NBS

NAT'L INST. OF STAND & TECH R.I.C.

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PUBLICATIONS li

I NBSIR 81-2358

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Analysis of Data From the Energy

Monitoring and Control System

At the Norris Cotton Federal

Office Building

/

U.S. DEPARTMENT OF COMMERCE

National Bureau of Standards

National Engineering Laboratory

Center for Building Technology

Building Equipment Division

Washington, DC 20234

September 1981

Issued November 1981

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81-2358

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Sponsored by:

The Department of Energy

Washington, DC 20585

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NBSIR 81-2358

ANALYSIS OF DATA FROM THE ENERGY

MONITORING AND CONTROL SYSTEM

AT THE NORRIS COTTON FEDERAL

OFFICE BUILDING

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William B. May, Jr.

U.S. DEPARTMENT OF COMMERCE

National Bureau of Standards

National Engineering Laboratory

Center for Building Technology

Building Equipment Division

Washington, DC 20234

September 1981

Issued November 1981

Sponsored by:

The Department of Energy

Washington, DC 20585

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

NATIONAL BUREAU OF STANDARDS, Ernest Ambler, Director
iUSMH jAic.tfi'*- t;
ABSTRACT

The Norris Cotton Federal Office Building (NCFOB) in Manchester, New Hampshire,

is a medium-size office building, occupied in September 1976, designed to serve as a demonstration and a feasibility test for energy-conserving building

features. A building energy monitoring and control system was operated as a data acquisition system over a 13-month period ending in September 1980.

Experience encountered during the checkout and operation of the system is

discussed. Results from data reduction procedures used to calculate

approximately 160 parameters describing the energy performance of the building

are presented on a monthly basis. Hourly data are also presented for daily

building operation profiles, building envelope performance, and performance of

the mechanical systems.

Key Words: building performance data; computer data acquisition; energy

conservation in commercial buildings; building envelope;

mechanical systems; energy monitoring and control systems.

iii
PREFACE

This report is one of a series of reports documenting National Bureau of

Standards (NBS) research and analysis efforts in developing energy and

cost data in support of the Department of Energy (DoE)/NBS Building Energy

Conservation Criteria Program. The work described in this report was

supported by DoE/NBS Task Order No. A008-BCS under Interagency Agreement

No. EA Ilk 01 6010.
TABLE OF CONTENTS

Page

1. INTRODUCTION 1

2. DESCRIPTION OF NORRIS COTTON BUILDING 2

3. DESCRIPTION OF DATA ACQUISITION SYSTEM 6

4. DATA REDUCTION PROCESS 9

5. RESULTS--MONTHLY PERFORMANCE PARAMETERS 19

6. RESULTS--DAILY PROFILES OF NON-HVAC ENERGY 22

7. RESULTS--BUILDING ENVELOPE PERFORMANCE 23

8. RESULTS--MECHANICAL SYSTEMS 31

9. CONCLUSIONS 35

10. REFERENCES 37

APPENDIX Detailed Description of NCFOB Energy Data Sheets 64

V
1

2

3

4

5

6

7

8

9

10

11

12

13

14

LIST OF FIGURES

Page

Schematic diagram of Norris Cotton Federal Office

Building mechanical system 39

Diagram of JC-80/55 minicomputer control system configuration

at Norris Cotton Federal Office Building 40

Format of data contained on magnetic tapes generated at the

Norris Cotton Federal Office Building 41

Diagram of electric power distribution system at Norris Cotton

Federal Office Building. Circled numbers indicate

kilowatt-hour meters 42

Sample instruction file for table-producing data retrieval

program 43

Total energy consumption at the NCFOB building boundary as calculated from JC-80 and manual readings 44

Natural gas consumption at NCFOB as calculated from JC-80

and manual readings 44

Major categories of electrical energy consumption for the

NCFOB as calculated from JC-80 and manual readings 45

Electrical energy use for lighting on lower floors of NCFOB

as calculated from JC-80 and manual readings 45

Electrical energy use for lighting on upper floors of NCFOB

as calculated from JC-80 and manual readings 46

Electrical energy use for lighting on essential circuits of

NCFOB as calculated from JC-80 and manual readings 46

Miscellaneous office electrical energy use at NCFOB as calculated from JC-80 and manual readings 47

Miscellaneous office electrical energy use at NCFOB as calculated from JC-80 and manual readings 47

Electric energy used by fan colls and solar pumps at NCFOB

as calculated from JC-80 and manual data 48

Electric energy use by heat pumps at NCFOB as calculated from

JC-80 and manual data 48

vi
LIST OF FIGURES (Continued)

Number Page

16 Mechanical equipment electrical loads at NCFOB as calculated

from JC-80 and manual data 49

17 Demand profile of total energy for lighting at NCFOB 50

18 Demand profile of office miscellaneous electric loads at

NCFOB 50

19 Electrical circuit analogy for equivalent thermal parameter

model 51

20 Comparison of average inside temperature at Norris Cotton

Federal Office Building measured by JC-80 and calculated by

ETP analysis for February 1980 52

21 Measured outdoor, indoor and structure temperatures calculated

by ETP analysis for Norris Cotton Federal Office Building

during February 1980 52

22 Measured addition of internal and heating energy to building

space of Norris Cotton Federal Office Building during

February 8-14, 1980 53

23 Measured outside and inside temperatures and structure

temperatures calculated by ETP analysis for Norris Cotton

Federal Office Building during June 20-29, 1980 53

24 Natural gas boiler efficiency as a function of boiler output

at the Norris Cotton Federal Office Building 54

25 Heating performance of heat pump system at Norris Cotton

Federal Office Building during February 1980 54

26 Cooling performance of heat pump system at Norris Cotton

Federal Office Building during July 1980 55

27 Measured performance of electric chiller at Norris Cotton

Federal Office Building during July 1980 55

28 Solar collector array efficiency at Norris Cotton Federal

Office Building 56

29 Fuel energy for heating versus calculated heating requirements

at Norris Cotton Federal Office Building during February

1980 56

vll
LIST OF FIGURES (Continued)

Number Page

30 Operating energy versus calculated heating requirements during

February 1980 at the Norris Cotton Federal Office Building 57

31 Fuel energy for cooling versus cooling requirements at the

Norris Cotton Federal Office Building during July 1980 57

32 Operating energy versus calculated cooling requirements during

July 1980 at Norris Cotton Federal Office Building 58

33 Total mechanical system efficiency for heating versus calculated

heating requirements at Norris Cotton Federal Office Building

during February 1980 58

34 Total mechanical system performance factor for cooling versus calculated cooling requirements at Norris Cotton Federal

Office Building during July 1980 59

LIST OF TABLES

Number Page

1 Analog sensor types used by JC-80 system at the Norris Cotton

Federal Office Building 60

2 Description of data loss from NCFOB data acquisition system .... 61

3 Estimates from least squares fit to equivalent thermal

parameter model using data from February 9-15, 1980 62

4 Results from equivalent thermal parameters analysis of four

data sets 62

viii
CONVERSION FACTORS

This report uses only SI units. The following conversion factors to US Customary

Units are provided for convenience during the transition to SI units.

1 °c = (1.8 °C + 32)°F

1 J/(kg*°C) == 2.39 X lO"'^ Btu/lb“F

1 kg/m2 == 0.205 lbm/ft2

1 kg/m^ == 0.063 lb/ft3

1 kJ/m2*h == 0.088 Btu/ft2*h

II= 264 gallon (US)

1 kW = 0.284 tons, refrigeration

3413 Btu/h

1 kW/°C = 1895 Btu/hr*“C

1 kWh/°C = 3.6 MJ/°C = 525.7 Btu/®F

1 kWh/m^ = 0.0961 therms /CCF

1 L/s = 2.12 cfm

1 m2 == 10.76 ft2

1 m^/s == 15,848 gpm

1 MJ/m2»yr = 0.088 kBtu/ft^^y

1 W/m2. °c = 0.176 Btu/ft2. hr* °F

ix

1 . INTRODUCTION

The Norris Cotton Federal Office Building (NCFOB) is a seven-story government

office building located in Manchester, New Hampshire. This building, first

occupied in September 1976, was intended to serve as a demonstration of and

feasibility test for a number of building energy conservation features. Each

floor utilizes different types and arrangements of heating, ventilation, and

air conditioning (HVAC) equipment and lighting systems. The concepts used in

the building include heat pumps, modular boilers, fan coil units, fin-tube

radiation, variable-volume air distribution, heat recovery, and solar energy.

The building envelope is designed to minimize thermal transmission losses by

making use of a cubical shape, minimum fenestration, massive construction, and

external insulation.

The original building design was developed by an architect/engineering firm

under contract to the General Services Administration (GSA) , the agency responsible for federal buildings [1]. The National Bureau of Standards (NBS) has

participated in the project since the design stages under contract to the

Department of Energy (DoE). Besides evaluating the performance of the lighting

systems, the user acceptance of the building, and lessons learned in operating

the NCFOB [2, 3], NBS staff members have been collecting and analyzing energy

performance data on the building.

Included as part of the NCFOB control system is a minicomputer which functions

as a monitoring, control and data acquisition system using over 700 temperature

sensors, flow-meters, watt-hour meters, and other measuring devices located

throughout the building. Hourly average data have been collected by the data

acquisition system and were compiled for approximately one year—from September

1979 to September 1980. These data have been reduced and analyzed at NBS to

produce hourly, daily, and monthly values of performance parameters, energy

usage data, and other detailed information from the NCFOB.

1
2. DESCRIPTION OF NORRIS COTTON BUILDING

2 . 1 BUILDING ENVELOPE

The envelope of the Norris Cotton Federal Office Building was designed to

minimize heating and cooling loads by making use of several innovative ideas.

The building has an approximately cubical shape to minimize surface area. The

wall design, intended to minimize thermal transmission losses in the winter and

thermal gains in the summer, uses a massive masonry construction with insulation installed on the exterior of the masonry and covered with a granite facade.

The wall has an overall heat transfer coefficient (U-value) of 0.34 W/(m2«°C)

and a mass of approximately 390 kg/m^ of surface area. The window area averages only six percent of the total wall area, and the north building wall is

completely windowless. Overhangs and fins surround the double-glazed windows

to control solar gain.

There are seven floors of offices in the NCFOB with a total office floor area

of 9072 m^. The upper six floors are approximately the same size with an aspect ratio of 1:1. The first floor is larger than the upper floors providing

a one-floor base below the cubical shape formed by the upper floors. Two sets

of entrance doors are located on the first floor. Two underground basement

levels provide parking facilities and storage.

Approximately two and one half years after the building was first occupied,

the rate at which outside air was entering the building was measured using a tracer gas technique [4]. The measurements (taken in February 1979) indicated

that the air exchange rate with all outside air dampers closed (no ventilation

air; 100 percent recirculation) was 0.75 air change per hour on the first three

floors and 0.39 on the upper four floors with a building average of 0.54 air

change per hour [2,5].

2.2 MECHANICAL SYSTEMS

As in any new building, after the NCFOB was occupied in September 1976,

differences between the design predictions for the building and the actual

operational performance became apparent. The experimental nature of the NCFOB

required that the mechanical systems be more complex than in most buildings.

Therefore, the process of overcoming start-up problems and design inadequacies

took over two years. The major problems encountered at the building have been

described in a previous paper [5]. In many cases, problems with the automatic

controls forced building operators to resort to manual operation of systems.

The period during which the automated data acquisition system was collecting

data followed the "break-in" period, and during this time the NCFOB was not

operating as designed but operating in the best way possible given shortcomings

of the installed systems and controls. The following descriptions reflect the

building operation during the monitoring period.

Distribution and Terminal Equipment : The mechanical system at the NCFOB

includes a central plant providing heated and chilled water for two major distribution subsystems which supply heating and cooling for different parts of

the building. The first three floors of the building are served by a unitary

water-loop heat pump system consisting of 57 water-to-air heat pumps having

2
a combined capacity of 350 kW for heating and 280 kW for cooling. The first

and third floors use large ceiling-mounted heat pumps for the perimeter zones

and floor-mounted heat pumps for the core zones. The second floor has small

console-type heat pumps on the perimeter and larger ceiling-mounted heat pumps

for the core. A closed water loop supplies all of the heat pumps with thermal

energy for heating, and acts as a heat sink for cooling. During the cooling

season, thermal energy is removed from the heat pump loop through a closedcircuit evaporative cooler in the basement. The loop may be heated by boilers

in the central plant and operates at a temperature of 18-27°C depending on the

season.

The upper four floors of the building are served by several types of central

hot-water heating and chilled-water cooling systems, and the terminal equipment

on the upper four floors varies from floor to floor. The fourth floor has a standard variable air volume (VAV) system with perimeter hot-water finned-tube

radiation to offset transmission losses. The fifth floor has a variable air

volume system with a separate single-duct system and a large floor-mounted

heating-only two-pipe fan coil unit to offset transmission losses. The sixth

and seventh floors each have variable air volume for the core and three ceilingmounted four pipe fan coil units for perimeter heating and cooling. The fourth

and fifth floors and the sixth and seventh floor cores do not have local

chllled-water-cooling equipment but receive chilled air from the central

plant.

A hot water loop supplies the equipment on the upper four floors and also

supplies a few unit heaters and fin-tube radiators located in the basements.

The hot water loop is maintained at a temperature of from 37-60°C depending on

the magnitude of the hot water system load. This loop is shut down during the

cooling season.

A chilled water loop supplies water to the six four-pipe fan coils on the upper

two floors. The chilled water system also supplies a coll in the air handling

unit serving the upper four floors. This system is not operational during the

heating season.

The NCFOB has two separate systems for handling outside air. One system, the

heat pump air system, supplies ventilation air to the lower three floors by

bringing outside air down from the penthouse mechanical room where the supply

fan, return fan, outside air dampers, and return air dampers are located.

Cooling and heating of the air is accomplished by having the air pass in parallel

through six floor-mounted heat pumps before reaching interior areas of the

lower three floors. This air system is a variable air volume type.

The upper four floors are supplied with ventilation air through a second air

handling system located in the penthouse. This system, which is also a VAV

system, is configured much like the heat pump air system, except that the only

heating and cooling equipment in the air stream is a chilled water coil in the

air handling unit. A heat pipe heat recovery system is used to preheat the

outside air using energy recaptured from the exhaust air.

