1. W. E. Evers, "E-CUBE Computerized Energy Analysis: Energy-Equipment

Economics", ASHRAE Journal, September 1971.

2. A Field Study of Load Profiles and Energy Requirements for Heating

and Cooling System Selected for the Field Validation Test , ASHRAE

Symposium Bulletin No. 72-2, American Society of Heating, Refrigerat

ing and Air-Conditioning Engineers, New York, New York, 1972.

3. B. A. Peavy, F. J. Powell, and D. M. Burch, "Thermal Performance of an Experimental Masonry Building", ’ NBS Building Science Series 45,

1973.

4. B. A. Peavy, D. M. Burch, F. J. Powell, and C. M. Hunt, "Thermal

Performance of a Four-Bedroom Townhouse", NBS Building Science

Series 57, 1974.

5. T. Kusuda, "NBSLD, the Computer Program for Heating and Cooling

Loads in Buildings", NBS Building Science Series 69, 1976.

6. "Procedure for Determining Heating and Cooling Loads for Computerized Energy Calculations", ASHRAE Task Group on Energy Requirements

for Heating and Cooling, American Society of Heating, Refrigerating

and Air-Conditioning Engineers, 345 East 47th Street, New York, New

York 10017 (1971)

7. "Proposed Procedure for Typical Year Weather Data", ASHRAE Task

Group on Energy Requirements for Heating and Cooling, American

Society of Heating, Refrigerating and Air-Conditioning Engineers,

345 East 47th Street, New York, New York 10017, January 29, 1973.

8. D. M. Sanders, and G. T. Tamura, "A Fortran IV Program to Simulate

Air Movement in Multi-Story Buildings", DBR Computer Program No.

35, National Research Council of Canada, Ottawa, March 1973.

9. "ASHRAE Handbook of Fundamentals", Chapter 13, American Society of

Heating, Refrigerating and Air-Conditioning Engineers, New York,

New York 10017, 1972.

10. C. W. Coblentz, and P. R. Achenbach, "Field Measurements of Air

Infiltration in Ten Electrically-Heated Houses", ASHRAE Transactions, Vol. 69, 1963, p. 358.

11. "A Study of Commercial Buildings Heated With Gas", Report EES 269x,

Engineering Experiment Station, the Ohio State University, Columbus,

Ohio (Charles F. Sepsy, Project Supervisor, Department of Mechanical Engineering)

14
Appendix A. Air-Side Systems Simulation

The first floor of the building employed a multi-zone air handling

system which supplied processed air to each of five zones. The supply

air temperature to each zone was regulated by the hot and cold deck

dampers according to the zone thermostat.

To simplify the analysis, all the zones are combined and the system

is treated as a single zone double duct system such as depicted in Figure Al.

The following notations are used to describe the system simulation

equations; most of them are depicted in Figure Al (input variables

underlined)

1. Airflow data expressed in cfm

CFMIN ; minimum outdoor air ventilation

CFML : air leakage to the zone through cracks and

openings in the building exterior walls

CFMV : outdoor ventilation air which is brought

into the air handling system

CFMS : total airflow through the air handling

system

CFMC: airflow through the cooling coil

CFMH: airflow through the heating coil

2. Temperature data expressed in °F

DB : outdoor air temperature

TA : zone temperature

TC : temperature of the air leaving the cooling

coil

TH : temperature of the air leaving the heating

coil

TM: temperature of the air after the fan

TSUP: temperature of the air being supplied to the zone

3. Humidity ratios expressed in lb of water per lb of dry air

WA: humidity ratio of the outdoor air

15
CFMC

16

Figure

Al.

Multi-zone

System

of

HUD/Omaha
WIN: humidity ratio of the zone air

WM: humidity ratio of the air after the fan

WC: humidity ratio of the air leaving the cooling

coil

WH: humidity ratio of the air leaving the heating

coil

WSUP: humidity ratio of the air being supplied to

the zone

4. Heating and cooling loads expressed in Btu/hr

QL : zone heating and cooling load

QFAN : heat generated by the fan

QOCPL : latent heat generated by the zone occupant

QLATNT: cooling coil latent heat load

QCOILC: cooling coil load

QCOICH: heating coil load

The general equations that are used to simulate the system are then

where

TSUP = CFMH * TH + CFMC * TC

CFMS ( 1 )

QL = 60 * RHO * CP * CFMS * (TSUP - TA) (2)

CFMS = CFMH + CFMC (3)

RHO density of air in lbm/ft"^ = 0.075

CP ” specific heat of air in Btu/lbm • °F = 0.24.

