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Reference

NBSIR 86-3392

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NATL INST OF STANDARDS & TECH R.I.C.

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Burch, Douglas M/Comparison of measured QC100 U56 NO.86-3399 1986 V19 C.1 NBS-P Comparison of Measured and

Predicted Sensible Heating and

Cooling Loads for Six Test

Buildings

D.M. Burch

G.N. Walton

B.A. Licitra

K. Cavanaugh

U.S. DEPARTMENT OF COMMERCE

National Bureau of Standards

Gaithersburg, MD 20899

June 1986

QC

100

• U56

86-3399

1986

ired for:

:ric Power Research Institute

MBS

RESEARCH

INFORMATION CENTER NBSIR 86-3399

COMPARISON OF MEASURED AND

PREDICTED SENSIBLE HEATING AND

COOLING LOADS FOR SIX TEST

BUILDINGS

D.M. Burch

G.N. Walton

B.A. Licitra

K. Cavanaugh

U.S. DEPARTMENT OF COMMERCE

National Bureau of Standards

Gaithersburg, MD 20899

June 1986

Prepared for: Electric Power Research Institute

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

NATIONAL BUREAU OF STANDARDS. Ernest Ambler. Director

CONTENTS

Page

Abstract • • 1

1. Introduction... i 1

2. Description of Computer Programs... 2

2.1 Thermal Analysis Research Program (TARP) 2

2.2 Electric Power Research Institute Methodology for

Preferred Systems (EMPS) ..2

3. Description of the Test Buildings 2

4. Instrumentation and Measurement Technique.... 3

5. Comparisons of Space Conditioning Loads without a Partition Wall 4

6. Comparisons of Space Conditioning Loads with a Partition Wall 7

6.1 Description of Interior Mass Features 7

6.2 Results 8

7. Comparisons of Predicted Space Heating Loads to Steady-State Theory....

8

8. - Summary and Conclusions 8

Acknowledgments ...... 9

References 9

Tables, 1-4 11

Figures, 1-10

iii
'
COMPARISON OF MEASURED AND PREDICTED SENSIBLE HEATING AND COOLING

LOADS FOR SIX TEST BUILDINGS

D. M. Burch, G. N. Walton, B. A. Licitra, and K. Cavanaugh

ABSTRACT

Hourly sensible heating and cooling loads for six test buildings were predicted using two computer programs, called TARP and EMPS. The predicted loads were

compared to corresponding measured loads for winter heating, spring heating, and summer cooling periods. Both computer programs predicted the general trends

of the measured data. During the winter period, cumulative sensible heating loads

predicted by TARP agreed with measured loads within an RMS average difference of

11.5%, and predicted peak sensible heating loads agreed within an RMS average

difference of 12.1%. During the winter period, poorer agreement was obtained with

EMPS. During the summer period, cumulative sensible cooling loads predicted by

EMPS agreed with measured loads within an RMS average difference of 14.8%, and

predicted peak sensible cooling loads agreed within an RMS average difference of

16.5%. During the summer period, poorer agreement was obtained with TARP. The

agreement between predicted and measured loads is comparable, and in many instances

better, than that obtained in similar computer program validation studies.

Keywords: Thermal Analysis Research Program (TARP); EPRI Methodology for Preferred

Residential Systems (EMPS); Validation of computer programs; Whole

Building Performance; Heating Loads; Cooling Loads; and Energy

Conservation.

1. INTRODUCTION

Computer programs are currently available that perform hourly building

energy simulation analysis. Building designers, architects, and building owners

use these computer programs to size HVAC equipment, to predict peak demands, or

to predict annual energy costs. Moreover, such programs are used to minimize

annual energy costs by investigating trade offs in the envelope design, selection

of HVAC systems and equipment, and by analyzing various methods of building

operation. In addition, many utility companies are interested in the prediction

of accurate hourly space conditioning electrical loads in order to establish the

effects of building/system trade offs on utility system loads.

The heat-transfer processes that occur in buildings are very complex and can

not be mathematically formulated in a precise manner without incurring excessive

amounts of computer time and memory. As a result, the heat-transfer algorithms

contained in computer programs contain simplifying approximations. Some of these

approximations are discussed later in the paper. In isolated cases, these algorithms may be incorrectly applied. Moreover, computer programs require that the

heat-transfer properties for the materials comprising the building envelope be

specified as input. In most cases, these heat-transfer properties are obtained

from handbooks and may differ from actual values by 10% or more. These factors

cause predicted space conditioning loads to deviate from actual measured loads.

In order to determine whether computer programs are sufficiently accurate to permit

them to be utilized for the purposes outlined above, a need exists to quantify the

difference between computer-predicted and measured space heating and cooling

loads for full-size buildings.