3
In addition to the main air-handling systems, untreated ventilation air is

provided for the two below-grade parking levels and a mechanical equipment

penthouse is heated and ventilated.

During the data acquisition system monitoring period, the space temperature

thermostat setting was 18°C for heating and 25.5°C for cooling with a winter

setback to 15.5°C from 6 pm to 5 am during the week and all day on weekends

and holidays.

Plant Equipment ; The NCFOB has a number of energy conversion devices in a central plant utilizing natural gas, fuel oil or electric power to provide

heated or chilled water for the building water loops. Figure 1 is a schematic

of the central plant equipment in the NCFOB. Four-55 kW natural gas modular

boilers and two number two fuel oil modular boilers (not shown in figure 1) can supply hot water to the heat pump and hot water loops. The oil boilers

are used as backup equipment in the event of an interruption of natural gas,

or can be used during winter operation in sequence with the gas boilers to

meet higher than expected heating loads. A 211 kW electric reciprocating

chiller and an 88-kW hot water driven absorption chiller provide chilled water.

Electric power for the reciprocating chiller can be purchased or supplied by a 150-kVA natural-gas-fueled engine-generator set with heat recovery to hot water

from engine and exhaust cooling. During the monitoring period the electric

chiller was always driven by purchased power. The absorption chiller was used in sequence with the electric chiller and was seldom operated, since the

electric chiller capacity was sufficient to meet the load in most cases.

Solar Energy System ; A solar energy system is installed at the NCFOB and

includes 353 m^ of liquid-type flat-plate collectors mounted on the roof of

the building at an angle of 45 degrees. In the winter, the system is operated

with an ethylene-glycol/water solution as the collector fluid, and a heat

exchanger is used between the collector loop and the building solar storage

loop. For summer operation, water is used as the collector fluid and the heat

exchanger is bypassed. Energy collected in the solar array can be stored in

one of three 37.850 k£ storage tanks located in the basement.

The NCFOB solar system is used to supply energy to the service hot water system.

If no solar energy is available, the service hot water is heated by a natural

gas-fired storage water heater. Energy for the hot water heating system may

be provided by the solar system during the spring and fall. During midwinter,

the heating water system temperature is raised to 60°C and at this temperature

the efficiency of the existing solar system is too low for any usable energy

to be collected.

Controls ; The NCFOB has two distinct automatic control systems for the

mechanical equipment. A pneumatic system provides basic local loop control

and device actuation. Tied to the pneumatic system is a supervisory minicomputer monitoring and control system. The minicomputer system was designed to

provide some overall control functions such as solar system mode selection,

programmed start/stop control, optimum start-time, nighttime thermostat setback, and maintenance management. In addition, the computer monitors over 900

binary and analog sensors, allowing the building operators to watch critical

4
equipment and set up alarm signals for changes of state. Part of the function

of the minicomputer is to act as the automated data acquisition system for the

building

.

2 . 3 LIGHTING SYSTEMS

The NCFOB has six different illumination systems, all having approximately the same connected electric power per unit floor area. The fourth floor uses high

pressure sodium lighting with a power density of 18.3 W/m^. On the fifth floor,

the lighting is built into the furniture, and illuminates only task areas. The

fifth floor lighting power density varies with furniture spacing, but was measured as 26.2 W/m^. The remaining floors all use fluorescent lighting with

a variety of luminaire spacings and lense types. All floors with fluorescent

lighting have a lighting power density of 19.8 W/m^.

2. A MISCELLANEOUS EQUIPMENT

Additional energy-consuming equipment at the NCFOB includes electric-resistance

snow-melting coils in the driveway to the underground parking garages, two

nine-story passenger elevators, one ten-story freight elevator, and a packaged

air-conditioning unit for the elevator machine room. A portion of the first

floor is occupied 24 hours per day as a security office for the building.

5
3. DESCRIPTION OF DATA ACQUISITION SYSTEM

The minicomputer-based supervisory control system which performed automated

data acquisition functions at the Norris Cotton Federal Office Building is a Johnson Controls JC-80/55 building automation system*. The JC-80/55 is offered

by Johnson Controls as a proprietary, off-the-shelf system with capabilities

for supervisory control and monitoring of mechanical systems. The proprietary

system was chosen by a bidding process to provide system monitoring and control

capability for GSA and to satisfy existing government and GSA criteria for

building control systems.

The JC-80 system was installed during construction of the building and was nominally operating by November 1976. Johnson Controls was a contractor only

to the General Services Administration (GSA) under the construction contract,

and did not have any agreements with NBS. NBS was under contract only to DoE

and did not have a direct agreement with GSA. This lack of close contact

resulted in an Installed JC-80 system which was not capable of satisfying NBS

requirements to monitor the energy performance of the building. Meetings in

September 1977 between Johnson Controls, GSA, and NBS staff members resulted in

Johnson Controls agreeing to upgrade the existing JC-80 system and install

features which would allow NBS to use the JC-80 to collect hour-by-hour data.

The modifications to the original JC-80 (a JC-80/45) were completed by April

1978 and NBS staff began a process of collecting data and evaluating the data

collection system. NBS staff members spent the following year and a half performing calibrations of the Instrumentation sensors, uncovering problems with

the JC-80 and reporting them to Johnson Controls for correction, and developing

a data reduction plan. The process was complicated by several factors. First,

since the JC-80 was a proprietary system, most of the software was unavailable

for examination by NBS. This meant that software problems had to be discovered

by examining externally available inputs and outputs to the software during

operation of the system and reporting discrepancies to Johnson Controls.

Secondly, the building and the JC-80 were owned and operated by GSA, which was naturally reluctant to allow NBS personnel to work on the control system of an operating building. Finally, the JC-80 system was constructed as a commercial

system and it was usually not possible to make modifications to the system at

the site. Software system changes had to be made at a Johnson Controls facility

in Wisconsin and the modified software system had to be stored on magnetic

tape and shipped to the building. In several cases, required changes were delayed by weeks. By August 1979, repairs and modifications to the JC-80 had

been completed and an evaluation of the system had resulted in a data reduction

plan which took into account the limitations of the system. Data collection

was then accomplished from September 1, 1979 to October 1, 1980 with only

small interruptions.

* Commercial equipment is identified in this publication in order to adequately

describe the data aquisition system used. Such identification does not

imply recommendation or endorsement by the National Bureau of Standards, nor does it imply that the materials or equipment identified are necessarily the

best available for this purpose.

6
Figure 2 illustrates the system configuration for the JC-80 . The philosophy

of this system is to allow local-loop controls to function conventionally with

the JC-80 providing set-point adjustment and overriding Indirect device control.

Each of the sensors and actuators in the system connects to the central system

through a signal conditioning cabinet called a loop remote. Communications

with the loop remotes in the JC-80/55 system are not handled by the central

processor, but by a peripheral processor called the loop controller, using a concept of limited distributed processing. The loop remote cabinets do not

have "stand-alone" capability and do not operate if the central system is not

operational.

3.1 LOOP REMOTES

The loop remote field cabinets contain the circuitry for analog-to-digital

conversion and other signal conditioning. Each loop remote may contain up to

50 "point module" circuit cards, each of which may be connected to from four

to eight sensors depending on the sensor type. There are a total of 19 loop

remotes in the NCFOB. The loop remotes are interrogated sequentially by the

loop controller processor, and updated sensor values are transmitted to the

central system.

3.2 JC-80 CENTRAL SYSTEM

The JC-80 central processor is a Modcomp minicomputer processor using Johnson

Controls software to accomplish monitoring and control functions. The system

is designed to scan the system data points approximately every 20 seconds.

Sensor point values which have changed by an amount called the filter increment are updated and are stored in the central system half-megaword (16 bit

word) magnetic disc storage. The central system software converts digital

values received from the loop controller to a number in engineering units using

equations appropriate to the sensor type.

A cathode ray tube terminal (CRT), lineprlnter, and teleprinter (TTY) provide

operator interface to the JC-80. From the CRT, an operator can display sensor

values, direct information to be printed on the lineprlnter or TTY, start or stop devices, and direct execution of system programs using the JC-80 command

mnemonic language.

A number of JC-80 software routines are used to allow the JC-80 to function as

a data acquisition system. "Calculated point" software is used to make calculations using the sensor point values as inputs to an algorithm. An averaging

algorithm is used to calculate hourly average values for sensors using instantaneous values as input. The averaging routine is executed a number of times

during an hour and is set up so that the average value stored in the JC-80 is

the average for the hour up to that point in time. The average is reset to zero at the start of each hour. The number of instantaneous values included

in the average is determined by a parameter which may be termed the "calculated

point interval." For each hourly average data point there is a calculated

point Interval in minutes representing the time period between applications of

the averaging equation. As the specified value of the calculated point interval

is decreased, the value of the calculated average approaches the true average

value.

7
^ 1

.

\

In order to transmit hourly averaged values of sensor readings to NBS, a magnetic tape drive was included in the central system peripheral equipment.

A JC-80 software routine called the "data logger" took values for 720 instrumentation sensors and placed the data in storage locations on the system disc

at the beginning of each hour. Each night at midnight, the data logger routine

wrote 24 hours of data on magnetic tape.

Of the 720 instrumentation sensors whose values were written on the magnetic

tape, 107 were binary sensors which indicated on-off or mode status for various

pieces of equipment in the NCFOB. The binary values on the tape represented

the state of the sensors at the beginning of the hour. Five hundred fifteen

of the data logger points were hourly average values from analog sensors. Nine

types of analog sensors were used. Table 1 lists the analog sensor types and

the number of each type. The 98 remaining data logger points represented

readings from kilowatt-hour meters in the building. The kilowatt-hour meters

produce a contact closure on a data line each time a certain quantity of electrical

energy passes through the meter. Software pulse counting routines accumulated

total contact closures for one hour and these values were stored on the magnetic

tape by the data logger software.

8
4. DATA REDUCTION PROCESS

The process of reducing the Information gathered on the automated data

acquisition system at the NCFOB consisted of extracting data from the magnetic

tapes generated at the NCFOB and using them to calculate a number of parameters

describing the building on hourly, daily, and monthly levels.

4.1 READING, CHECKING, AND COMPRESSION OF DATA

The magnetic tapes used to store and transport data from the NCFOB JC-80 were

732 m (2400 ft), nine-track tapes written at a density of 32 characters/mm

(800 cpi). The information was stored on the tape in ASCII code with a lineprinter image format using 134 characters per tape record and one record per

tape block. Each 52 records of the data comprised one line-printer image

"page" with the format shown in figure 3. A page contained the hourly values

for 18 data points from a 24 hour period and for each day of data, 40 lineprinter image pages were generated. The magnetic tapes were sent to NBS by

mail when one week of data had been collected. One week was felt to be the

maximum time that should elapse between collecting and examining data so that

problems with the data could be detected early.

Data reduction at NBS was performed using a UNIVAC 1108 computer. A number

of computer programs were used to process the data before calculations were actually made. After reading the information from the magnetic tape, the

ASCII code on the tape was translated to "fieldata," the Internal alphanumeric

character code of the UNIVAC computer. The data, after translation, had to be

"transposed" so that the calculation program could read all data points for

each hour in sequence. The tapes were originally written in a form such that

18 point values for all hours of one day were written and followed by values

for a different 18 points for all hours of the same day. It was necessary to

strip off a large quantity of extraneous header information leaving only an

index number, point value, and engineering unit code for each data point.

The data transposition routine checked through the data for missing data, offline points, "glitches," and out-of-range numbers. Values for the kilowatthour meters were converted from counts of meter contact closures to kilowatthours by taking the difference between counts for successive hours and applying

a conversion factor. The original magnetic tape files were archived on magnetic

tape at a higher density (246 characters/mm) (6250 bpi) with two weeks to a tape.

The transposed, condensed and checked data files were also stored on archival

tapes in a compressed form. Where 26 magnetic tapes were required to store the

original data logger output, only one tape was required to store the condensed

data.

4.2 CORRECTION OF DATA LOSS

In a long term-data collection effort, it is difficult to avoid the loss of some data. The collection of data by the JC-80 was no exception to this rule,

but the losses involved did not prevent the evaluation of the data. Three

types of data loss were experienced with the JC-80 system. The first type

occurred when the sensors and the data acquisition system operated properly

but problems with the actual magnetic tape drives at the site caused a garbling

9
or loss of data. In most cases this type of error was detected by the computer

programs used to read, check, and transpose the data at NBS, and corrections

could be made by the use of a text editor. A second type of data loss usually

involved malfunctions in the field hardware of the JC-80 system, causing a partial outage of the complete set of data points for a time period ranging

from one hour to several days. If the loss was short term or a lost point was

not critical in the calculation of performance parameters, this type of outage

could be dealt with by interpolation or assumption of data values. In some cases, partial loss of data required that the entire data set for a number of

hours be rejected. The most serious loss of data occurred when the total JC-80

system at the site was inoperative due to one of a number of causes. The failure of the JC-80 resulted in a complete data outage of all points for a period

lasting from one hour to several days. The most frequent causes of complete

failure of the JC-80 system were inability of the system to restart properly

after a very short power failure or voltage "dip," and problems with software

which caused the system to "hang" and require a manual reset, with resulting

loss of stored data logger information.

Since the calculation of dally and monthly parameters was a goal of the data

collection, a technique for deriving monthly values from incomplete data had to

be used. Two techniques were possible. One method is the averaging of all

available data over the period of successful data collection, using the assumption that missing data is similar to the data collected. This technique is not

acceptable, however, if it is desired to have data which appears to be continuous, such as needed in verification of building simulation computer programs.

Therefore, all complete data outages requiring complete rejection of data were handled by a data replacement technique. By the use of this technique, missing

or incomplete blocks of data were removed from the continuous hourly data and

replaced by blocks of data taken from another day during which no outage

occurred. The replacement blocks were carefully chosen to represent conditions

as close to the original as possible, and only the dates on the replacement

blocks were changed. The criteria used to evaluate replacement blocks were whether or not the rejected data blocks were from a weekend or holiday and the

weather during the blocks. Weather conditions were determined from tabulated

weather measurements reported monthly by the National Climatic Center for

nearby Concord, New Hampshire. The measurements used included sky cover,

temperature, windspeed, percent sunshine, and precipitation readings taken

every three hours. Table 2 is a summary of the completeness of the data taken

by the JC-80 system during the year of data acquisition. The table shows that

there is a general improvement in the completeness of the data during the first

part of the collection period but a leveling off in completeness during the

latter part. The number of hours requiring replacement remained around 15 to

25 percent of total hours with occasional dips to approximately 5 percent. The

longest uninterrupted period of data collection was 17.75 days in one month and

after a few months into the collection period, the longest outage in each month

ranged from one to five days.