These three relationships determine the values of CFMH and CFMC as follows

CFMC

TH - TC

CFMS * (TH - TA) - QL

60 * RHO * CP (4)

17
CFMH - CFMS - CFMC. (5)

By knowing the airflows through the heating and cooling coils, one can determine the coil loads as follows

QCOILC - 60 * RHO * CFMC * CP * (TM - TC)

where

+ 60 * RHO * CFMC * (WM - WC) * 1,061 (6)

1,061 = latent heat of condensation of water vapor in Btu/lbm;

QCOILH - 60 * RHO * CFMH * CP * (TH - TM) . (7)

The values of TM and WM can be evaluated by the following equations:

_ CFMV * DB + (CFMS - CFMV) * TA QFAN

CFMS 60 * RHO * CFMS * CP ( 8 )

WM

CFMV * WA + (CFMS - CFMV) * WIN

CFMS (9)

where

CFMV * CFMIN when heating is required

when cooling is required and DB > 55 °F

The room humidity ratio WIN was calculated from the following moisture

balance equation:

60 * RHO * CFMS * (WSUP - WIN) + 60 * RHO * CFML * (WA - WIN)

= QOCPL/1,061.

The value of WSUP is available from

WSUP

CFMC * WC + CFMH * WH

CFMS

18
where

WC 0.009 when the cooling coil is on (saturation

humidity ratio at 55 °F)

WC WM when the cooling coil is off

WH WM always.

The cooling coil was assumed "on" during the summer months (May

through September) as long as TM was greater than TSUP as calculated by

equation (1), while the heating coil was off during the same time. Thus

the cooling coil capacity, equation (6), can be reduced identically to

QCOILC = 60 * RHO * CFMS * CP * (TM - TSUP)

+ 60 * RHO * CFMS * (WM - WSUP) * 1,061. (11)

The economizer cycle was simulated by shutting the cooling coil off

and increasing the outdoor air quantity up to as much as CFMS while TM

was maintained at 55 °F, and by letting TSUP = TM, and WSUP = WM.

Air leakage CFML was calculated by a Coblentz-Achenbach type equation [10] :

AC = 0.272 - 0.0071 * WS + 0.019 * (TA - DB)

where

AC = number of air changes/hour = 60 * CFML

WS = wind speed in mph.

When the last formula's value for AC became negative and DB was greater

than TA, it was assumed that the air leakage was approximately 1/4 air

changes per hour. This value was obtained by a separate calculation

making use of the computer program in reference 8.

19
Appendix B.

Miscellaneous Correspondence

20
2223 Dodge Street Omaha, Nebraska 68102

Telephone 402-348-4000 i4

Northern

Natural

Company

August 22, 1973

Mr. Stanley Liu

National Bureau of Standards

Building 226, Room B-104

Washington, D.C. 20234

Dear Mr. Liu:

Attached is a copy of the electric load profile used in the

analysis of KAY-JAY Tower. Our synthesis was based on a combination of empirical data from the O.E.A. Apartments (a hi-rise building occupied by retired teachers) and actual observation of the

KAY-JAY Tower. From Ray Alvine § Associates, the design connected

load is 2.0 kw/sq. ft. in Zones 2 and 3 excluding elevators. From

O.E.A. building, the actual metered sustained peak is 1.1 kw/sq. ft.

I have drawn two axes on the accompanying chart to illustrate the

adjustment required to account for the different definitions of

peaks. Having defined the peak, the load profile was adjusted primarily by ratioing the O.E.A. building data to KAY-JAY data based

on the different peaks. Further adjustment was made to eliminate

the morning peak on O.E.A. based on observation of KAY-JAY and the

fact that O.E.A. has a central dining room.

This load profile as derived includes all equipment within the

occupied spaces. Specifically excluded are the window-type air con- ditioners, all elevator equipment and outside lighting. Exhaust fans were negligible and the circulating hot water pump electrical usage

was included in the equipment section. All living units had electric

cooking. A brief inspection of several units indicated typical domestic lighting levels, TV's (very few color), refrigerators and normal

miscellaneous appliances such as irons.

The inside temperature, as indicated by the building operator,

is 78° D.B. For the air conditioned portion of the tower, the inside

temperature is 75° D.B. Please note that only a portion of the

dwelling units were air conditioned. If you need further information,

please let me know.