1
In response to the above interest, the Electric Power Research Institute

(EPRI), the research organization representing the electric utility companies,

sponsored a study at the National Bureau of Standards (NBS) to verify the accuracy

of the computer program, called the EPRI Methodology for Preferred Residential

Systems (EMPS) prior to its wide dissemination and use by the electric utility

companies. For this study, measured hourly sensible conditioning loads for six

test buildings [1,2] are compared to corresponding predicted values using EMPS

and the Thermal Analysis Research Program (TARP). TARP is considered to be one of

the most sophisticated contemporary computer programs for predicting space heating

and cooling loads of buildings because it models many of the heat-transfer processes

more precisely than other computer programs. It was believed to provide a good

reference computer program for verifying the accuracy of EMPS. EMPS (version

2.1) was previously compared to measured space conditioning loads for the same six

test buildings [3]. In the present study, a revised version of EMPS 2.1 containing

improved solar algorithms is used.

2. DESCRIPTION OF COMPUTER PROGRAMS

2.1. Thermal Analysis Research Program (TARP)

TARP is a research computer program developed at NBS. It is written in

FORTRAN 77 with an emphasis on program portability. Its computer algorithms

are partly based on subroutines from the Building Loads Analysis and Systems

Thermodynamics (BLAST) computer program. TARP computes space conditioning loads

by performing a detailed heat balance on each zone of a building. TARP Is unique

in that it determines air exchange between zones and across the building envelope.

Transient conduction heat transfer is computed using conduction transfer functions.

TARP, however, does not contain HVAC system and equipment simulation algorithms.

Further information on TARP is contained in ref. [4].

2.2 Electric Power Research Institute Methodology for Preferred Systems (EMPS)

EMPS 2.1 is an integrated package of three computer programs written in FORTRAN

that allows users to predict hourly space heating and cooling loads in conventional

and passive-solar residences, and to determine the costs to both the owner and the

utility of the energy use. In this study, only the energy analysis portion of

EMPS is used. The energy analysis portion uses an electrical analog R-C network

to calculate transient thermal loads for a building. Up to ten thermally coupled

building spaces may be represented. The coupling between spaces includes conduction

between partition walls/floors but does not include convective coupling as contained

in TARP. The thermal loads and equipment simulations are carried out simultaneously

at each time step (1 hour or less). System simulations are provided for central

and/or unitary heating and/or cooling systems. A major focus of the EMPS program

is on the residential system options, which include two-stage heat pumps, groundcoupled heat pumps, and utility controlled load cycling. The program was developed

by Arthur D. Little, Inc. and is currently available from the EPRI Software Center.

Further information on EMPS is contained in ref. [5].

3. DESCRIPTION OF THE TEST BUILDINGS

Six 20 ft (6.1 m) by 20 ft (6.1 m) , one room, test buildings with a 7-1 ft

(2.3 m) high ceiling were constructed outdoors at NBS located in Ga 1 the

r

s hu rv , UP.

A photograph of one of the test buildings is given in fig. 1. These buildings

have the same floor plan and orientation.

2
They were identical, except for the wall constructions, which were as follows:

Building No. 1. Building No. 2.

Building No. 3.

Building No. 4.

Building No. 5.

Building No. 6.

Insulated lightweight wood frame,

Uninsulated lightweight wood frame,

Insulated masonry (outside mass),

Uninsulated masonry,

Log , and

Insulated masonry (insulation sandwiched between inside and

outside mass).

A detailed description of the walls of the buildings is given in ref. [6].

The properties of the walls are given in table 1. The steady-state thermal

resistances for the walls of building Nos. 1, 3, 5, and 6, as well as those for

building Nos. 2 and 4, were designed to be approximately equivalent, but in fact

turned out to be somewhat different. With the exception of building No. 6, an effort was made to use construction representative of current practices of the

United States.

Each building contained two double-hung windows on both the north and south

walls. Each window contained an insulating glass glazing fitted with an exterior storm glazing. Each building had a 19.5 ft^ (1.81 m^) hollow metal

door filled with perlite insulation on the east wall.

The edges of the concrete slab-on-grade floors were insulated with 1-inch-

-thick (25 mm) polystyrene insulation at both the inner and outer surfaces of the

footing. Two-inch-thick (50 mm) polystyrene insulation was installed over the top

surfaces of the slab-on-grade floors in order to reduce the effect of seasonal

variations in earth heat transfer.

Each building contained a pitched roof forming an attic space vented with

soffit and gable vents. Eleven inches (280 mm) of glass-fiber blanket insulation [R-34 h’ft^*F/Btu (R-6.0 m^’K/W)] was installed over the ceiling.