After the replacement of missing or rejected data, the complete 13 months of

data were divided into data files each containing one half month of data and

the files were archived on a magnetic tape. These files were used as input to

the parameter calculation routine.

10
4.3 Calculation of Parameters

A complex computer program (written in FORTRAN V) was used to calculate

parameters from the magnetic tape data. Although 720 values of sensor readings

were taken for each hour, not all of the values were used for calculations.

After studying the installed sensors and evaluating their performance on the

basis of sensor location, adherence to installation specifications, type of

measurement, sensor type, and results of sensor calibrations, a number of sensors were judged to be unusable. Readings from the rejected sensors were generally not reproducible or consistent with other sensor readings, and the

effort to salvage the rejected sensors was considered to be excessive. The sensor types that were most often considered unacceptable were fluid flow

measurements in small diameter piping, air flow measurements, duct dewpoint

temperature measurements, illumination sensors, and natural gas measurements

using a sampling technique rather than a totalizing technique (as used in the

main gas meter). Rather than being unable to calculate parameters dependent

on data from sensors judged unacceptable, assumptions were made in the calculations to allow many of the originally planned parameters to be determined.

Approximately 160 parameters were calculated by the reduction program from the

data collected in each hour. After the calculations for one hour were completed, the output values were stored and added to data for previous hours to

produce totals and averages of the output values on a daily and monthly basis.

Data Conversions and Calibrations : The data taken from the JC-80 magnetic

tapes were initially in English units. SI units were selected as the internal

units and output units for the reduction program. Kilowatt-hours were chosen

as the basic unit of energy (since the data were in one-hour blocks).

All of the critical sensors used in the calculations were given a calibration

check before the sensor values were used. Special instrumentation was transported to the site and used to compare the measured values displayed by the

JC-80 with a standard measurement. Nutating disc flow-meters checked against

a weighing meter were used as a standard for liquid flow measurement, and

liquid-in-glass thermometers were used as a temperature standard. Additional

temperature calibrations were made between inlet and outlet temperature sensors

for the same piece of equipment to calibrate temperature differential measurements. The standard flow-meters were placed so as to be in series with the

JC-80 flow-meters for the calibration run. Correction factors derived from the

calibrations were second order, involving two constants for each sensor. The

correction factors were applied to the input data by the reduction program

before calculations were made.

Mechanical Systems Status ; It was important to make a determination of the

status of the mechanical equipment during each hour that data was collected.

If a piece of equipment was not operating, then the flow and temperature values

associated with the equipment could have been meaningless. The reduction program set status variables for each hour by checking kilowatt-hour readings,

flowrates, and binary Information from equipment on/off controllers. Due to

limitations in the data acquisition software, it was possible to only record

binary information once per hour. Since the equipment monitored usually

changed changed state only 2 to 3 times per day, it was assumed that a piece of

11
equipment was on during the entire hour if either the previous or present value

of the binary point indicated an on status. Status was checked for major air

and water transport loops, major pieces of equipment, special modes of operation, heating or cooling status for fan coils and heat pumps, floor occupation,

and day or night status. In addition, certain status variables were set based

on manual observations not included in the JC-80 instrumentation, such as the

presence of water or ethylene glycol/water solution in the solar collectors or

the existence of winter or summer operation of the building.

Natural Gas Use ; Natural gas consumption at the building boundary was reported

on the JC-80 data tapes as counts from a pulse generator on the main gas meter.

The count value was converted to m^ by using a gas meter factor and then to

equivalent thermal energy using a constant conversion factor of 10.356 kWh/m^.

The natural gas used was consumed by one of three types of equipment: the ser- vice water heater, the engine-generator, or the boilers. The water heater and

engine generator gas usages, which were relatively small, were measured by gasflow transducers located at the equipment. The gas consumed at the boilers was calculated by subtracting the engine-generator and service water heater gas use

from the main gas meter reading.

Boiler Performance : The original water flow and temperature sensors located in

the boiler piping were determined to be unusable due to a large number of

elbows, tees, pumps, and valves packed into the piping around the boilers.

Therefore the output of the gas boilers were approximated by calculation. Four

gas boilers in a modular configuration exist at the building, as shown in figure 1. The boilers are piped in parallel, each boiler having its own boiler

water pump which does not run unless the boiler is producing useful energy.

The electrical consumption of each pump was measured separately, and thus if a boiler pump had been used in any hour its electrical consumption was greater

than zero. The number of gas boilers operating in any hour was the same as the

number of boiler pumps operating. If the boilers operating during a given hour

were operating for the full hour at full-load and steady-state conditions, they

would consume a rated input amount of gas and have a constant steady-state

efficiency. In the actual building the boilers operate at varying conditions

from full load to zero load, since the boilers may cycle on and off during an

hour. In addition, the four boilers may be operating at different load points

(due to the modular concept). The boiler efficiency at part-load conditions

is a function of the load point and this function is similar for most conventional boiler designs. Measurements were taken at NBS on a modular boiler system [6], and were used as the basis for a prediction of boiler efficiency as a function of load point at the NCFOB. A one-time measurement of the boiler

steady-state efficiency was made for each of the boilers at the NCFOB using

stack gas temperature and CO2 measurements and the average boiler efficiency

was determined to be 80 percent. The rated full-load gas input for each boiler

at the NCFOB was determined to be 61.3 kW. The percentage of full-load input was obtained by dividing the measured natural gas consumption at the boilers

by the product of the number of boilers operating and the rated full-load input

for one boiler. The part-load boiler efficiency for the modular boiler system

was determined using:

eff = (1 - 0.583 %fH))

( 1 )

12
where eff is part-load efficiency, %fli is percent of full load input, and

effgg is steady-state full-load efficiency. This equation was fitted from

experimental measurements described in reference [6]

.

The calculated boiler

system output was then the product of the part-load boiler efficiency and the

measured natural gas input to the boilers. This output calculation neglected

jacket losses from the boiler. However, since boilers were piped in parallel

with Individual pumps and the pumps did not operate when the boiler was inactive,

jacket losses were assumed to be low due to the small size of the boilers.

Heat Pump System Heating and Cooling Requirements ; The heating and cooling

requirements, or respectively, the energy delivered by or absorbed by the heat

pump terminal units, was calculated by the data reduction program. There are

56 heat pump units located on the first three floors of the NCFOB and the

original concept for the data system was to Individually instrument the heat

pump units with temperature, flow, and electric energy sensors. After installation of the JC-80 system, it was determined that many of the sensors for the

heat pump system, particularly the flow-meters in the relatively small diameter

water piping leading to the heat pumps, did not give consistent or accurate

readings. Therefore, in the reduction algorithms, an approximation technique

was used to calculate the capacity of the heat pump system in a given hour from

the electrical energy input and a knowledge of the statuses of the individual

heat pump units in the heat pump system. Manufacturers' data, available for

each type of heat pump unit, specified the fan power consumption, steady-state

heating and cooling load compressor input, and steady-state heating and cooling

output capacity for a given source water temperature. Heat pump units in a typical Installation will not operate at steady-state conditions at all times

since the units may cycle on and off to meet a load smaller than the rated

full load. Tests were performed at NBS on a unitary water-source heat pump at

steady-state and part-load conditions [7]. The data from this heat pump was taken under part-load conditions at several cycling rates and water source

temperatures. Using the test data, the percentage of full-load output capacity

was found to be a linear function of the percentage of full-load compressor

input. This result was used to predict heat pump capacity at the NCFOB.

For the calculation of heating and cooling requirements, the heat pump system

was divided into six zones—a perimeter and core zone for each of the three

floors. Each of the zones contained from two to thirty-two heat pumps and in

general, the heat pumps were all of different steady-state full-load capacities.

Usable sensor measurements included the on/off and cooling/heating mode status

of each of the heat pumps and a single value of hourly electric energy consumption for all of the heat pumps in a zone. The electric energy measurement was

the sum of energy to heat pump compressors and unit fans. To determine the

estimated output capacity for each hour in each zone, the following procedure

was used:

1. The status of each heat pump was checked to determine if the unit

was on or off. The rated fan energy consumption for all units that were

on was summed to give a total rated fan energy consumption. Subtracting

this number from the total electric energy consumption gave the total

zone compressor energy consumption.

13
2. A full-load steady-state compressor input and capacity output for

the zone were calculated by summing the rated compressor inputs and

capacity outputs for each of the individual heat pumps that were in

either a heating or cooling mode. It is possible for some units to have

fans running but no compressor operation during an hour. Cooling

capacity was given a negative value.

3. The part-load factor for each zone was calculated by dividing the

actual zone compressor input by the rated full-load steady-state

compressor input.

4. Finally, the output capacity for the zone was taken as the product

of the part-load factor and the rated full-load steady state capacity.

During the heating season, the thermal energy needed from the heat pump water

loop by the heat pump units in a zone was calculated by subtracting the electric

energy input from the heating capacity for each hour. The total energy to be

supplied by the central plant to the water loop was taken as the sum of the

energy needed by the zones. Two other quantities computed for the heat pump

system were the electric energy to heat pumps in the cooling mode and electric

energy to heat pumps in the heating mode.

Simultaneous heating and cooling within a zone may have taken place occasionally

during brief periods in spring and fall. With one exception, this was not

taken into account in the heat pump calculation procedure, so that if simultaneous heating and cooling did take place the calculated requirements would

be slightly smaller than the actual since heating and cooling requirements

canceled each other in the calculations. The exception concerned the NCFOB

computer room which required some cooling all year. A special calculation

included this cooling load even if other heat pumps in the zone were heating.

Hot Water Heating System Heating Requirements ; As in the case of the boiler

and hot water systems, an approximation technique had to be used to calculate

the hot water heating system requirements for the upper four floors. Sensors were installed on each floor to monitor supply flow rate and temperature and

return temperature for the hot water system lines leading to radiation coils

and unit heaters. The flow measurements in the relatively small diameter

piping were considered to be unacceptable.

The total output of the natural gas boilers was used to supply energy in the

winter to both the heat pump system and the hot water heating systems. The

amount of energy delivered to the heat pump system by the boilers was assumed

to be equal to the heat pump water loop thermal energy requirements calculated

for the heat pumps. It was then assumed that the remaining boiler output was used to supply the hot water heating system. This assumption does not take

into account the loss of energy through the insulation on the water piping. It was not possible, given the shortcomings of the instrumentation, to calculate

individual floor or zone heating requirements for the upper four floors.

14
Chilled Water System Cooling Requirements : Original chilled water system

sensors placed on the Inlets and outlets to the terminal equipment were found

to be unusable and cooling requirements for the upper four floors served by

the central plant-based chilled water system were approximated by the output

of the two central chillers at the NCFOB. The installed instrumentation on the

electric chiller in the central plant consists of a kilowatt-hour meter measuring electric energy consumption by the chiller, inlet and outlet temperature

sensors on the evaporator and condenser, and flow-meters on the evaporator and

condenser. The absorption chiller instrumentation was the same, except that

the electric energy measurement was replaced by inlet and outlet temperature

and flow measurements for the chiller generator. These sensors were judged to

be usable for calculating chiller output.

The energy extracted from or added to a water loop by an individual piece of

equipment is given by the following general equation:

‘Iw ~

*^w * ^p * TMw * (^in “ ^out^

o where 6^ is the density of water in kg/m at the location where the flow rate

is measured, m^ is the flow rate in m^/s, Cp is the specific heat of water in

j/(kg • °C) and tj^^ and tQ^j. are the inlet and outlet temperatures, respectively. Water density was determined by an empirical equation as a function of

temperature and specific heat was taken as one of three values depending on the

range of temperatures within which the water temperature fell. The effect of

chemical additives to the water systems was neglected. The energy extracted

from the chilled water loop by each chiller was determined by using equation

(2) and values from the chiller sensors. The sum of the two chiller outputs

was assumed to be equal to the load on the chilled water system by the chilled

water coil in the VAV air handling unit and the fan coil units in cooling mode.

It was not possible to calculate floor by floor or zone cooling loads for the

upper four floors.

Service Hot Water : The service hot water system is based on a small storage

tank with three sets of supply and return piping connected to it. One set of

pipes brings hot water from a gas-fired hot water heater preheat tank. A

second set delivers energy from the basement hot water storage tanks. The

remaining pipes lead to the service hot water supply loop which circulates

through the building. Make-up water is introduced in the return line when a draw is made on the system. The service hot water load is determined using

the supply temperature, return temperature, and system flow in equation (2).

Building Environment : Values of service hot water supply temperature, average

wind speed, and storage tank temperatures were taken directly from input

information. Algorithms were used to calculate average daytime and nighttime

outside dry-bulb temperatures and daytime humidity. Occupied building and

unoccupied building space temperatures and occupied humidity were determined

for each floor by averaging north, south, east, and west perimeter and core

zone temperatures.

15
Electrical Energy Use ; Figure 4 is a schematic of the electric power

distribution system at the NCFOB. Ninety-eight kilowatt-hour meters, shown as circles in figure 4, measure the electric energy delivered by the building

switchboard circuits and remote electrical panels to the building loads. The

main power bus enters the building in the basement and connects to a basement

switchboard. The main bus duct riser transfers power to another switchboard in

the penthouse. Branch circuits off the main riser supply receptacles and lighting circuits on the building floors. The penthouse switchboard consists of a normal section and an emergency section. The emergency section supplies loads

that are considered essential, such as elevators, lights in stairways, and the

pneumatic control system air compressor. If utility power fails, these circuits can be supplied by the engine-generator set. The nonnal section of the

switchboard supplies loads such as the chiller and motor control center from

which major electric motors are supplied power. All major pieces of equipment

in the penthouse had their electric energy consumption monitored.

Two types of electric lighting loads were monitored at the NCFOB. These are normal and essential lighting loads. The determination of lighting energy for

each floor was accomplished by summing values from kilowatt-hour meters measuring lighting loads. This was possible since lighting circuits were almost never mixed with non-lighting circuits in metered electrical panels.