Sincerely,

Dave Barnes

Marketing Consultant

DWB :blg

Attachments

21
i. Company & Product Information

Type Customer: Commercial X. Industrial

Company: Q. E.A. APARTMENTS

Address: __22Q_NQRIH. .22ND. STREET OMAHA,. NEBRASKA

Principal Product or Service: APARTMENTS

Operation: Hours/Day 24. Shifts/Day Days/Week Z Weeks/Year

Square Feet: 2

83.662 Number of Floors 12

PASSENGER

Number of Buildings: L

Number of Elevators:

Additional Building Description:

MAIL ROOM, LOUNGE, AND STORAGE AREA. TOTAL OF 132 APARTMENTS

l Type:

AREA INCLUDES A DINING ROOM. KITCHEN. LAUNDRY .

Electric Load

Connected Load:

Lighting

Motors (Including air handling and appliances)

Motors (A/C and heating) . Other

Total

Total Connected Load:

106

754

59

919

.KW

_KW

.KW

.KW

.KW

Recorded Peak Demand :. Largest Motor:_

JLiM KW/1,000 ft.* (Excludes A/C, heating & elevator motors)

JM KW, l- 4 3 KW/ 1.000 ft.* 15

III. Energy Requirements & Costs

Maximum Month:

Minimum Month:

Yearly Requirement:

Average Gas Cost

Natural Gas

Month Mcf

JULY 1,56 1 -QCI t 234

Electric

Utility Standby Fuel

Meter (Gallons)

KWH’s

66^938 . Demand (KW) Propane Oil

4U5SZ

Month

JULY

,QC_L«_

641 , 4QQ. 7.461

0 /Mcf; Average Electric Cost

Remarks —ELECTRIC AND GAS BILL NOT AVAILABLE

.0/KWH

Thermal Loads

Equipment:

Heating: HOT WATER

Capacity:

Boiler: 3,000 MBTU/Hour

Air Conditioning: ABSORPTION CHILLER A/C: 100 Tons

Refrigeration: Refrigeration: Tons

Other: Other:

V. General Information

HIGH RISE APARTMENT FOR RETIRED EDUCATIONAL EMPLOYEES. EACH APARTMENT USES

ELECTRIC RANGES AND OVENS FDR COOKING

.

22
HOURLY

DEMAND—

%

OF

RECORDED

PEAK

DEMAND

ELECTRIC LOAD PROFILE

TIME OF DAY — HR.

Total Connected Electrical Load (Less air conditioning 835_KW

heating, and elevator motors)

Recorded Peak Demand (Normally less than 5 minutes and 12 0 KW

greater than one second)

Average Daily Load Factor (Normal Operation)

(Reduced Operation)

Annual Load Factor

Tc>-yr
Appendix C. Summary of Building and System Information*

BUILDING DESCRIPTION: Omaha, Nebraska, 40° latitude, 12 stories, rectangular with large axis on North-South orientation,

all exposed glass on East and West, 82,870 sq. ft.,

masonry construction.

Mechanical System :

Zone #1 - Multi-zone air handling unit with hot-water coil, chilled

(First Floor) water cooling coil, economizer fresh air cycle, high

(5,170 ft^) recovery domestic hot-water system.

Zone #2 - Individual fan-coil units with hot-water coil, fan cycle

East Floors control; zone level control reset on hot water.

(2 thru 12)

(38,500 ft2)

Zone //3 - Same as Zone #2.

West Floors

(2 thru 12)

(38,500 ft2)

EQUIPMENT: 2-100 ton reciprocating water chillers with cooling tower,

2-1,440,000 Btu input heating boilers, 3-500,000 Btu input

gas-fired domestic water heaters, 25 kW for tower and cooling pumps, and a 10 kW heating pump.

* This information was obtained from building drawings.

24
Appendix D.' Input Data for NBSLD

1. Weather Data: National Climatic Center weather tape for Omaha,

Nebraska, 4/61 - 3/62

2. Wall Construction Data*:

L = thickness of the layer, ft.

K = thermal conductivity of the layer, Btu/hr-ft-°F

D = density of the layer material, lb per cu. ft.

C = specific heat of the layer material, Btu per (lb) (°F)

R = thermal resistance value of the layer in (hr) (sq. ft.)