Each building was equipped with a centrally located 4.1 kW electric forced-air

heating plant equipped with a 13,000 Btu/h (3,800 W) , split, vapor-compression,

conventional residential air-conditioning system.

A detailed description of the heat-transfer properties for the buildings is

given in ref. [6]

.

4. INSTRUMENTATION AND MEASUREMENT TECHNIQUE

The instrumentation and measurement technique used have been described in

detail in ref. [6]. A brief synopsis is given below.

A weather station was located at the test site. It contained a rotatingcup anemometer for measuring the wind speed, two pyranometers for measuring the

hemispherical solar radiation incident on a south-facing vertical surface and

a horizontal surface, and a lithium-chloride transducer for measuring the outdoor relative humidity. The outdoor temperature was measured with a thermocouple

mounted 1 ft (0.3 m) from the center of the north wall of an instrument building

located at the test site.

The total electrical energy utilized by each building was measured using a watthour meter equipped with a demand metering device that generated a contact

3
closure for each 3.6 Wh consumed.

The cumulative sensible cooling load (Qs ) was determined from the relation:

P

Qo = m*C_ / AT'dt (1)

P

0

where

m = mass rate of air through cooling equipment, lb/h (kg/s);

C = specific heat of air, Btu/lb*F (J/kg‘K);

AT = temperature drop of air across cooling plant, F (°C);

t = time , h ( s ) ; and

P = period of time, h (s).

The sensible cooling load was experimentally determined by integrating the temperature drop (AT) during the periods when the air-distribution blower operated.

The temperature drop (AT) was measured with a multi-junction thermopile installed

between the supply and return of the air conditioning system. The mass flow rate

(m) of air through the cooling equipment was measured using a pitot-static airflow

measuring device mounted in a long, straight return duct.

The latent loads were determined by collecting and weighing condensate from

the air conditioners at hourly intervals in large cyclinders. These measurements

were not meaningful at hourly intervals due to condensation on the interior walls

of the cylinders during cool night periods, suction of condensate back into the

condensate lines when the air conditioners operated, and time delays between condensation formation and collection in the cylinders. These experimental difficulties

prevented meaningful comparisons between predicted and measured hourly latent loads.

The indoor temperature and indoor relative humidity within each building were measured at various locations with thermocouples and a transducer, respectively.

Winter infiltration rates for each building were measured under a wide range

of outdoor temperatures and wind speeds. The data obtained for each building were fitted to an empirical equation. The coefficients for each equation were specified as input to the programs. Summer air infiltration rates for each

building were measured and found to be weakly dependent on outdoor conditions.

Constant summer infiltration rates were specified as input to the programs. The

infiltration rates for the test buildings were less than 0.2 volume changes per

hour and had a very small effect on the space heating and cooling loads of tin* test buildings.

Data acquisition systems having 100 channels were installed in building N 1, 3, and 5. Each system served the building in which it was located, and th.- even number building located across from it. Data were recorded at hourly int--rv.il;.

5. COMPARISONS OF SPACE CONDITIONING LOADS WITHOUT A PARTITION WALL

A geometric description of each building including the heat -t rans t * r pr i-*s of its components, an operation schedule that included a constant internal l--ad of about 290 W and a thermostat set temperature, and an outdoor climatic fillfor winter heating, spring heating, and summer cooling periods were sp.-cit i

.

•

<

i

as input to the two computer programs. The thermostat set temperatures wi-n4
68 F (20°C) for heating and 76 F (24°C) for cooling. The three periods covered in

the analysis were:

Predicted and measured space conditioning loads were compared during the last three

days of each period. Outdoor temperature and solar insolation data for the three

periods are given in fig. 2.

Cumulative sensible conditioning loads for the six test buildings predicted by

TARP and EMPS are compared to corresponding measured values in fig. 3. Each comparison consists of three bars. The first bar is the TARP cumulative load, the second

bar is the measured cumulative load, and the third bar is the EMPS cumulative load.

The height of a bar corresponds to the magnitude of the cumulative load. The

cumulative loads predicted by both programs track the general trend of the measured

data. From figure 3B and 3C, it is seen that a thermal mass effect is present in

the spring heating and summer cooling periods. Here the heavyweight masonry and log

buildings are seen to consume less space heating and cooling energy than identical

lightweight buildings having equivalent thermal resistance in their building

envelopes. Wall mass is seen to be more effective when it is placed inside, as opposed to outside, the wall insulation. When this thermal mass effect was experimentally observed, both computer programs predicted the correct relative cumulative

load. That is, the ranking of the test buildings and the relative magnitudes of

the predicted thermal mass effects were the same as those for the actual test

buildings.