Summation algorithms were used to determine the electrical energy used by the

HVAC systems and by miscellaneous loads in the NCFOB, using readings from

appropriate meters. Miscellaneous loads were defined as loads on receptacles

plus loads by miscellaneous pieces of non-lighting and non-HVAC equipment such

as sump pumps and snow melters. Receptacle and office equipment loads were determined for each floor with the total miscellaneous load defined as floorby-floor loads plus the other miscellaneous building loads.

Total Energy Use ; Total electrical energy use was obtained from the

kilowatt-hour value of the building main meter. Total natural gas use was

taken from the value calculated from the building main gas meter readings.

For each hour, the sum of the two totals for electric energy and natural gas

represented the total building energy use for the hour, excluding fuel oil use. Due to a lack of adequate computer-connected instrumentation, manual readings

were taken for the fuel oil boilers. During the year of monitoring the building, the oil boilers were seldom used (12 h, total). Total HVAC energy, again

excluding fuel oil, was the sum of natural gas use and HVAC electric power.

For comparison to the HVAC energy, the total HVAC requirements were summed from

calculated cooling, heating, and service hot water requirements.

Solar Collectors : If the NCFOB solar system was operating during an hour being

examined, the data reduction program determined the thermal output of the solar

collectors on the building roof. Also calculated were collector system temperature levels and solar irradiation in the collector plane. Inlet and outlet

temperature sensors and flow meters installed in the collector array supply and

return piping were used to provide values for the calculations on the solar

system. A heat exchanger is located between the solar array piping and the

building piping to isolate the antifreeze solution used in the winter. Calculations were made to determine both collector output from the array and output

16
from the array and heat exchanger together. Equation (2) was used as the basis

for calculating thermal output.

During the monitoring period, the solar system was used only to supply energy

to the service hot water system. The contribution of solar to the service hot

water load was calculated using values from sensors in the service hot water

system in equation (2).

Parameter Averaging, Totalization, and Storage ; The 160 output values generated

by the previously described algorithms were average values for one hour only.

To produce total energy values for a month-long period required that approximately 720 hourly values for a month be summed. When a monthly average of

hourly data was desired for a particular parameter, the total was divided by

the number of hours in a month. Average and total values for day-long periods were generated in a similar manner. Four types of averages were used beside

the standard average. A daytime average value was obtained by only adding

hourly output values to the totalization when the hour of data was for a daytime

hour. The final total was divided by the number of daylight hours in the

totalization time period. Similar averages were calculated for certain points,

using nighttime hours, occupied hours, and unoccupied hours as bases.

The output values from the data reduction were stored in three computer magnetic

disc storage files at NBS in a special unformatted form. A variable record

size input/output (I/O) routine was used which is faster than Fortran l/O and

has special record search capabilities.

Hourly output parameters were stored in one of two larger computer files each

containing approximately six to seven months of data. The 160 output parameters for each hour were written into a single 202-word record (a word contains

36 binary bits on the UNIVAC), with the first word serving as an identifier

containing the hour and day for the data. Before a month-long block of data, a one-word identifier record containing the month and year was written, allowing

a block of data for a particular month to be located. Daily averaged and

totaled values were stored in the same two files in a 6201-word record containing data for the entire month, with a one word identifier giving the month and

year.

Totalized and average values on a monthly basis were stored in a smaller

computer file in 202-word records. An identifier word contained the month and

year for location purposes.

Data Retrieval and Analysis : Two types of special programs were used to

retrieve data from storage. One type of program was designed to print out

tables of selected parameters as a functon of the hour, day, or month. The

other program type was used to generate data for use in plotting routines.

These two types of programs allowed analysis to be performed on the data

collected by the JC-80 system at the NCFOB.

The main table-producing program reads a list of instructions in order to access the correct data. The instruction list contains the time basis desired

and the beginning time or date for the data. Also in the instruction list is

17
a number describing the general type of data desired. Figure 5 shows a sample

instruction list with a description of the six data types available.

The Appendix contains sample printouts from this program on a monthly basis.

The plotting data generation routines have the same basic structure as the

table program but the data instruction list contains the number of time periods

desired as well as the time basis, and also has space for up to 10 index numbers

identifying calculated parameters. The output of the plotting data routines

is a data file or array containing columns of numbers, the first column

containing the time and the other columns containing the desired data parameters. Data retrieved using the plotting data program described were used by

software plotting packages to examine trends and relationships between data

parameters on hourly, daily, or monthly bases.

18
5. RESULTS — MONTHLY PERFORMANCE PARAMETERS

During the process of reducing the 13 months of data collected on the

acquisition system, monthly parameters were compiled from the data. A full

listing of the monthly values calculated may be found in the Appendix, along with

a definition of each quantity calculated. The number of parameters is too large

to discuss here in detail. Study of the assumptions outlined in chapter 4 will

determine the usefulness of the data for specific purposes.

It should be noted that the performance data compiled is not useful for

comparison of HVAC systems on one floor with those on another floor for three

reasons: First, instrumentation problems did not allow the collection of

detailed data for each floor; collected data did not fully describe the performance of individual pieces of equipment because equipment output was not adequately measured in many cases; finally, the HVAC and lighting system design

was too complex to allow simple comparisons of energy consumption between

floors

.

5.1 VALIDATION OF MONTHLY VALUES

A check of some of the results from the data acquisition system is possible

using the monthly results because manual readings of a number of kWh and gas

meters were taken concurrently with the data collection by the acquisition

system. The manual readings were taken weekly and were compiled into a set of

parameters comparable to some of the parameters produced by the reduction

program. Figure 6 shows a comparison of measurements of total energy consumed

at the building boundary, as determined both from the JC-80 readings and the

manual readings. Any disagreement between the two data sources is an indication of instrument error (in gas and electrical measurements) and the validity

of the replacement technique used to deal with missing data. Figure 6 shows

that the agreement for total energy is good, with a some exceptions which will

be explained as more detailed information is examined.

Figure 7 shows the natural gas consumption for the NCFOB and validates the main

gas meter measurements by the data system. The main gas meter used was actually

the utility meter.

Detailed Monthly Electric Energy Use ; Because of a large number of manually

readable kWh meters (98), the best detailed comparison between the data system

measurements and the manual readings is available for electric energy values.

Figure 8 shows the total electrical energy use and a comparison for the manual

and automated readings.

Figures 9 through 16 display comparisons between manual and automated readings

for several categories of electric energy use. Figures 9 and 10 show floorby-floor lighting energy. The most outstanding feature of this data is the

relatively high constancy of loads. The curves for the 1st floor lighting

illustrate the effect when a data system sensor fails and indicates zero energy

use. This causes a discrepancy between manual and automated readings and

several failures of this type can cause the small discrepancies in total usage

in figure 6. Figure 11 is a plot of electrical energy use for lighting on

19
essential circuits. These circuits are supported by the emergency generator

during power failures.

Figures 12 and 13 display floor-by-floor usage of energy for miscellaneous

office loads which, like the lighting loads, remain relatively constant. In

figure 13 there is a large discrepancy for the 4th floor. This is due to one

of the sensors on the 4th floor being inoperative for the entire period of data

collection and assumed values being used for this sensor.

Figure 14 shows electrical data for fan colls and for the solar pumps. Fan

coil loads are constant, with the exception of the 5th floor, where there is a large heating-only fan coil whose use was discontinued in warmer weather. The

solar pump data represent a variable load which depends on the amount of solar

irradiation. The agreement between manual and data system is not as good as for the constant loads, but improves considerably at the end of the year when

more hours of original data were available.

Heat pump electric energy consumption is shown in figure 15 and is a seasonally

varying load. First floor heat pump energy consumption is larger than for the

upper floors because of a 24-hour occupied area (guard office and computer

room), larger floor area, and the presence of main entrance doors on this

floor. There are some discrepancies for the upper two floors between manual

and JC-80 values.

Other important mechanical system electrical loads are shown in figure 16.

Energy to fans is constant until the warmer months when fan usage is increased

to implement nighttime flushing of the building and thus reduce cooling

requirements. The chiller and evaporative coolers represent equipment used

only in summer. The controls and miscellaneous category Includes electrical

energy for pumps, and shows an increase in summer.

5.2 ANNUAL TOTAL ENERGY CONSUMPTION

In order to make comparisions between buildings, it is useful to express building

gross energy consumption on a per unit area basis. It is Important that all

buildings involved have their areas calculated in a consistent manner and that

all references to a single building use the same area. The GSA Public Buildings

Service (PBS) has developed a method of calculating building area which it uses

in comparing its own buildings and as a basis for energy consumption goals [8].

This method identifies three types of building area: office space, mechanical

equipment space, and garage areas. Since garage and mechanical areas use energy for lighting, elevator service and ventilation, GSA/PBS felt that it was important to include such areas in the total but not on the same level as fully conditioned office areas. The GSA/PBS equivalent gross floor area is

then defined as one quarter of the mechanical and garage areas plus the total

office area.

In order to be consistent with the GSA/PBS areas, NBS used an area for the NCFOB

of 10 900 m^. This includes 9072 m^ of office space, 643 m^ of mechanical space,

and 6672 m^ of garage. In the design stage, GSA established an energy consumption goal of 627 MJ/m2»yr for the NCFOB and for other energy conserving buildings

20
to follow. This figure used the equivalent gross floor area described.

The annual energy consumption of the NCFOB has been falling since the first

month of building operation. Annual consumption for the fourth operating year

(September 1979 to August 1980) was 527 MJ/m^ • yr, 15 percent below the GSA

goal. Part of the success in being below the goal is due to the lower thermostat settings required by the Emergency Building Temperature Restrictions

(EBTR) regulations.*

An annual energy use figure which was calculated for the Norris Cotton Building

is the expression of energy use per unit area and per number of occupied hours.

The value of this figure is that it prevents buildings which are not operated

all day from having apparently low energy usage per unit area. For the NCFOB,

occupied hours are tabulated in the Appendix as an output of the data reduction

for each month. These occupied-hours figures include all hours when the building was occupied for HVAC purposes (including hours when no people are present

such as during nighttime flushing operations in the summer). Taking the maximum

number of hours for any floor during the month as the occupied hours for the

building, the NCFOB was occupied a total of 3667 hours during the 4th operating

year. This is a use factor of approximately 42 percent. Dividing the total

energy use by the area and the occupied hours yields a figure of 156 kj/

(m^ • occupied hour).

* Federal Register, July 16, 1979 (44 FR 41205).
6. RESULTS — DAILY PROFILES OF NON-HVAC ENERGY

Building energy use can be divided into two broad categories—HVAC and

lighting-miscellaneous. HVAC energy is used to provide all heating, cooling,

ventilation, and service hot water, and varies as a function of the time of

year. Lighting-miscellaneous energy is used to provide energy to all other

functions of the building, such as lighting, elevators and electric receptacles

for operating typewriters, copiers and other office equipment.

Monthly totals of energy for lighting and miscellaneous have already been

presented in chapter 5. In figures 17 and 18, hourly energy use profiles are presented for the total building lighting and miscellaneous energy, respectively, over a three day period. In both figures, the first day presented is

a weekend day and the other two days are weekdays. Figure 17 shows total

energy for lighting used in each hour of the day in kWh/h or average hourly

kW. Data from two three-day periods is presented, one set from near the winter

solstice and the other from near the summer solstice. Also presented is the

percentage of the building occupied to show the normal working hours of the

building. Figure 17 illustrates that there is little difference from summer

to winter in this building since little daylighting is used and lighting is

always on when the building is occupied.

Figure 18 shows the hourly energy used for miscellaneous office electric loads

such as typewriters, copiers, and similar equipment. This figure also indicates the occupied hours of the building. As in figure 17, data from summer

and winter months are given and there is very little difference between the curves for the two sets of data. Three distinct times of day may be observed

in figure 18. There is a slight dip around noon corresponding to lunchtime

and morning and afternoon working sessions to either side of lunch. The usage

of office equipment appears to be higher in the morning than the afternoon.

22
7. RESULTS -- BUILDING ENVELOPE PERFORMANCE

The most important features of the envelope of the Norris Cotton Federal Office

Building are the use of massive masonry wall construction, application of

external wall insulation, and incorporation of very small windows in the

building shell design. An important application of the hourly data collected

by the data acquisition system is to determine the effectiveness of these

techniques as used in the NCFOB. If building data such as interior temperatures are studied, it becomes obvious that in this building, steady-state models

cannot be used to evaluate the performance of the envelope because steady-state

conditions are rarely reached. The equipment in the NCFOB is slightly undersized by conventional criteria, and there were many cases where space temperatures floated below or above thermostat settings and did not remain constant

over the period when the building was occupied. The use of night setbacks also

introduced variation in the space temperature.

Many computer-based building models are available to predict the space

temperatures and energy use of a building given assumptions of building parameters such as window shading factors and transmission loss coefficients.

However, such models are not suited to determining building parameters from

actual data.

7.1 CONCEPT OF EQUIVALENT THERMAL PARAMETERS

Extremely detailed transient heat transfer analysis might serve to determine

building characteristics but the computations involved would be overwhelming.

Kusuda [9] and Sonderreger [10] have used a technique of simplified transient

analysis using equivalent thermal parameters (ETP) to describe the behavior of

buildings. The concept of ETP's makes the assumption that a building can be

modeled as a simple system consisting of a single uniform indoor air temperature, an outdoor air temperature, a building mass with a uniform temperature

and constant heat capacitance, and thermal resistances connecting the mass,

indoor air, and outside air. Figure 19 shows the equivalent electrical analog

circuit for this simple model. A differential equation involving time can be

developed to describe this system. Sonderegger has used a technique of solving

the differential equation describing the simple model using actual measured

data from a residential structure and determining values for the thermal resistances and capacitance shown in figure 19. A similar technique was used by

Kimura for a commercial building [11].

The solution of the ETP model can be accomplished using discrete data and a finite difference equation derived from the differential equation. Ideally the

technique requires instantaneous temperature and heat rate data taken at

regular Intervals. The data collected for the NCFOB by the JC-80 included only

average hourly space temperatures and outdoor temperatures and energy totals

for each hour. However, it was felt that the data could be used to model the

NCFOB using the ETP concept.