(°F) per Btu

Roof

:

L K D C

.5 1 . 140. .20 6 Inch Concrete Ceiling

.208 .143 60. .20 2.5 Inch Lightweight Concrete

.125 .0283 16. .20 1.5 Inch Rigid Insulation

.0313 ,0938 70. .35 3/8 Inch Built-up Roofing

East/West

L

Exterior

K

Wall:

D C R ““ ““ ““ c=s

.3333 0.22 38.0 0.2 4 Inch Lightweight Block

.33333 0.77 125. 0.22

0.91 15/8 Inch Airspace

4 Inch Face Brick

North/South Exterior Wall

L K D C R ““

.04167 .12 58. .26 1/2 Inch Gypboard

.63542 1.0 140. 0.2

0.91 1.5 Inch Wall Furring

(Airspace)

7 5/8 Inch Concrete

.33333 ,77 125. .22

.91 1 Inch Airspace

4 Inch Facing Brick

Thermo-physical data taken from ASHRAE Handbook of Fundamentals, page

431; see reference 9.

25
Ground Floor:

L K D C R

0 . 0 . 0 . 0 . .05 Vinyl Asbestos Tile

.3333 1 . 140. .2 4 Inch Concrete Floor

.6667 .20 100. .44 8 Inch Sand and Gravel

1st Floor Ceiling

L K D C R

.0625 .02 21. .20 3/4 Inch Acoustic Tile

Ceiling

0 . 0 . 0 . 0 . 1.12 Airspace

.50 1 . 140. .20 6 Inch Concrete Floor

0 . 0 . 0 . 0 . .05 Vinyl Asbestos Tile Floor

Floor/Ceiling 2-12 •

L K D £ R

0 . 0 . 0 . 0 . 0.5 1/16 Inch Vinyl Asbestos

Tile

.5 1.0 140. .2 6 Inch Concrete

Partition Wall:

L K D C R

.125 .12 .58 0.26

.91

1 1/2 Inch Gypboard

3 Inch Airspace

.125 .12 .58 0.26 11/2 Inch Gypboard

3. Normalized Daily Schedule (24-hour profile) of Heat Input for Lighting, Equipment and Occupancy:

2 Ground Floor Zone Lighting (maximum - 2 watts/ft )

Hours 1 through 24, Fraction of Maximum

.05 .05 .05 .05 .05 .05 .50 .50 .50 .50

.80 .80 .80 .80 .80 .80 .80 .80 .80 .80

.80 .05 .05 .05

26
Ground Floor Zone Occupancy (maximum - 50 persons)

Hours 1 through 24, Fraction of Maximum

0 . 0 . 0 . o • o • o • 0 . .25 .25 .25

.25 .25 .25 .25 .25 .25 .25 .25 .25 .25

.25 0 . 0 . 0 .

East/West Zone Floors 2-12 Lighting (maximum -

2

2 watts/ (ft )-floor)

Hours 1 through 24, Fraction of Maximum

.15 .15 .15 .15 .15 .20 .25 .30 .35 .40

.40 .40 .40 .30 .30 .40 .50 .55 .55 .55

.50 .45 .35 .20

East/West Zone

'

Hours 1 through

Floors 2-12 Occupancy (maximum -

24, Fraction of Maximum

110 persons/zone)

.70 .70 .70 .70 .70 .70 .70 .70 .70 .35

.35 .35 .35

.35 .35 .70

.35 .35 .35 .35

.70

.35 .35 .35

4. Interior Environment Setting:

Ground Floor :

Heating Season (October-April) - 75 °F, relative humidity (R.H.)

unregulated

Cooling Season (May-September) - 70 °F, 50% R.H.

2nd Through 12th Floor (Apartments) :

Heating Season - 78 °F, R.H. unregulated

Cooling Season - 75 °F, 50% R.H. for A/C space (1/4 of total space);

R.H. and temperature unregulated for rest of space

5. Infiltration, Air Changes Per Hour:

Ground Floor :

AC = 0.272 - 0.0071 (WS) + 0.019 (TA - DB) for TA > DB

=0.25 for TA < DB

27
East /West Zone:

AC = 0.088 + 0.022 (WS) + 0.0016 (TA - DB) for TA > DB

=0.25 for TA < DB

where

AC = air changes per hour

WS = wind speed in mph

TA = room temperature, °F

DB = outside temperature, °F

Note that the coefficients in the above formula were found by

fitting the equation to points generated by the computer program

of reference 8.