The largest percentage differences between predicted and measured cumulative

heating loads during the winter period occurred for building No. 6. A thermographic

survey of building No. 6 indicated that this building contained thermal anomalies

consisting of missing perlite insulation in the walls. A finite-difference analysis

[7] indicated that multi-dimensional heat flow patterns in the walls contributed

to the anamolous behavior of building No. 6.

Hourly sensible conditioning load profiles for the six test buildings predicted

by the two computer programs are compared to corresponding measured values in fig. 4

for the winter heating period, in fig. 5 for the spring heating period, and in

fig. 6 for the summer cooling period. The hourly sensible conditioning loads predicted

by the two computer programs track the general trend of the measured loads. Note that

in many instances the TARP and EMPS computer predicted loads tracked each other more closely than the measured loads. This is because both computer programs contain very

similar heat-transfer assumptions and approximations, and identical building description data is specified as input to both programs. Predicted and measured cumulative

loads, and predicted and measured peak loads, are compared in Table 2 for the

winter heating period, in table 3 for the spring heating period, and in Table 4

for the summer cooling period. In each table, the A portion pertains to TARP and

the B portion pertains to EMPS. At the bottom of each column, the percentage

difference is the root-raean-square (RMS) average percentage difference.

In tables 2-4, the peak space conditioning load (Qp) was determined using the

relation:

winter heating period

spring heating period

summer cooling period

February 21 - March 5, 1982

April 13 - April 25, 1982

July 25 - August 5, 1982.

Qp - (Qi-1 + Qi + Qi+1 )/3 ( 2 )

5
where Qi-i = space cooling load one hour prior to the peak, W;

Qi = space cooling load at peak, W; and

Qi+1 = space cooling load one hour after the peak, W.

The above relation was used to smooth out fluctuations in load caused by the on/off

operation of the thermostat. Fluctuations in load were particularly apparent in

the measured summer cooling loads.

During the winter heating period, better overall agreement was obtained with

TARP (see Table 2). For this period, TARP predicted cumulative heating loads

within a range from -13.4 to 19.9% with an RMS average difference of 11.5% and the

peak heating loads within a range from -21.5 to 1.5% with an RMS average difference

of 12.1%. During the same period, EMPS predicted cumulative heating loads within

a range from -21.7 to 29.5% with an RMS average difference of 19.1% and peak heating

loads within a range from -27.6 to 6.1% with an RMS average difference of 17%.

During the spring heating period (see Table 3), the RMS average differences

for both TARP and EMPS tended to be larger than the winter values given in Table

2. A factor that may have contributed to this result is that earth heat transfer

is a larger percentage of the overall envelope heat transfer during mild climatic

periods. Since the earth heat transfer is imprecisely modeled in both computer

programs, larger discrepancies may occur during mild climatic periods. For the

spring period, better agreement between measured and predicted loads was obtained

with TARP.

During the summer period (see Table 4), cumulative cooling loads predicted

by TARP agreed with measured values within a range from 7.8 to 36.6% with an RMS

average difference of 24.9%, and peak cooling loads predicted by TARP agreed with

measured values within a range from 6.2 to 38.5% with an RMS average difference

of 26.6%. During the same period, EMPS predicted cumulative cooling loads within

a range from -1.3 to 30.3% with an RMS average difference of 14.8% and peak cooling

loads within a range from -9.5 to 29.1% with an RMS average difference of 16.5%.

During the summer period, better overall agreement was obtained with EMPS.

Differences between predicted and measured space heating and cooling loads

for the above comparisons were believed to be due to the following factors: uncer- tainties in the heat-transfer properties specified as inputs to the program; simplifying approximations used in the algorithms of the two programs; and experimental error in the measured loads and the weather parameters.

A complete description of the building envelopes including the heat-transfer

properties for the materials comprising the building envelopes was specified as input

to the programs. Heat-transfer properties were obtained from handbooks and may

have differed from actual values by 10% or more. Variability in the construction

and the presence of a few small thermal anomalies may have introduced additional

uncertainty. The amount of framing was estimated from photographs taken during

the construction of the buildings. Differences may have existed between these

estimates and the actual construction.

A series of outdoor temperatures was specified as input to the computer

programs and served as a boundary condition. A study of the microclimate surrounding the buildings indicated that the outdoor temperature at different locations

varied within a range of ± 2 F (± 1°C) at any instant. The outdoor temperature was considered to be uncertain by this amount.

During the winter heating period, the indoor temperature was specified as a

6
constant that corresponded to the average of the hourly indoor temperature measured

at the mid-height level. The effect of time fluctuations of the indoor temperature as a result of thermostat control was not taken into account in the computer

programs.