One of the basic equations describing the model in figure 19 is:

Q

= Hs(T - Ts) + H(T - To) (3)

23
where T is the inside temperature, Ts is the temperature of the building mass,

To is the outside air temperature, Hs is the heat transfer coefficient between

the building air and the mass, H is the heat transfer coefficient between the

building air and the outside, and Q is the net energy added to or removed from

the space including internal gains, mechanical cooling, and space heating. This

equation is an energy balance for the building. The second equation describing

the model describes the transient behavior of the system:

C = Hs (T - Ts) (4)

dt

where C is the equivalent thermal capacity of the system, not necessarily equal

to the total thermal capacity. Since Ts is difficult to measure, it may be

eliminated from the analysis by combining the two above equations into a single

differential equation:

C(1 + H/Hs)T = C(Q/Hs + HTo/Hs) - HT + HTo + Q (5)

where the dot above a variable denotes differentiation with respect to time.

A similar development was used by Sonderreger [10]. If an effective thermal

mass, C*, is defined as:

C* = C(1 + H/Hs) (6)

then the final differential equation is:

T = (HTo + Q)/(H + Hs) + H(To - T)/C* + Q/C* (7)

To convert equation (7) to a finite difference equation, the characteristics of

the experimental data must be taken into account. The time increment for the

discrete measured data from the JC-80 was one hour and thus the differentials

are approximated by the change in the value of temperature or heat rate between

hourly measurements. For temperature readings, the value of the temperature

at each hour is actually an average of the temperature over the previous hour.

For linear changes in temperature the average is equal to the temperature at

the midpoint of the hour. For non-linear temperature change the average is an approximation of the mid-hour temperature. For heat flow, the available

measurement is an integrated energy entering or leaving the building and this

approximates an average heat rate at the midpoint of the hour. The differentials in equation (7) are approximated by first interpolating the on-the-hour

measurements to calculate values half-way between the measured values and then

subtracting the interpolated values to obtain a linearized value for the slope

of the temperature or heat rate curves. In equation form this is:

T = (Tt+1/2 - Tt-l/2>/At = (ATj.)/At (8)

where At is the time step and t ± 1/2 represent times halfway between

measurement times.

24
By substituting expressions of the form of equation (8) for all differentials

in equation (7) and manipulating the equation to isolate '^t+1/2* equation

(7) may be converted to a difference equation of the following form:

Tt+1/2 = aTt-i/2 + b^Tot + b2ATOt + c^Q^ + C2AQt (9)

a = (1/At-H/2C*)/(1/At+H/2C*), (10)

b^ = (H/C*)/(1/At+H/2C*), (11)

b2 = (H/At(H+Hs))/(l/At+H/2C*), (12)

Cl = (1/C*)/(1/At+H/2C*), (13)

C 2 = (l/At(H+Hs))/(l/At + H/2C*). (14)

AQ and ATq represent the change in Q and Tq between t-1/2 and t+1/2, and At is

the time step.

The Q and AQ terms in equation (9) represent the sum of several heat sources

and sinks. The Q terms may be broken down into heat generated within or mechanically removed from the building and heat generated by solar irradiation

passing through the building windows. Although the windows in the NCFOB are small, solar irradiation was included in the analysis to see if the effects

of solar had any significance. Equation (9) may be expanded to include solar

by substituting:

Q = Q + AS (15)

where Q becomes all non-solar heat sources and sinks, A is an effective solar

window area and S is the solar irradiation in energy per unit time and per

unit area, in the Q and AQ terms. This results in an equation of the form:

'^t+1/2 ~ ^^t-1/2 ^l^°t b2AToj- + C]^Q|- + C2AQ^. + d]^S^- + d2AS{- (16)

where

di = ci*A (17)

*^2 ~ C2*A. (18)

To determine values for the thermal resistances and capacitances of the model,

a set of the experimental data can be used with a least squares regression to

determine what coefficients in equation (16) would result in the best agreement

between the temperatures predicted by the equation and the measured temperatures. Once the coefficients are known the ETP's can be determined by algebraic techniques from the coefficients.

25
7.2 APPLICATION OF EQUIVALENT THERMAL PARAMETERS CONCEPT

Although the data replacement technique described in chapter 4 was useful for

producing complete monthly totals and also dally totals, the technique produces

small discontinuities in the hourly data at the beginning and end of the

replaced block. Since the ETP technique is a transient analysis, only sets of

NCFOB data that were continuous were used to evaluate the constants in equation

(16). Table 2 in chapter 4 shows that there were a large number of gaps in the

continuous data collection and thus only ten sets of data were selected for use

in the ETP analysis. These ten sets were selected based on the criteria that

they consist of at least five continuous days.

The categories of data used in the analysis had to be carefully selected to

agree with the concept of the terms used in equations (3) and (4). The indoor

temperature terms for the measured data were calculated as an average of five

space temperature measurements on each of the seven floors of office space.

Although there was variation in the temperatures from floor to floor and core

to perimeter, the temperature was assumed to be uniform to preserve the simplicity of the analysis. The outdoor temperature was a single measurement

taken at the roof of the building.

The energy term Q was assumed to be a combination of a number of measured

parameters. During the winter, the heat energy added to the building space is

the sum of the energy added by the HVAC system, the Internal gains due to the

presence of people, and the internal gains from lighting and office equipment.

The energy from the HVAC system had been calculated, as described in chapter 4,

during the data reduction and could be used directly. The internal gain from

lights was assumed to be equal to the electric energy consumed for lighting.

Energy to lighting in the basements and non-office areas was excluded. Miscellaneous office electric energy was used as the internal gain from office equipment. The only quantity not measured was the gain from people. To approximate

the internal gain from people, an assumed daily occupancy profile was used.

This profile was based on a full occupancy of 280 persons, each producing

approximately 120 W of energy. Occupancy was assumed to begin at 7 am and

reach the full value by 8 am, continue until 4 pm at full occupancy and then

decline to unoccupied by 5 pm.

The solar irradiation term was taken from a measurement of tilted irradiation

at 60 degrees in the vicinity of the roof-mounted solar collectors.

Horizontal irradiation was not available.

To illustrate the techniques used to obtain the equivalent thermal parameters

for the Norris Cotton Building, a detailed example will be presented. One time

period selected for analysis was a time period from February 8 through 14, 1980.

During this period, 139 continuous hours of data were taken. The weather

during the period was cold with temperatures ranging from 0°C to -10°C and

solar radiation levels were high. To fit the data collected for this time span

to the model represented by equation (16), the data were arranged to correspond

as closely as possible to the terms of the equation, as described above. A

linear regression was done using a computer program to determine the coefficients in equation (16). The model equation has seven variables and a constant

26
term was included in the determination to improve the fit of data to the model

even though the theory does not predict the existence of a constant term.

Table 3 shows the output of the computer program used to perform linear

regression [12]. The second column of the table contains the computed coefficient for each variable and the third column shows the computed standard deviation for each coefficient. The fourth column of table 3 contains a number,

called the t-ratio, used to test the statistical significance of the coefficient. If any coefficient were equal to zero, then the corresponding variable

would have no statistical effect on the dependent variable. If the coefficient

is assumed to be zero, then the t-ratio is defined as the difference between

the computed coefficient from the regression and the assumed value, zero,

divided by the standard deviation for the coefficient. If the t-ratlo is less

than approximately 2 or 3, then the coefficient may be considered to be equal

to zero. If the t-ratio is greater than 2 or 3, then the variable corresponding to the coefficient is statistically significant and has an effect on the

dependent variable. It may be observed in table 3 that several variables are

not very significant for this data set, most notably the solar irradiation

terms. The lack of significance for the solar irradiation is not surprising

because of the very small window area for the building. The constant term,

the Tq term, the AQ term and the ATo term have low significance in this case. These results might be expected, since the close coupling between the mass and

the building space implies a large heat transfer coefficient between mass and

space and in equation (7) the Q and To terms are divided by this coefficient.

To determine the quality of the fit between the model with the calculated

coefficients and the measured data, the residuals, defined as the differences

between the model predictions and the measured values at all the time steps of

the data, were examined. The residual standard deviation is defined as:

L (observed values-predicted values)

(number of points)-(number of parameters)

(19)

The calculated residual standard deviation was 0.045°C, a value much smaller

than the probable Instrument error. The distribution of the residuals about

the mean was observed to follow a normal distribution, indicating a good agreement between model and measured data.

Table 3 showed that the coefficients a, b2 , and cj^ could be considered

significant. Regressions were not repeated using only significant parameters.

The assumption was made that the coefficients would not change appreciably.

Thus equations (10), (12), and (13) form a set of simultaneous equations for

determination of the equivalent thermal parameters C*, H, and Hs. Since a and Cl had the highest t-ratios, equations (10) and (13) were combined first

to yield the following relationships:

H = (l-a)/ci (20)

and

C* = (2-ciH)/2c]^ ( 21 )

27
If the coefficients from table 3 are substituted in the above equations, the

result is that the heat transfer coefficient between the outside air and the

inside air, H, is calculated to be 18.6 kW/°C; the effective thermal capacity,

C*, is calculated to be 728 kWh/°C; and using equation (12), the transfer

coefficient between the space and the mass, Hs, is calculated as approximately

500 kW/°C.

In order to determine if the above values for the equivalent thermal parameters

are reasonable, the parameters may be estimated from information about the

building envelope. The thermal loss coefficient, H, should have three components for this building. One component, the transmission loss, may be estimated

from the design values for the wall and roof constructions under steady-state

conditions [13]. If this is done the transmission loss coefficient is determined to be 3.5 kW/°C. The second component is infiltration loss and may be

empirically estimated using an air exchange rate that was measured at the building with a tracer gas technique [4]. The measured average air exchange rate

with building air circulation system operating but outside air dampers closed

was determined to be 0.54 air change/hour. With a building volume of 31 150 m^

and an outside air temperature of approximately 0°C, this amounts to an infiltration loss coefficient of approximately 9.5 kW/°C. The final component of

the thermal loss is the effect of forced ventilation of the building using outside air. It is assumed that opening the outside air dampers does not affect

the component of total air exchange rate due to effects other than mechanical

ventilation. The design minimum outside air rate of 5829 i/s (12,350 cfm) was used along with an assumed efficiency of 70 percent for a heat recovery heat

exchanger in the air system for the upper four floors to yield a ventilation

air loss coefficient of approximately 5.8 kW/°C. Combining the three estimated

components yields an estimated loss coefficient of 18.8 kW/°C which compares

well with the value determined from the regression analysis.

The thermal capacity of the building is more difficult to estimate than the

loss coefficient. Typically, the total capacity of the building walls will not

be used in hour-to-hour variations in room temperature during heating [14].

Using half of the wall thickness, the capacity of the building walls was estimated to be 280 kWh/°C, and the capacity of the floors to be approximately 450

kWh/°C. The resulting estimate is in the vicinity of 750 kWh/°C not including

the capacity of the building furnishings. The regression calculated value of

728 kWh/°C is not unreasonable. The value for the heat transfer coefficient

between the mass and the building space calculated from the regression analysis

when divided by the floor area is 45 W/m2» °C which is large but is not unreasonable given the lack of insulation between the air in the building and the walls

and floors.

A comparison betwen the measured inside temperature and the temperature

predicted using the calculated equivalent thermal parameters for the period of

February 8-14, 1980 is shown in figure 20. The original fit between measured

data and model using the full set of coefficients from table 3 was much closer

than shown in the figure, illustrating the effect of assuming all non-significant constants to be equal to zero. The fit is still acceptable, however. The

figure shows a weekend period followed by three working days. No heating is

provided during the weekend and the inside temperature steadily drops. During

the working days the mechanical equipment works to bring the temperature back

28
up. The figure shows that the space temperature never reached the set point

on Monday but gets closer to the set point on succeeding days. In this case,

the building mass works against the mechanical system and slows the achievement

of the space temperature setpoint.

Figure 21 shows the swings in outside temperature during the time period and

the smaller swings of indoor temperature relative to the outdoor temperature.

Also shown in figure 21 is a calculated structure temperature which turns out

to be quite close to the indoor air temperature. The calculation of structure

temperature is highly sensitive to the heat transfer coefficient between the

structure and the indoor air, Hs, and errors in the determination of Hs, which

was determined from a weak coefficient, have a large effect on the magnitude

of the structure temperature. Keeping in mind that the difference between

the structure temperature and the indoor temperature is of the same order of

magnitude as the probable measurement error in the temperatures, the structure

temperature is predicted as being slightly higher than the inside temperature.

The simplicity of the model presents some problems in physical interpretation

of the results but figure 21 seems to indicate that the mass participating in

the heat transfer during this time period may have been mostly the floors and

Interior furnishings since it is known that the wall temperatures in most cases

in the winter were less than the space temperature. Figure 21 illustrates that

the difference between inside and outside temperature is much larger than the

amplitude of the Indoor temperature variations. This means that the massive

walls should not cause any phase differences between Indoor and outdoor

temperature oscillations in this case.

The total energy added to the building space during the February 8 to 14 time

period is plotted in figure 22. These values include both mechanical system

heating requirements and internal gains. The figure shows that during the

weekend, little energy was added but during the weekdays daytime energy

addition was much greater than on weekends.

7.3 RESULTS OF EQUIVALENT THERMAL PARAMETERS ANALYSIS

A total of ten periods of continuous data were analyzed to determine the

equivalent thermal parameters for the Norris Cotton Building. Of the ten, only

four sets of data were judged to fit the simple ETP model acceptably and the

results from these four sets are shown in table 4. Of the unacceptable six

sets of data, four resulted in a relatively large and significant constant

term being generated by the least squares regression. Since the model cannot

explain the physical significance of the constant term, the data did not fit

the model. The problem with these sets may have resulted from error

in some of the measurements or the model may not have taken into account

significant energy transfers existing in the real building during the

time period. Due to physical mechanisms not reflected in the simple

model, a variable such as T may not have statistically significant

regression coefficients. I? the coefficient of this variable is small,

the fit will have a constant term to account for any heat loss caused

by the average indoor-outdoor temperature difference. The two remaining

unacceptable data sets resulted in unreasonable or negative coefficients

from the least squares regression.

29
Of the four data sets that fit the model, the results of the least squares

regression were consistent between sets. Table 4 shows that two sets were from

winter months and two from summer and fall months. The indoor-outdoor air heat

transfer coefficient, H, was found to be larger for the summer months than for

the winter months. This can be explained because during the summer, the heat

loss includes removal of heat from the building by nighttime flushing with outside air and economizer operation. The analysis predicts that these summer operations approximately double heat losses over those experienced during winter

operation.