Surface Data:

GROUND FLOOR ZONE

Surface Type

Area

ft^ Absorptivity

Ceiling 5,170

South Facing Exterior Wall 270 0.9

South Facing Window 170 0.0

West Facing Exterior Wall 540 0.9

West Facing Window 165 0.0

West Facing 760

North Facing Exterior Wall 154 0.9

North Facing 286

East Facing Exterior Wall 1,098 0.9

East Facing Window 366 0.0

Floor

28

5,170
WEST ZONE SURFACES

Area

Surface Type ft2 Absorptivity

Roof 3,500 0.9

South Facing Exterior Wall 2,100 0.9

West Facing Exterior Wall 14,025 0.9

West Facing Window 2,725 0.0

North Facing Exterior Wall 2,100 0.9

East Facing Partition 16,750

Partition Wall 3,500

EAST ZONE SURFACES

Area

Surface Type ft 2 Absorptivity

Roof 3,500 0.9

South Facing Exterior Wall 2,100 0.9

West Facing Partition Wall 16,750

North Facing Exterior Wall 2,100 0.9

East Facing Exterior Wall 13,970 0.9

East Facing Window 2,880 0.0

South Facing Partition Wall 3,500

Mechanical Ventilation:

Ground Floor:

Heating Mode - System air supply 4,100 cfm, 10% minimum outside

damper (750 cfm)

29
Cooling Mode - System air supply 4,100 cfm, economizer controlled

outside air with minimum setting at 10% (750 cfm)

East/West Zone ; 3,500 cfm each, all outside air

8. System Efficiency:

Boiler - See Figure D1 for partial load efficiencies used.

Ground Floor A/C - COP = 3.0

Apartment Room Air Conditioner » COP = 1.75

Domestic Hot-Water Heater Eff. = 0.7

9. Domestic Hot-Water Schedule (24-hour profile)

Maximum Value - 1.5 x 10^ Btu

Hours 1 through 24, Fraction of Maximum

.02 .02 .02 .02 .02 .02 ,02 .30 .30 .30 .30 .30

.30 .30 .30 .30 .30 .30 .30 .20 .20 .20 .20 .20

Exterior Lighting Schedule (24-hour profile)

Maximum Value - 4 kW

1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0

0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 1.0 1.0 1.0 1.0

30
THE

OHIO

STATE

UNIVERSITY

ENGINEERING

EXPERIMENT

STATION

LEGAL

AIDS

BUILDING

[11]

% ‘A0N3I0UJ3 aanoa

31

%

OF

RATED

LOAD
NBS-114A (REV. 7-73)

U.S. DEPT. OF COMM. BIBLIOGRAPHIC DATA

SHEET

1. PUBLICATION OR REPORT NO. NBSIR 76-1177

2. Gov't Accession

No.

3. Recipient’s Accession No.

4. TITLE AND SUBTITLE

COMPARISON OF COMPUTER- PREDICTED AND OBSERVED

5. Publication Date June 1977

ENERGY USES IN A MULTI-FAMILY HIGH-RISE

APARTMENT BUILDING

6. Performing Organization Code

7. AUTHOR(S)

J.P. Barnett and S.T. Liu

8. Performing Organ. Report No.

9. PERFORMING ORGANIZATION NAME AND ADDRESS

NATIONAL BUREAU OF STANDARDS

DEPARTMENT OF COMMERCE

WASHINGTON, D.C. 20234

10. Project/Task/Work Unit No. 4606370

11. Contract/Grant No.

12. Sponsoring Organization Name and Complete Address (Street, City, State, ZIP)

Department of Housing and Urban Development

13. Type of Report & Period Covered

Final

Office of Policy Development and Research

Washington, D.C. 20410

14. Sponsoring Agency Code

15. SUPPLEMENTARY NOTES

16. ABSTRACT (A 200-word or less factual summary of most significant information. If document includes a significant

bibliography or literature survey, mention it here.) A comparison has been made of the results of two computer programs, the National

Bureau of Standards Load Determination Program (NBSLD) and the American Gas Asso

ciations E-CUBE program, in predicting the energy consumption of a multi-family

high-rise apartment building located in Omaha, Nebraska. Results are given on a monthly basis for the computed energy values and compared with average monthly

values of metered data obtained over a five-year period. Close agreement was found between the energy consumption predicted by the two different computer

programs , as well as between the predicted values and the metered data (less than

7 A difference on an annual basis).

17. KEY WORDS (six to twelve entries; alphabetical order; capitalize only the first letter of the first key word unless a proper name; separated by semicolons

Building energy analysis; computerized energy analysis; energy consumption;

heating and cooling loads.

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(THIS REPORT)

1 ! For Official Distribution. Do Not Release to NTIS i 1 UNCL ASSIFIED 35

Order From Sup. of Doc., U.S. Government Printing Office Washington, D.C. 20402, SD Cat. No. 03

20. SECURITY CLASS

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22. Price

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