Both computer programs contain simplifying approximations. A few of the more

important ones include: a uniform indoor temperature; one-dimensional heat transfer;

and constant heat-transfer properties. The indoor temperature specified in the

computer programs is the mid-height value. The indoor temperature within the

buildings was observed to be stratified by as much as 8 F (4°C) during certain

periods. This caused the floor and ceiling heat-transfer surfaces to be modeled

with an inexact boundary condition temperature. Although state-of-the-art, the

one-dimensional heat-transfer assumption caused heat transfer at corners and within

the earth beneath the slab-on-grade floors to be imprecisely predicted. With

regard to the constant property assumption, mean temperature has been shown to

have a significant effect on the thermal conductances of insulation materials.

Other simplifying assumptions that may have affected the predicted results include

isotropic diffuse solar radiation and constant ground reflectance.

With regard to experimental error, the heating loads involved the measurement of electrical energy that was believed to be very accurate having an uncertainty

of ± 0.25%. On the other hand, the sensible cooling loads were computed as the

product of a mass flow rate of air through an air conditioner and an integrated

temperature rise across the unit. The airflow measurement was believed to be

uncertain by ± 5-8%. Including the uncertainty in the temperature difference

measurement, the overall uncertainty in the cooling load measurement could have

been as large as ± 12%.

In the comparisons of figures 4-6, the differences between predicted and

measured loads are larger during some periods. For instance, a larger difference

occurs during the first day of the heating load comparison for building No. 6

(see figure 4F). It was not possible to identify the specific factor(s) that

contributed to these larger differences because of the very large number of

parameters specified as input to the programs.

In view of the above uncertainties and simplifying assumptions, the level

of agreement between predicted and measured space heating and cooling loads is

considered to be good. This level of agreement is comparable and in most cases better than that for other similar computer validation studies cited in the literature [8-11].

6. COMPARISONS OF SPACE CONDITIONING LOADS WITH A PARTITION WALL

6.1. Description of Interior Mass Features

An east/west partition wall containing a standard-size door opening was installed in building Nos. 2 and 4 (see fig. 7). Each partition wall divided the

interior of the building into north and south rooms having approximately equal

floor area. The partition walls consisted of nominal 2 X 4 in (50 X 100 mm) studs

with 1/2 in (13 mm) gypsum board installed on either side. The total wall cross section framed was 27 ft 2 (2.5 m

2

) out of a total partition wall cross section of

145 ft 2 (13.5 m

2 ), giving a framing fraction of 19%. Each of the rooms was served

by separate supply and return ducts that provided approximately equal volumes of

conditioned air to each room. The thermostat for controlling the heating and

cooling plant was located 5 ft (1.5 m) above the floor at the north side of the

7
partition wall (see fig. 7). Interior room surfaces were painted with off-white

latex paint. For some of the summer tests, 1280 lb (581 kg) of office type

furniture (desks and chairs) was placed in building No. 2.

6.2 Results

A summer cooling test was conducted using building Nos. 2 and 4 with a partition

wall but without office furniture from July 18 - Aug. 26, 1983. Hourly sensible

cooling loads predicted by TARP and EMPS are compared to corresponding measured

values during the last three days of the test period in fig. 8. Good agreement

was obtained between computer-predicted and measured results for both programs.

After the furniture was installed in building No. 2, a summer cooling test was conducted from Aug. 31 - Sep. 6, 1983. Hourly sensible cooling loads predicted

by TARP and EMPS are compared to measured values for corresponding climatic

conditions during the last three days of the test period in fig. 9. As in the case of the previous results, very good agreement was obtained between computerpredicted and measured results.

It should be pointed out that the foregoing results have the limitation that

direct solar window gain did not occur because the roof overhang completely

shaded the south-facing windows. Therefore, direct solar gain algorithms in the

two computer programs were not exercised.

7. COMPARISONS OF PREDICTED SPACE HEATING LOADS TO STEADY-STATE THEORY

Weekly average sensible heating loads predicted by TARP and EMPS are plotted

as a function of average outdoor. temperature in fig. 10. For each set of predicted

values, a best-fit straight line was obtained for the linear regime of the results.

The slope for each of these straight lines is labeled on the plot. The slope

corresponds to the overall envelope heat-transfer coefficient (K) defined by the

relation

:

K = l (Uj/Ai) + pTC

p

*I (3)

o where = thermal transmittance of the ith building component, Btu/h'ft^'

( W/m2 • K) ; O ') A^ = surface area for the ith building component, ft (m )

;

p = density of air, lb/ft 2 (kg/m 2 );

V = inside volume, ft 2 (m2

);

I = rate of infiltration, volume changes per hour; and

Cp = specific heat of air, Btu/lb*F (J/kg*K)

F

Using eq. (3), the envelope heat-transfer coefficient (K) for Building No. 2 was computed to be 199 Btu/h*F (105 W/K). This value agrees within 3.5 % of the

slope for the TARP computer predictions and within 8.3% for the EMPS computer

predictions. These results indicate that for these six test buildings TART r.