Table 4 shows that there is a slight increase in the effective thermal capacity

during the summer months Indicating that more of the building mass is being

used. This is as would be expected since no space conditioning is used during

unoccupied hours in the summer and more of the building mass could be expected

to approach the ambient temperature. Figure 23 shows the outdoor. Indoor, and

calculated structure temperature for the time period of June 20 to 29, 1980.

This figure is comparable to figure 21 except that figure 23 is for summer

operation. It may be observed that the structure temperature tracks the inside

temperature closely. The start of mechanical cooling is obvious in the figure

as the inside and the structure temperatures decrease toward a set point.

30
8. RESULTS — MECHANICAL SYSTEMS

The performance of the mechanical equipment at the Norris Cotton Federal Office

Building can be examined at two levels, equipment performance and overall

system performance.

8.1 EQUIPMENT PERFORMANCE

The mechanical systems at the NCFOB utilize several types of equipment and the

hourly data can be used to evaluate, to some extent, the performance of various

types of equipment. In chapter 4, the assumptions used to calculate the performance parameters for the building were stated. For most of the mechanical

equipment, input energy quantities were satisfactorily measured, but to determine

equipment output or efficiency the equipment was essentially simulated.

Four major types of equipment were evaluated using the hourly average data.

These were the natural gas boilers, the heat pumps, the electric chiller, and

the solar system. The efficiencies of the four modular boilers acting together were examined to verify the part-load performance curve assumed in the calculations and determine the operating point of the boiler system in different

months. Figure 24 is a plot of boiler efficiency calculated by the data reduction program during three months of the year versus the boiler output. A

relationship between efficiency and load of this type was assumed for the data

reduction calculations of boiler performance and figure 24 verifies that the

assumed curve was correctly used in the calculations. The points on the figure

lie along one of four curves, depending on how many boilers were operating at

the time. If the efficiencies were plotted versus the boiler output divided by

the full load output of the number of boilers operating, the curves would all

coincide. Three different types of points are displayed in figure 24, one type

for each month of data. The figure shows that in the colder month, February,

most of the points are on the higher end of the four boiler curve, while

in the warmest month, April, most of the points lie on the lower end of the one or two boiler curve. This figure points out that the use of modular boilers

was successful since the boiler loading varied during the year and a single

large boiler would have had lower efficiency at lower loads in spring and fall

(a large boiler might be represented by the 4 boiler curve).

For the heat pump system, the coefficient of performance (COP) for Individual

units was taken from manufacturers data. The hourly data produced by the data

reduction program allows the heat pump system to be viewed as a whole and the

distribution of load point to be examined. Figure 25 shows the calculated COP

for the heat pump system during the month of February 1980. The COP in this case is the sum of all calculated hourly output divided by the input electric

energy to the heat pumps, including energy to the unit fans. During this month

the heat pump load is almost entirely for heating and the loop water temperature was constant. The COP is plotted versus the load and the maximum heating

requirement Indicated on the figure represents the full load heating capacity

of the heat pump system. The general shape of the data in figure 25 is similar

to the curves in figure 24 for the boilers because of the effects of part-load

operation on the heat pump system performance. The most obvious feature of the

figure is the division of the points into two groupings. The upper grouping

31
represents the operation of heat pumps during unoccupied periods. IVhen the

building is unoccupied, only a few of the heat pumps are operating and these

are operating at relatively high part-load points. Thus the apparent COP of

the units is higher as a function of load. The lower curve, then, is for the

occupied period when all of the heat pumps are operating with at least their

fans running. Note that the occupied period points are distributed evenly

along the part-load curve.

Figure 26 represents the calculated COP of the heat pump system during the

cooling season for the month of July 1980. As for figure 25, loop water

temperature was constant during the month, but at a higher temperature than in

winter. Again the maximum value of requirements represents the total steadystate cooling capacity for the heat pump system. For this month of cooling

operation it appears that most of the points are clustered in the lower end of

the part-load curve. The explanation for this is that since the heating loads

predominate in this climate, the heating capacity of the heat pumps determines

the size of the unit. For a given unit the ratio of heating to cooling capacity is relatively fixed, and thus the heat pumps end up being somewhat oversized with regard to cooling capacity. The points in figure 26 generally lie

along a single curve, unlike the points in figure 25, because during the

cooling season no cooling is performed during the unoccupied hours except

under unusual conditions.

The central plant electric chiller input and output were both measured and no approximations were made for the output of the chiller. Figure 27 is a plot of

the measured coefficient of performance (COP) for the electric chiller as a function of the evaporator output. This figure shows that most of the chiller

operation is at around the same load point. However, this point is not the same as the rating of the chiller (211 kW) but is nearly half of the rated

capacity. It is not clear if this discrepancy is real or due to measurement

error. The rated conditions for the electric chiller were examined, and it was noted that the measured evaporator flow rate was approximately half of the

rated flow rate. This low flow rate could be due to some measurement error or could be correct and represent a problem in the chilled water circuit which is

reducing the flow rate.

The solar system at the Norris Cotton Building and the use made of the solar

heated water were described in chapter 2. During the year of monitoring by the

JC-80, the solar system provided energy for service hot water and met most of

that load. Very little energy was supplied to the hot water heating system at

the building.

The solar array on the roof was operated all year during daylight hours even

if the energy collected could not be put to any use. The performance of the

array was monitored and the information collected is useful in illustrating

the performance of solar collectors in an array on an actual installation that

has been in service for several years. Figure 28 is a plot of solar collector

efficiency based on the gross area of the array plotted versus a term to represent the operating level of the collectors as recommended by ASHRAE standard

93-77. The operating level term is the inlet temperature to the collector

array minus the ambient dry bulb temperature divided by the solar irradiation

32
I

i

per unit area on the collector array. The data points in the figure are hourly averages taken from three different months. Points taken when the solar

pumps were not operating at full speed for the entire hour were not plotted in

figure 28. There is a large amount of scatter visible in the data since the

points were not taken under laboratory conditions but represent a large number

of environmental conditions which would tend to shift the efficiency curve around on the plot. The points from February and the points from April

generally lie in the same area of the plot. The line on the figure represents

an average performance curve for the array based on laboratory tests of individual collectors of the same types as those in the array. The average array

performance is determined by weighting individual performance test results by

the area of the collector types in the array and by using the assumption that

the flow rates in the array are the same as for the collectors during the lab

tests. The existence of higher or lower flow rates in the individual rows of

the collector array than were used in the lab tests would result in a shifted

performance curve.

The efficiency points for the array during August are in general much lower

than the winter or spring points. During the summer, Irradiation and ambient

temperature levels are much higher than in the winter. If there are collectors

in the array with restricted flow, local boiling in parts of the collector

array can result. If this problem is excessive, the array can become steambound, resulting in a much lower efficiency curve. It is likely that this has

occurred at the Norris Cotton Building since steam has sometimes been observed

being discharged at relief valves in the array.

8.2 TOTAL MECHANICAL SYSTEMS PERFORMANCE

In large buildings, equipment exists which supplies required ventilation and

transfers thermal energy, produced from the fuel, to heat or cool the building

space. This equipment, which includes pumps, controls, and fans, requires

energy to operate in addition to the fuel used to satisfy the building loads.

Such energy usage may be termed energy distribution energy or "operating energy.

It is important to look at both the operating energy and the fuel energy in

studying large buildings.

Figure 29 is a plot of the total fuel energy used per hour, including electric

energy to the compressors in the heat pumps, versus the heating requirements

calculated by the method in section 4.3 using data from February 1980. The

data in figure 29 fall into a straight line with little scatter, due to the

assumptions about equipment performance and the assumption that there is no transmission loss from pipes and ducts in transferring energy from the central

plant to the building conditioned space. As the heating requirements approach

zero, the fuel use also decreases toward zero.

The measured operating energy per hour for the same period of data collection

as in figure 29 is shown in figure 30. The operating energy is plotted versus calculated heating requirements but there appears to be very little relationship

between load and operating energy, as expected. There are two groups of data

in figure 30, the upper group with a magnitude of about three times the lower

group. The upper group represents occupied building operation with all

33
ventilation fans operating and the lower group is for unoccupied operation with

only minimal operating energy.

Figure 31 is similar to figure 29 but represents fuel energy data from July

1980 during the cooling season. The fuel energy for cooling, mostly electric

energy to the compressors in the heat pumps and the chiller, is plotted versus

the calculated hourly cooling requirements. As in the case of the heating

season data, the points lie in a straight line with little scatter because the

cooling requirements were calculated from manufacturer equipment capacity data

and measured input energy.

The operating energy for July 1980 is shown in figure 32, which is analagous

to figure 30. The operating energy points are plotted versus the cooling

requirements, and as with the heating points, fall into two groups, the occupied

hours and the unoccupied hours. During the summer, usually no space conditioning is used during the unoccupied hours and thus the cooling requirements are very small. The unoccupied operating energy points all cluster at lower cooling requirements for this reason. The upper group of points, representing the

occupied hours, shows a very slight increase with increased cooling

requirements

.

The concept of efficiency is useful in measuring the performance of a total

mechanical system. For heating season operation the hourly average efficiency

of the mechanical system was defined as the calculated heating requirements for

an hour divided by the measured total energy used for heating, where the total

energy for heating includes operating energy but does not Include non-HVAC

energy such as for lighting. The hourly efficiency can be plotted versus the

heating requirements to produce a part-load heating efficiency curve and this

is done in figure 33 for data from the month of February 1980. As in previous

figures, two groups of points occur, corresponding to unoccupied and occupied

operation. The system efficiency approaches 70 percent during occupied hours,

a figure which includes the effects of boiler efficiency, heat pump COP, and

relative amounts of fuel and operating energy. The calculation of efficiency

assumes that all piping and duct losses from the HVAC system are not really

lost but help satisfy heating requirements by convection and radiation of lost

heat into occupied spaces. The efficiencies for unoccupied heating in figure

33 are higher for a given load because the operating energy is much less than

during occupied hours when all pumps and fans are operating.

Figure 34 is similar to figure 33 except that instead of efficiency, the

concept of cooling factor is used. Cooling factor is used here to mean the

calculated cooling requirements for one hour divided by the measured total

energy used in the same hour for cooling, including operating energy. The

occupied cooling factor approaches about 1.2 at larger loads. This is less

than the COP’s of individual pieces of equipment such as heat pumps and the

electric chiller because the operating energy brings down the net cooling

factor. The unoccupied data points are generally at low loads and low cooling

factors

.

34
9. CONCLUSIONS

1. An automated data acquisition system was operated at the NCFOB compiling

7441 complete hours of data out of a possible 9504. The longest uninterrupted

period was 17.75 days in September 1980 and the longest outage was 10 days in

September 1979.

2. A number of major problems were experienced in the checkout and operation

of the minicomputer control/data acquisition system at the NCFOB due to three

major causes: proprietary system software which was difficult to evaluate;

lack of contractual agreements between NBS, the commercial supplier of the

system, and the building operator; and the fact that the system was a commercial design, lacking laboratory accuracy and the capability for on-site system

changes

.

3. A technique of replacing missing or unusable hours of data with data from

similar hours and changing the date on the replacement hours was successfully

utilized. The technique did result in discontinuities when the data was used

for transient analysis.

4. Hourly average data from the control/data acquisition system was used to

calculate monthly, daily, and hourly building energy performance parameters.

Parameters based on electrical energy measurements were considered the most

reliable.

5. The complexity of the HVAC system design and failure of the instrumentation

to produce originally-planned measurements, prevented the collected data from

being used to make detailed floor-by-floor comparisons of HVAC equipment.

6. Using simplified transient heat transfer analysis, equivalent thermal

parameters were determined from actual continuous hourly data. The calculated

parameters compared well with estimated values. This technique is useful for

determining dynamic heat transfer coefficients in large buildings with

simple measurements.

7. Based on the equivalent thermal parameter analysis, the small windows in

the building were found to admit an insignificant amount of solar energy.

8. Based on the equivalent thermal parameter analysis, the insulation design

of the Norris Cotton Building was found to be effective in producing a low

transmission loss for the building. During the heating season however, the

large mass, closely coupled with the interior space, was found to inhibit the

return to desired temperatures after an unoccupied period when the space

temperature set point had been setback.

9. Reduced data from boiler fuel consumption and boiler operating hours showed

that the use of modular boilers resulted in higher boiler efficiencies over the use of a single large boiler.

10. Reduced data on heat pump system performance show that hourly COP’s of the

heat pump system are lower in summer than winter. The units are sized for the

35
large heating loads in winter and not the smaller cooling loads in summer and

therefore operate at a lower, less efficient part-load point in summer.

11. Hourly average total mechanical system heating efficiency calculated from

assumptions about equipment performance approached a maximum of 70 percent at

large loads in the month of February 1980 during occupied hours. This figure

includes operating energy and fuel energy. Average heating efficiency for

February was 30 percent.

12. The hourly average mechanical system cooling performance factor calculated

from measurement and assumptions of equipment performance was observed to

approach a maximum of 1.2 for large cooling loads in July 1980. This figure

includes operating energy and fuel energy. Average cooling factor for July was

0.91.

36
10 . REFERENCES

[1] Isaak, N. ; Isaak, A. Designing an Energy Efficient Building. General

Services Administration/Public Buildings Service spec. publ. 1975

September, 43 p.

[2] Hill, J. E.; May, W. B.; Richtmyer, T. E.; et al. Performance of the

Norris Cotton Federal Office Building for the First Three Years of Operation. Nat. Bur. Stand. (U.S.) Bldg. Sci. Ser. 133; 1981 June, 125 p.

[3] Elder, J.; Tibbott, R. L. User Acceptance of an Energy Efficient Office

Building - A Study of the Norris Cotton Federal Office Building. Nat.

Bur. Stand. (U.S.) Bldg. Sci. Ser. 130; 1981 January, 122 p.

[4] Hunt, C. M. Ventilation Measurements in the Norris Cotton Federal Office

Building in Manchester, New Hampshire. ASHRAE Transactions. Vol. 85,

part 1, 1979.

[5] Richtmyer, T. E.; May, W. B.; Hunt, C. M.; Hill, J. E. Thermal Performance

of the Norris Cotton Federal Office Building in Manchester, New Hampshire.

Proceedings of the DoE/ASHRAE Conference on Thermal Performance of Exterior

Envelopes of Buildings; 1979 December; Orlando, FL.

[6] Kelly, G. E.; Didion, D. A. Energy Conservation Potential of Modular

Gas-Fired Boiler Systems. Nat. Bur. Stand. (U.S.) Bldg. Sci. Ser. 79;

1975 December, 54 p.

[7] Mulroy, W. J.; Kelly, G. E. Laboratory Tests of a Residential Unitary

Water-Source Heat Pump. Nat. Bur. Stand. (U.S.) NBSIR in preparation;

1981

.

[8] General Services Administration/Publlc Buildings Service. Energy

Conservation Design Guidelines for New Office Buildings. 2nd Edition,

1977, 324 p.

[9] Kusuda, T.; Tsuchiya, T.; Powell, F. J. Prediction of Indoor Temperature

by Using Equivalent Thermal Mass Response Factors. Proceedings of the

5th Symposium on Temperature. Nat. Bur. Stand. (U.S.), Washington, D.C.

1971.

[10] Sonderegger, R. Diagnostic Tests Determining the Thermal Response of a House. ASHRAE Transactions. Vol. 84, part 1, 1978.

[11] Kimura, K. ; Ishino, H.; Komiya, H. ; Matsura, J. Study on the Comparative

Verification of Various Methods of Air Conditioning Load Calculation by

Field Measurements, Second Symposium on the Use of Computers for

Environmental Engineering Related to Buildings, 1974 June.

[12] Hogben, D. ; Peavy, S. T.; Varner, R. N. Omnitab II User's Reference

Manual. Nat. Bur. Stand. (U.S.) Tech. Note 552; 1971 October, 264 p.

37
13. May, W. B.; Spielvogel, L. G. Analysis of Computer Simulated Thermal

Performance of the Norris Cotton Federal Office Building. Nat. Bur.

Stand. (U.S.) NBSIR 80-2093; 1980 November, 62 p.

14. B^rresen, B. A. Heat Storage in Walls. Building Service Engineer

(British). Vol. 41, 1973 December, p. 17.

38
39

Figure

1.

Schematic

diagram

of

Norris

Cotton

Federal

Office

Building

mechanical

system.
Figure 2. Diagram of JC-80/55 minicomputer control system configuration

at Norris Cotton Federal Office Building.

AO
DAILY

DATA

LOG

(NIPPO)

REQUESTED

BY:

SYSTEM

02

JUL.

1980

00:06

TITLE:

PAGE

29

Figure 3

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Format of data contained on magnetic tapes generated at the Norris

Cotton Federal Office Building.

41

000

000
MAIN BREAKER

Figure 4. Diagram of electric power distribution system at Norris Cotton

Federal Office Building. Circled numbers indicate kilowatt-hour

meters

.

42
12

3

4

5

6

7

a

9

10

1

1

12

13

14

15

01 H SO 06 01 14 30

02 H SO 06 01 14 30

03 H SO 06 01 14 30

04 H SO 06 01 14 30

05 H 80 06 01 14 30

06 H SO 06 01 14 30

NN A NN NN NN NN NN

CPAGETYPE #3 C AVG I NTER VAL 3 C YEAR 3 C MONTH 3 C DAY 3 C HOUR 3 C DAYS/M0NTH3

PAGE7YPES:

1. ENERGY CONSUMPTION AND PERFORMANCE

2. BUILDING HEATING REQUIREMENTS

3. BUILDING COOLING REQUIREMENTS

4. ELECTRICAL ENERGY USE

5. SOLAR SYSTEM PERFORMANCE

6. BUILDING ENVIRONMENT

5. Sample instruction file for table-producing data retrieval

program.

43
GJ/MONTH

GJ/MONTH

800.0

700.0

600.0

500.0

400.0

300.0

200.0

100.0

0.0

1979-1980

Figure 6. Total energy consumption at the NCFOB building boundary as calculated

from JC-80 and manual readings

1979-1980

Figure 7. Natural gas consumption at NCFOB as calculated from JC-80 and

manual readings.

44

10

BTU/MONTH

NATURAL

GAS

10®

BTU/MONTH
1979-80

Figure 8. Major categories of electrical energy consumption for the NCFOB

as calculated from JC-80 and manual readings

1979-80

Figure 9. Electrical energy use for lighting on lower floors of NCFOB as calculated from JC-80 and manual readings.

45
1979-80

Figure 10. Electrical energy use for lighting on upper floors of NCFOB as calculated from JC-80 and manual readings.

1979-80

Figure 11. Electrical energy use for lighting on essential circuits of

NCFOB as calculated from JC-80 and manual readings.

46
1979-80

Figure 12. Miscellaneous office electrical energy use at NCFOB as calculated from JC-80 and manual readings.

1979-80

Figure 13. Miscellaneous office electrical energy use at NCFOB as calculated from JC-80 and manual readings.

47
1979-80

Figure 14. Electric energy used by fan coils and solar pumps at NCFOB as calculated from JC-80 and manual data.

1979-80

Figure 15. Electric energy use by heat pumps at NCFOB as calculated from

JC-80 and manual data.

48
:

I

z

o

toO

SEP OCT NOV DEC JAN FEB MAR APR MAY JUN JUL AUG SEP

. 1979-80

Figure 16. Mechanical equipment electrical loads at NCFOB as calculated

from JC-80 and manual data.

49
CL

UJCt

X

O

3

q:

a:

X

X

LJ

Ct

X03X

200

150 -

100 •-

50 -

0

Feb. 10

Jun. 22

11

23

12

24

-100% occupied

Figure 17 . Demand profile of total energy for lighting at NCFOB.

Figure 18. Demand profile of office miscellaneous electric loads at

NCFOB

.

50
TO

Figure 19. Electrical circuit analogy for equivalent thermal parameter

model.

51
Q

ll) o

q;

lli

Lij

cn

23

Figure 20. Comparison of average inside temperature at Norris Cotton Federal

Office Building measured by JC-80 and calculated by ETP analysis

for February 1980.

Figure 21. Measured outdoor, indoor and structure temperatures calculated

by ETP analysis for Norris Cotton Federal Office Building during

February 1980.

52
O

UJO

D:

UJ

UJ

(/)

400

300

W

200

100

0 I I I 1 II I I TT I T I 'I ' r T

Feb. 8 9 10 11 12 13 14

Figure 22. Ffeasured addition of internal and heating energy to building

space of Norris Cotton Federal Office Building during

February 8-14, 1980.

Figure 23. Measured outside and inside temperatures and structure

temperatures calculated by FTP analysis for Norris Cotton

Federal Office Building during June 20-29, 1980.

53
E

F

F

IC

IE

N

C

Y

BOILER OUTPUT, KWH/HR

Figure 24. Natural gas boiler efficiency as a function of boiler output

at the Norris Cotton Federal Office Building.

3.0

2.5

H

E

A

T 2.0

IN

G

1 .5

C0

P

1 .0

0.5

0.0

0 50 100 150 200 250 300 350

HEATING REOUIREflENTS, KWH/HR, FROM FEBRUARY 1980

Figure 25. Heating performance of heat pump system at Norris Cotton Federal

Office Building during February 1980.

54
2.5

0 50 100 150 200 250 300

COOLING REOUIREHENTS. KWH/HR, FROM JULY 1980

Figure 26. Cooling performance of heat pump system at Norris Cotton Federal

Office Building during July 1980.

COOLING REQUIPvEMENTS, KWH/HR

Figure 27 . Measured performance of electric chiller at Norris Cotton Federal

Office Building during July 1980.

55
1 .0

0.8

E

F

F

I

^ 0.6

E

N

C

Y 0.4

0.2

0.0

0.00 0.05 0.10 0.15 0.20 0.25 0.30

(T, IN-T, Al/SOLAR (*C • m^) /W

Figure 28. Solar collector array efficiency at Norris Cotton Federal

Office Building.

400

H

P

E

R

H 300

0

U

R

100

0

0 50 100 150 300 350 300

KUH PER HOUR

Figure 29. Fuel energy for heating versus calculated heating requirements

at Norris Cotton Federal Office Building during February 1980.

4* February 1980

4. April 1980 ^ August 1980

56
CL

IxJ

Ct

X

O

13

Ct

80

K

U

H

P

E

R

H

0

U

R

0 50 100 150 200 250 300

KUH PER HOUR

Figure 30. Operating energy versus calculated heating requirements during

February 1980 at the Norris Cotton Federal Office Building.

I<.WH PER HOUR

Figure 31. Fuel energy for cooling versus cooling requirements at the

Norris Cotton Federal Office Building during July 1980.

57
100

0

P

E 80

R

A

TN

G 60

E

N

ER 40

G

Y KWH

HR 20

0

0 50 100 150 200 250 300

COOLING LOAD KWH PER HOUR

Figure 32. Operating energy versus calculated cooling requirements during

July 1980 at Norris Cotton Federal Office Building.

1.0

H

E

A

T

I 0.8

N

G

E

F 0.6

F

IC

IE 0.4

N

C

Y

0.a

0 50 100 150 800 850 300

KUH PER HOUR

Figure 33. Total mechanical system efficiency for heating versus calculated

heating requirements at Norris Cotton Federal Office Building

during February 1980.

unoccupied

if *

+ + X

*<• <*

occupied

1—I—I—

r

T 1 1 T "I 1 T 1—r—I—

r

T—I—I—I—'—I—I—

r

58
COOLING REOUIREMENTS, KWH/HR, FROh JULY 1980

Figure 34. Total mechanical system performance factor for cooling

versus calculated cooling requirements at Norris Cotton

Federal Office Building during July 1980

1—

300

59
Table 1. Analog sensor types used by JC-80 system at the

Norris Cotton Federal Office Building

Sensor type Quantity Description

Liquid flowmeters 79 Impact tube combined with reversed

static tube. Pressure differential

fed into transducer.

Air flowmeters 55 Array of pitot tubes to determine

average air velocity in ducts.

Liquid temperature

air temperature

286 Nichrome wire-wound resistance

temperature element.

Air dewpoint

temperature

49 Nichrome wire-wound resistance

temperature element combined with

dewcell.

Air humidity 6 Humidity elements.

Flue gas temperature 7 Thermocouples

.

Natural gas flow 7 Positive displacement meter.

Illumination 15 Photoelectric cells

Solar radiation 5 Pyranometer

Electric energy 98 Contact closure in kilowatt-hour

meter

.

60
Table 2. Description of data loss from Norris Cotton Federal Office

Building data acquisition system

Month

Number of

hours

in month

% of

hours

usable

% of

hours

replaced

Longest

uninterrupted

period (days)

Longest

outage

(days)

September 79 720 50.1 49.9 6.25 10.00

October 79 744 61.3 38.7 8.29 9.71

November 79 720 74.9 25.1 4.54 1.58

December 79 744 76.1 23.9 6.50 2.00

January 80 744 77.2 22.8 5.79 2.38

February 80 696 82.6 17.4 5.83 1.00

March 80 744 88.0 12.0 4.38 0.67

April 80 720 80.0 20.0 10.67 4.42

May 80 744 75.3 24.7 9.33 5.71

June 80 720 81.8 18.2 9.08 4.21

July 80 744 95.3 4.7 10.58 1.00

August 80 744 80.9 19.1 14.42 5.00

September 80 720 94.3 5.7 17.75 1.00

Average 78.3 21.7

61
Table 3. Estimates from least squares fit to equivalent thermal

parameter model using data from February 9-15, 1980

Independent Standard Deviation Coefficient

variable Coefficient of coefficient t-Ratio

T a = 0.974175 0.005072 192.05

To bi = -0.001665 0.002371 0 • o 1

ATo b2 = 0.035435 0.009251 3.83

Q Cl = 0.001390 0.000061 22.74

AQ C2 = -0.000141 0.000209 -0.68

S di = -0.051665 0.024551 -2.10

AS d2 = -0.135498 0.048453 -2.80

Constant e = 0.333352 0.112416 2.97

Residual standard deviation = 0.044668171

; based on degrees of freedom 137 - 8 = 129

62
Table 4. Results from equivalent thermal parameters

analysis of four data sets

hours in data set

Dec 22-28

154

Feb 09-15

139

Jun 21-30

217

Sep 06-24

425

a, coeff. of 0.983793 0.974175 0.969487 0.973435

b]^, coeff. of Tq 0.0077678 NS 0.008986 0.008956

b2 » coeff. of ATq NS 0.035435 NS NS

C]^, coeff. of Q 0.001110 0.001391 0.001021 0.001007

C 2 , coeff. of AQ NS NS NS -0.001014

di , coeff. of S NS NS NS NS

d2 , coeff. of AS NS NS NS NS

e, constant NS 0.333 NS NS

H, kW/°C 14.6 18.6 29.9 26.4

C*, kWh/°C 893.3 728.4 994.9 1006.0

NS - not significant

63
Appendix — Detailed Description of NCFOB Energy Data Output Sheets

A full listing of the Norris Cotton Federal Office Building (NCFOB) energy data

for a given period of time consists of six 132 column computer pages. Each

page displays a different category of data as a function of time. Data can be

for hourly, daily, or monthly time periods with six to seven time periods worth

of data on one page. The tables at the end of this appendix contain monthly

data for the 13 months of data collection.

All of the six data pages have certain features in common. At the top of each

page is a title describing the type of data. Below the title is information

describing the time span of the data and the type of time period. Data are contained in six to seven vertical columns with column headings indicating the

time period for the data in the column. The energy parameter names for the

data on the page are located at the left of the page.

The data values printed on each page are usually in electrical or thermal

kilowatt-hours. All other units used are SI units. The numbers are printed in

a format that provides at least four significant figures. However, it may not

be true that the numbers are correct to four figures.

Data Page 1: Energy Consumption and Performance

The first of the six pages of data is Intended to provide overall energy

consumption and energy balance information. A general breakdown of fossil fuel

(oil and gas) use and electrical energy use is presented, followed by figures

for energy rejected from the building during cooling operations. Also presented

are total energy use figures and solar system general performance parameters.

The following definitions describe the parameters in detail:

Total Natural Gas Use is the thermal equivalent of the natural gas delivered

to the building main during the given time period.

NG to Boilers is the thermal equivalent of natural gas entering the four

natural gas modular boilers.