- diets the envelope heat-transfer coefficient more closely than EMPS.

8. SUMMARY AND CONCLUSIONS

Computer predictions using TARP and EMPS followed closely the gener.il trends

8
of the measured sensible conditioning loads for the six test buildings, thereby supporting the validity of both the computer programs and the measured data. TARP

tended to provide better agreement between predicted and measured sensible heating

loads during winter and spring heating periods, while EMPS provided better agreement

during summer cooling periods. During the winter period, TARP predicted cumulative

sensible heating loads within an RMS average difference of 11.5% and peak sensible

heating loads within an RMS average difference of 12.1%. During the summer period,

EMPS predicted cumulative sensible cooling loads within an RMS average difference

of 14.8% and peak cooling loads within an RMS average difference of 16.5%. This

agreement is good in view of the uncertainties associated with the measurements,

uncertainty for the heat-transfer properties comprising the building envelope, and

the simplifying approximations used in the computer algorithms.

ACKNOWLEDGMENTS

This study was sponsored by the Electric Power Research Institute.

REFERENCES

1. D. M. Burch, D. F. Krintz, and R. S. Spain, "The Effect of Wall Mass on Winter

Heating Loads and Indoor Comfort - An Experimental Study," ASHRAE Transactions,

Vol. 90, Part 1, 1984.

2. D. M. Burch, K. L. Davis, and S. A. Malcolm, "The Effect of Wall Mass on the

Summer Space Cooling of Six Test Buildings," ASHRAE Transactions, Vol. 90,

Part 2, 1984.

3. F. Y. Sorrell, T. J. Luckenback, and T. L. Phelps, "Validation of Hourly Building

Energy Models for Residential Buildings," ASHRAE Transactions, Vol'. 91, Part 2,

1985.

4. G. N. Walton, "Thermal Analysis Research Program - Reference Manual,"

NBSIR 83-2655, National Bureau of Standards, 1983.

5. R. L. Merriam and R. J. Rancatore, "EMPS 2.1 Computer Program for Residential

Building Energy Analysis - Engineering Manual," Report No. 1830-4, Arthur D.

Little, Inc., 1985, Cambridge, MA 02140.

6. D. M. Burch, W. E. Remmert , D. F. Krintz, and C. S. Barnes, "A Field Study

of the Effect of Wall Mass on the Heating and Cooling Loads of Residential

Buildings," Proceedings of the Building Thermal Mass Seminar, Oak Ridge

National Laboratory CONF-8206130 , 1982, Oak Ridge, TN.

7. F. Arumi-Noe, "Anomalous Heat Losses in the NBS Thermal Mass House 6 — Three

Dimensional DEROB Simulation," Contract Report, School of Architecture,

University of Texas, 1983, Austin, TX.

8. F. Arumi-Noe and D. M. Burch, "DEROB Simulation of the NBS Thermal Mass

Test Buildings," ASHRAE Transactions, Vol. 90, Part 2, 1984.

9. D. M. Burch, B. A. Peavy, and F. J. Powell, "Comparison Between Measured

and Computer-Predicted Hourly Heating and Cooling Energy Requirements for an Instrumented Wood Frame Townhouse Subjected to Laboratory Tests,"

ASHRAE Transactions, Vol. 81, Part 2, 1975.

9
10. R. Judkoff, D. Wortman, and J. Burch, "Measured Versus Predicted Performance

of the SERI Test House: A Validation Study," National Heat Transfer Conference,

Seattle, WA, July, 1983.

11. B. Anderson, F. Bauman, and R. Kammerud, "Verification of BLAST by Comparison

with Direct Gain Test Cell Measurements," Lawrence Berkeley Laboratory,

Report No. LBL-10619, Nov., 1980.

10
TABLE 1

Properties of the Exterior Walls of the Test Buildings

Building Thermal Resistance Mass

Active

Thermal Capacitance3

No. h *f t 2 * F/Btu m

2 *K/W lb/ft2 kg/m2 Btu/F MJ/K

1 12.2 2.1 4.4 21. 283. 0.54

2 3.6 0.63 4.2 21. 283. 0.54

3 13.7 2.4 64. 310. 283. 0.54

4 4.6 0.81 42. 210. 283. 0.54

5 10.3 1.8 17. 83. 1540. b 2.9

6 12.4 2.2 83. 410. 4470. 8.5

a Here the term "active thermal capacitance" refers to thermal

capacitance interior to the insulation or cavity air space

of the exterior wall system.

b Based on one-half log thickness.