Fuel Oil to Boilers is the thermal equivalent of the fuel oil fed to the oil

boilers. This value is from manual readings and is available only for monthly

periods

.

Boiler Energy to Heating is the energy transferred from the oil and gas boilers

to the heat pump or hot water systems for heating purposes.

Boiler Energy to Cooling is the energy transferred from the fuel oil boilers

to the concentrator of the absorption chiller. Gas boilers are never used for

cooling purposes.

NG to Eng/Gen is the thermal equivalent of the natural gas delivered to the

gas engine-generator set.

64
Eng/Gen to Electric Chiller represents the quantity of electrical energy used

by the electric chiller when the chiller is supplied by the engine-generator

rather than by purchased power.

Heat Recov. to Cooling is the energy recovered from the water jacket and

exhaust stack of the engine-generator and utilized to provide thermal energy

to the absorption chiller. This is the sum of waste heat energy supplied to

the chiller directly and from storage.

Heat Recov. to Heating is the energy recovered from the water jacket and

exhaust stack of the engine-generator and utilized for space heating by the hot

water and heat pump systems.

Heat Recov. to D. Hot Water is energy recovered from the engine-generator and

used to heat domestic hot water.

Eng/Gen to Auxiliary Power is the electrical energy delivered to loads other

than the chiller by the engine-generator. These other loads consist of sections

of the motor control center. The motor control center supplies the major pumps

and motors and may be driven by the generator when the chiller electrical load

is not great enough to generate sufficient waste heat to drive the absorption

chiller.

NG to Dorn. Hot Water is the equivalent thermal energy for the natural gas used

by the conventional domestic hot water heater.

Heater Energy to DHW is the thermal energy added to the main domestic hot water

tank by the conventional hot water heater.

Total Electrical Energy Use is the electrical energy measured at the building

main power bus.

Electric Energy to Heating is the electrical energy delivered to those heat

pumps which are in the heating mode.

Electric Energy to Cooling is the energy delivered to those heat pumps which

are in the cooling mode.

Electric Energy to HVAC Systems includes the electrical energy to all heat

pumps, pumps, fans, controls and other pieces of equipment associated with

heating, cooling and ventilating the building space.

Electric Energy for Lighting is the energy for all lighting, external and

internal, at the NCFOB.

Miscellaneous Electrical Loads includes all non-lighting and non-HVAC loads

such as receptacle loads, snow-melting equipment, and elevators.

Energy Rejected during Cooling is the thermal energy rejected from the water

loops of the building closed-circuit coolers during operation of chillers or heat pumps in a cooling mode.

65
CCl(HPS) represents energy rejected by the closed circuit cooler for the heat

pump system.

CC2( Condensers) represents energy rejected by the closed circuit cooler which

cools the chiller condensers.

CC3 (ENG/GEN) represents energy rejected by the closed circuit cooler which

dumps excess waste heat to keep the engine/generator jacket temperature below

a safe level.

Total Energy Consumed is the sum of the electrical energy and the equivalent

thermal energy of the natural gas and fuel oil used by the building at the

building boundary.

HVAC Energy Consumed is the electrical energy used for HVAC purposes plus the

thermal equivalent of the natural gas and oil by the building.

Total Building HVAC Load is the sum of the space heating and cooling

requirements plus the domestic hot water load. It represents the energy that

must be added to or removed from the space to maintain acceptable comfort

levels

.

Solar Energy Incident is the total solar radiation energy which falls on the

tilted solar collector surface on the roof of the building. The total gross

collector area is 352.6 m^.

Useful Solar Energy Collected is the thermal energy removed from the solar

array and stored in one of the storage tanks. If the temperature at the solar

array output is less than the lowest tank temperature the solar loop is run in

a bypass mode and no energy is stored. The useful energy value is an estimate

based on solar and storage tank temperatures.

Solar Energy Utilized is that part of the thermal energy drawn from storage

which was originally obtained from the solar collector array.

Solar to Heating (HWS) is the solar energy drawn from the storage tanks for use in the hot water system.

Solar to Heating (HPS) is the solar energy drawn from the storage tanks for use in the heat pump system.

Solar to Cooling is the solar energy drawn from the storage tanks in the summer

for use in the absorption chiller.

Solar to Hot Water is the solar energy drawn from the storage tanks for use in

heating domestic hot water.

Solar Utilization Efficiency is the percentage of the total solar energy

falling on the collector panels which is utilized in the building mechanical

systems for heating or cooling purposes.
Solar Fraction of HVAC Load is that portion of the energy to HVAC Systems

which is provided by energy collected from the solar array.

Total HVAC Performance Factor represents the efficiency of the building

mechanical systems in meeting the heating and cooling load. This factor is the

HVAC load divided by the total energy consumed for HVAC purposes.

Data Page 2: Building Heating Loads

Building heating requirements are broken down on the first three floors by

floor zone for space loads and ventilation loads. Core zones include the area

in the central part of the building where the central air systems are located.

Perimeter zones consist of the areas around the outside of each floor near the

windows. For the upper four floors the total heating requirements only, are given.

Definitions of specific parameters are included below:

Total Heating Load is the energy added to the building space to maintain

comfort levels.

Percent Loads Supplied are the amounts of energy of different types applied to space

heating divided by the space heating load. Fossil fuels are used in the boilers

to generate thermal energy. Heat recovery is energy recovered from the engine

generator. Cooling heat rejection is energy from the chiller condenser applied

to heating.

Percent Loads Handled are the percentages of the total load carried by the two

primary space heating systems.

Heat Pump System COP is the coefficient of performance for heating calculated

for the heat pump system as a whole. In this case the C.O.P. equals the total

energy rejected from all heating mode heat pumps of the space divided by the

electric power consumption of all heat pumps in the heating mode.

Data Page 3: Building Cooling Loads

Cooling loads are broken down in the same manner as heating loads (see Data

Page 2: Building Heating Loads). Definitions of specific parameters are included below:

Total Cooling Load is the energy removed from the building space to maintain

comfort levels.

Cooling Energy Used is the energy required by refrigerating equipment to remove the energy of the total cooling load from the building.

Percent Energy Supplied represents the amounts of different types of energy

applied to space cooling divided by the total cooling energy used (see above).

Fossil fuel energy Includes thermal energy from boilers and electrical energy

from the engine generator. Heat recovery is thermal energy obtained from the

67
engine generator and used in the absorption chiller. Outside air may be used

for cooling when outside air enthalpy is below Inside air enthalpy.

Percent Loads Handled are the percentages of the total cooling energy used by

each of three major cooling subsystems.

Chilled Water Production by Electric Chiller is the energy removed from the

chilled water system by the electric chiller to lower the chilled water

temperature

.

Chilled Water Production by Absorption Chiller is the energy removed from the

chilled water system by the absorption chiller to lower the chilled water

temperature

.

Data Page 4: Electrical Energy Used

The information on this page describes the electrical energy usage by the

NCFOB. Major loads are the lighting, HVAC and miscellaneous electrical loads.

Definitions of the major loads are included in the data page one definitions.

Other selected definitions are given below:

Electrical Energy for Normal Lighting is the energy to those lights which are

not considered essential in case of power failure. This category includes the

bulk, of office and lobby lights.

El. Energy for Essential Lighting is the energy to those lights which are considered essential during a power failure. This category includes stairway

and penthouse lights.

Totals Heat Pumps and component heat pump loads for each floor represent the

electrical energy consumption by all heat pumps in the building or on a floor,

regardless of the heat pump mode.

Totals Fan Coils and component fan coil loads for each floor represent the

electrical energy consumption by all fan coil units in the building or on a floor

.

Fans is the total electrical energy consumption for the four central air

system fans; two supply and two return fans.

Evaporative Coolers is the electrical energy consumed to operate the three

closed circuit coolers in the building.

Electric Chiller is the electrical energy consumed by the electric chiller.

Total, Pumps and Misc. Motors is the public utility generated electrical

energy consumed by all of the important pumps and most of the minor fans

in the building.

Solar System Pumps is the electrical energy consumed by the two solar system

variable speed pumps.

68
Controls and Mlsc. is the electrical energy to a number of devices not Included

in other categories but which have a function in the HVAC systems. Devices in

this category include the pneumatic control system air compressor, pneumatic

control panels, furnace controls, elevator machine room air conditioner and

miscellaneous fans and pumps not included under the pumps and motor category.

Elevators is the electrical energy consumed by the three elevators in the NCFOB.

Fire, Computer and Emergency Systems is the electrical power used by the JC-80

minicomputer and the fire and other emergency warning systems.

Undocumented Loads are miscellaneous loads not individually metered.

Data Page 5: Solar System Performance

This page is intended to report the thermal performance of the solar energy

system on the NCFOB. There are four rows of solar panels in the solar array,

each row containing collectors of a different design. Definitions of the solar

system parameters are given below:

Total Energy Incident is the total solar irradiation falling on the gross area

of the array in the time period specified.

Useful Solar Energy Collected ; See the definition for data page 1.

With Temp. > 70°F, < 110°F ; quantity of solar energy which is collected at a temperature level greater than 21°C (70°F) but less than 43°C (110°F).

With Temp. > 110°F, < 130°F : is the solar energy collected at a temperature

level greater than 43°C (110°F).

With Temp. > 130°F, < 180°F ; is the solar energy collected at a temperature

level greater than 54°C (130°F).

With Temp. > 180°F, < 220°F ; is the solar energy collected at a temperature

level higher than 82 °C (180°F) during the summer.

With Temp. > 220°F ; is the solar energy collected at a temperature level greater

than 104 “^C (220°F). This energy can sometimes be used in the absorption

chiller

.

Solar Array Collection Efficiency is the average net energy gain in the

collector fluid passing through the solar array divided by the total energy

incident on the gross area of the array (352.6 m^).

Total System Collection Efficiency is the useful solar energy collected (see

data page 1) divided by the total energy incident on the gross area of the

array.

Electrical Energy to Operate System is the electrical energy required to run

the solar system pumps and the pump speed controller.

69
Solar System COP is the Useful Solar Energy Collected (see definition on data

page 1) divided by the electrical energy to operate system (see definition

above )

.

Tank Degree C-Hours are the temperatures of the three storage tanks multiplied

by the number of hours in the time period for the data. These values are of

primary interest in hourly printouts.

Data Page 6: Building Environment

The sixth page of the performance data is Intended to display the conditions

of the inside and outside building environment at the NCFOB. Definitions of

the reported quantities are included below:

Average Outside Dry Bulb Temp. (Day) is the dry bulb temperature measured on

the roof of the NCFOB averaged over the daylight hours.

Average Outside Dry Bulb Temp. (Night) is the dry bulb temperature measured on

the roof of the NCFOB averaged over the hours after sunset and before sunrise.

Average Outside Humidity (Day) is the relative humidity of the outside air

measured on the roof of the NCFOB averaged over the daylight hours.

Average Wlndspeed is the magnitude of the wind velocity measured above the

roof of the NCFOB averaged over the time period specified for the data.

Inside Space Temperatures are the average dry bulb temperatures for each of

the floors in the NCFOB. In most cases the core, north, south, east and west

zone temperatures are averaged to obtain the floor average. OCC designates the

temperature averaged over the hours that the floor is occupied (see definition

below). UNOCC designates the temperature averaged over the hours that the

floor is unoccupied.

Space Humidities are the average relative humidities for the main seven floors

of the NCFOB. The values are averages over the occupied hours of the floor.

The humidity values are derived from the core dewpoint and dry bulb temperatures except for the second floor humidity which is the average of the

humidities in the five floor zones.

Occupied Hours for a floor are the number of hours that the floor is in a so-called occupied mode. The occupied/unoccupied modes can be set by the building operator or the JC-80 minicomputer. When in unoccupied mode the air systems

are shut down and no cooling is provided. In winter, some minimum temperature

is maintained. Unoccupied mode is usually maintained at night or on weekends.

Hot Water Use is the net energy removed from the domestic hot water loop

which circulates through the NCFOB.

Average HW Temp, is the average of the domestic hot water temperature measured

in the hot water circulating line at the outlet of the domestic hot water

storage tank.

70
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3393

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2335

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TOTAL

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PERFORMANCE

FACTOR.

3161.

29S4.

1882 8

1376-02.

3053.

6618

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ENERGY

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88
NBS-114A (REV. 2-80

U.S. DEPT. OF COMM.

4.

1 . BIBLIOGRAPHIC DATA

SHEET (See instructions)

PUBLICATION OR 2 REPORT NO.

. Performing Organ. Report No. 3.

81-2358

Publication Date November 1981

TITLE AND SUBTITLE

ANALYSIS OF DATA FROM THE ENERGY MONITORING AND CONTROL SYSTEM AT THE NORRIS

COTTON FEDERAL OFFICE BUILDING

5. AUTHOR(S)

William B. May, Jr.

6. PERFORMING ORGANIZATION (If joint or other than MBS. see instructions) 7. Contract/Grant No. NATIONAL BUREAU OF STANDARDS

, DEPARTMENT OF COMMERCE 8. Type of Report & Period Covered

WASHINGTON, D.C. 20234

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

The Department of Energy

Washington, D.C. 20585

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)

The Norris Cotton Federal Office Building (NCFOB) in Manchester, New Hampshire, is a medium-size office building, occupied in September 197 6, designed to serve as a demonstration and a feasibility test for energy-conserving building features. A

building energy monitoring and control system was operated as a data acquisition

system over a 13-month period ending in September 1980. Experience encountered

during the checkout and operation of the system is discussed. Results from data

reduction procedures used to calculate approximately 160 parameters describing the

energy performance of the building are presented on a monthly basis. Hourly data

are also presented for daily building operation profiles, building envelope performance, and performance of the mechanical systems.

12. KEY WORDS (S/x to twelve entries; alphabetical order; capitalize only proper names; and separate key words by semicolon s) Building performance data; computer data acquisition; energy conservation in

commercial buildings; building envelope; mechanical systems; energy monitoring and

rontrol sy.qtem.q.

13. AVAILABILITY 14. NO. OF

Uni imited PRINTED PAGES

1 1 For Official Distribution. Do Not Release to NTIS

1 1 Order From Superintendent of Documents, U.S. Government Printing Office, Washington, D.C.

20402.

98

15. Price

Order From National Technical Information Service (NTIS), Springfield, VA. 22161 $9.50

USCOMM-DC 6043-P80
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