11
Table 2

Comparison of Predicted Sensible Heating Loads to Corresponding Measured Loads

for the Winter Heating Period

A.' TARP

Building

Cumulative Load Peak Load

Measured

kWh

Predicted

kWh

Diff.

%

Measured

kWh

Predicted

kWh

Diff.

%

1 34.7 33.8 -2.7 914. 806. -11.8

2 73.7 78.1 +6.0 1786. 1741. -2.5

3 38.2 33.0 -13.4 890. 753. -15.4

4 64.3 77.0 +19.9 1690. 1602. -5.2

5 36.0 37.8 +5.3 821. 834. +1.5

6 43.1 37.8 -12.2 971. 762. -21.5

RMS Average 11.5 12.

1

Building

Cumulative

B. EMPS

Load Peak Load

Measured

kWh

Predicted Diff.

kWh %

Measured

kWh

Predicted

kWh

Diff.

%

1 34.7 31.4 -9.7 914. 742. -18.8

2 73.

7

86.3 +17.2 1786. 1895. +6 . 1 3 38.2 30.0 -21.4 890. 693. -22.1

4 64.3 83.2 +29.5 1690. 1729. +2.3

5 36.0 34.7 -3.3 821. 742. -9.6

6 43.1 33.7 -21.7 971. 703. 1K3 • O' RMS Average 19.1 17.0

12
Table 3

Comparison of Predicted Sensible Heating Loads to Corresponding Measured Loads

for the Spring Heating Period

A. TARP

Building

Cumulative Load Peak Load

Measured

kWh

Predicted

kWh

Diff.

%

Measured

kWh

Predicted

kWh

Diff.

%

1 15.7 12.4 -20.8 663. 693. +4.6

2 42.4 38.9 -8.2 1640. 1641. +0.09

3 13.1 9.18 -30.0 540. 518. -4.

1

4 24.5 31.6 +29.0 1105. 1173. +6 .

1

5 9.96 9.89 -0.8 514. 520. +1 .

3

6 8.40 4.70 -44.1 449. 325. -27.7

RMS Average 26.4 11.9

Building

Cumulative

B. EMPS

Load Peak Load

Measured

kWh

Predicted

kWh

Dif f

.

%

Measured

kWh

Predicted

kWh

Diff.

%

1 15.7 11.8 -24.6 663. 576. -13.1

2 42.4 45.8 +8.0 1640. 1768. +7.8

3 13.1 8.12 -38.1 540. 440. -18.5

4 24.5 36.3 +47.8 1105. 1260. +14.0

5 9.96 9.43 -5.3 514. 440. -14.4

6 8.40 4.07 -51.5 449. 283. -37.0

RMS Average 34.4 19.8

13
Table 4

Comparison of Predicted Sensible Cooling Loads to Corresponding Measured Loads

for the Summer Cooling Period

A. TARP

Building

Cumulative Load Peak Load

Measured

kWh

Predicted

kWh

Diff.

%

Measured

kWh

Predicted

kWh

Diff.

%

1 100.4 116.2 15.6 3280. 3544. 8.0

2 140.5 151.5 7.8 5276. 5608. 6.2

3 78.5 107.3 36.

6

2166. 2811. 29.8

4 91.6 124.5 35.8 2917. 3950. 35.0

5 81.6 99.2 21.6 2155. 2661. 23.5

6 69.6 82.1 18.1 1576. 2183. 38.5

RMS Average 24.9 26.6

Building

Cumulative

B.

Load

EMPS

Peak Load

Measured

kWh

Predicted

kWh

Diff.

%

Measured

kWh

Predicted

kWh

Diff.

%

1 100.5 99.2 -1.3 3280. 2967. -9.5

2 140.5 147.9 5.2 5276. 5467. 3.6

3 78.5 29.6 17.9 2166. 2333. 7.7

4 91.6 119.3 30.3 2917. 3767. 29.1

5 81.6 82.5 1.1 2155. 2133. -1.0

6 69.6 74.5 7.1 1576. 1967. 24.8

RMS Average 14.8 16.5

14
Fig. 1. Photograph of a test building

15

1
A. Winter heating period

Bo Spring heating period

C. Summer cooling period

Fig. 2. Climatic data for the three load comparison periods

16
INSULATED BUILDINGS UNINSULATED BUILDINGS

A. Winter heating period

INSULATED BUILDINGS UNINSULATED BUILDINGS

B. Spring heating period

INSULATED BUILDINGS UNINSULATED BUILDINGS

C. Summer cooling period

Fig. 3. Comparison of predicted cumulative sensible conditioning loads

to corresponding measured loads for the six test buildings

17
A. Insulated wood frame (No. 1) B. Uninsulated wood frame (No. 2)

C. Insulated masonry with outside D. Uninsulated masonry (No. 4) mass (No. 3)

E. Log (No. 5) F. Insulated masonry with insulation

sandwiched between inside and

outside mass (No. 6)

Fig. 4. Comparison of predicted sensible heating loads using TARP and IMPS

to corresponding measured loads for the six test buildings during

the winter heating period

18
SENSIBLE

HEATINU

LOAD.

KW

SENSIBLE

HEATINQ

LOAD,

KW

A. Insulated wood frame (No. 1) B. Uninsulated wood frame (No. 2)

!. Insulated masonry with outside

mass (No. 3)

D. Uninsulated masonry (No. 4)

E. Log (No. 5) F. Insulated masonry with insulation

sandwiched between inside and

outside mass (No. 6)

Fig. 5. Comparison of predicted sensible heating loads using TARP and EMPS

to corresponding measured loads for the six test buildings during

the spring heating period

19
SENSIBLE

COOLINQ

LOAD,

KBtu/h

O

SENSIBLE

COOLING

LOAD,

KBtu/h

***

SENSIBLE

COOLINQ

LOAD,

KBtu/h

Insulated wood frame (No. 1) B. Uninsulated wood frame (No. 2)

Insulated masonry with outside D. Uninsulated masonry (No. 4) mass (No. 3)

E. Log (No. 5) F. Insulated masonry with Insulation

sandwiched between inside and

outside mass (No. 6)

Fig. 6. Comparison of predicted sensible cooling loads using TARP and EMI’S to corresponding measured loads for the six test buildings during

the summer cooling period

20
Window

Window

Fig. 7. Schematic of test building No. 2 showing the partition wall
B. Uninsulated wood-frame (No. 2)

C. Uninsulated masonry (No. 4)

Fig. 8. Comparison of predicted sensible cooling loads using TAKP and

EMPS to corresponding measured loads for the uninsulated test

buildings with a partition wall but without office furniture

22
100

A. Outdoor climatic data

B. Sensible cooling load comparisons

Fig. 9. Comparison of sensible cooling loads predicted using TAK.P and EMPS

to corresponding measured loads for the uninsulated wood-frame

. test building (No. 2) with a partition wall and office furniture

23
A. TARP

B. EMPS

Fig. 10. Comparison of predicted heating load correlations to

steady-state theory

24
NBS-114A (rev. 2 -aci U.S. DEPT. OP COMM.

BIBLIOGRAPHIC DATA

SHEET (See instructions)

lo PUBLICATION OR

REPORT NO.

NBSIR 86-3399

2. Performing Organ. Report No. 3. Publication Date

JUNE 1986

4. TITLE AND SUBTITLE

COMPARISON OF MEASURED AND PREDICTED SENSIBLE HEATING AND COOLING

LOADS FOR SIX TEST BUILDINGS

5. AUTHOR(S)

D. M. Burch, G. N. Walton, B. A. Licitra, and K. Cavanaugh

6. PERFORMING ORGANIZATION (If joint or other than NBS. see instructions)

NATIONAL BUREAU OF STANDARDS

DEPARTMENT OF COMMERCE

WASHINGTON, D.C. 20234

7. Contract/Grant No.

8. Type of Report & Period Covered

9. SPONSORING ORGANIZATION NAME AND COMPLETE ADDRESS (Street. City. State. ZIP)

EPRI

10. SUPPLEMENTARY NOTES

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

bibliography or literature survey, mention it here)

Hourly sensible heating and cooling loads for six test buildings were

predicted using two computer programs, called TARP and EMPS. The

predicted loads were compared to corresponding measured loads for winter

heating, spring heating, and summer cooling periods. Both computer

programs predicted the general trends of the measured data. During the

winter period, cumulative sensible heating loads predicted by -TARP agreed

with measured loads within an RMS average difference of 11.5%, and

predicted peak sensible heating loads agreed within an RMS average

difference of 12.1%. During the winter period, poorer agreement was

obtained with EMPS. During the summer period, cumulative sensible

cooling loads predicted by EMPS agreed with measured loads within an RMS

average difference of 14.8%, and predicted peak sensible cooling loads

agreed within an RMS average difference of 16.5%. During the summer

period, poorer agreement was obtained with TARP. The agreement between

predicted and measured loads is comparable, and in many instances

better, than that obtained in similar computer program validation

s tud ie s .

12. KEY WORDS (Six to twelve entries; alphabetical order; capitalize only proper names; and separate key words by semicolon s) Thermal Analysis Research Program (TARP), EPRI Methodology for Preferred

Residential Systems (EMPS); Validation of computer programs; Whole

Building Performance; Heating Loads; Cooling Loads; and Energy Conservation,

13. AVAILABILITY

| X 1 Unlimited

| | 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

28

15. Price

$9.95

USCOMM-OC S043-PS0