THE THERMAL PERFORMANCE OF FIXED AND VARIABLE SELECTIVE
TRANSMITTERS IN COMMERCIAL ARCHITECTURE
by
William A. Bartovics
B.A. Williams College, 1972
Williamstown, Massachusetts
M.A. ED. Stanford University, 1973
Stanford, California
Submitted in Partial Fulfillment
of the Requirement for the
Degree of
Master of Science In Architecture Studies
at the
Massachusetts Institute of Technology
February, 1984
c William A. Bartovics,
1984
The author hereby grants to M.I.T. permission to reproduce and to
distribute publicly copies of this thesis docuterlt in whole or in part.
Signature of Author
Tepartinnt
~o-F
Architecture
September 27, 1983
Certified by
Timothy E. Johnson
Principle
Thesis Supervisor
Accepted by
Julian Beinart, Chairman
Department Committee
On Graduate Students
MASSACHUSETTS NiTMSR~
OF TiCHNLOGY
MAR 11984
LI6RARIES
Research
Associate
THE THERMAL PERFORMANCE OF FIXED AND VARIABLE SELECTIVE
TRANSMITTERS IN COMMERCIAL ARCHITECTURE
BY
William A. Bartovics
Submitted to the Department of Architecture
on September 20, 1983
in partial fulfillment of the requirements
for the Degree of
Master of Science in
Architecture Studies
ABSTRACT
A parametric model is developed for use in evaluating the relative
thermal and lighting performance of a variety of existing and proposed
types of commercial glazing materials.
The glazing materials considered
are divided into three general categories: (a) traditional glass of both
clear and reflectorized types; (b) glazings with selective transmission
properties of the fixed variety which largely reflect the invisible
portion of the solar spectrum and contain only heat and which establish a
range of operating cost bases; and (c) newly proposed electro-chromic
glazing materials which variable transmit both the heat and daylight
portions of the solar spectrum.
This parametric model is based on
comparisons of total annual energy consumption for a typical perimeter
office in a multi-story office building situated in a variety of cities
in the continental U.S..areas of reasonably dense commercial development
within the continental U.S..
The results of the simulations showed a handsome potential savings,
over several standard glazing types, for selective transmitters of both
the fixed and switchable variety. Fixed transmitters were also excellent
performers,several configurations offering savings often only slightly
lower than the highest savings attained in the switchable group. The
switchable transmitter group contained glazings which produced the lowest
annual loads.
The primary reductions were made in cooling loads without
dramatic increases in lighting loads, but heating savings, resulting
primarily from glazing materials of high thermal resistance, proved to be
significant in cold climates.
Thesis Supervisor: Timothy Johnson
Principal Research Assistant, M.I.T.
ACKNCWLEDGEMENTS
Timothy Johnson
For the opportunity and contacts to
undertake this porject and
and
For
the
support, guidance
knowledge necessary to complete it.
Harvey Bryan
For suggesting the topic,
For valuable research help
materials and
For his daylighting experience.
and
The Polaroid Corp.
and
Their Employees:
John Bownan
Ginny Calloway
John Cary
Carl Chiulli
Bob Eckert
Sheryl Healy
Alice Holway
Frank Plankey
Ron Sahtjian
Bob Suleskv
For the funding, materials necessary
to carry out this project
in
prograrming,
assistance
For
equipnent use, Graphics design,
material properties,
For the clarity of thought and
guidance which each provided
in turn with a personal interest
from which I have benefitted
hugely, and for which I am
grateful.
Gordon Tully
For educating me in the Sunpulse methodology and
For guidance in its manipulation.
Ecos, Inc.
and
David DelPorto
For word-processing equipment and
time without which this
document could not have been
produced.
Wolfgang Rudorf
For architectural Illustrations,
Formatting of graphical design,
Layout assistance and for
unsurpassed nocturnal vigilance.
Doru Illiesiu
For editorial and graphical
assistance
Charles St.Clair
For assistance with prograning
solar correlation and integration
techniques.
Becky Bartovics
For her consistant support and
labor toward the production of
this thesis.
TABLE OF CONTENTS
PART 1
INTRODUCTION
p.
PART 2
SIMULATION SITES AND WEATHER DATA
p. 13
PART 3
SIMULATION PROGRAM & STRATEGY FOR SWITCHABLE GLAZING
p.
27
PART 4
ARCHITECTURAL CHARACTERISTICS & OCCUPANCY REQUIREMENTS
p.
37
PART 5
AUXILLIARY POWER SYSTEMS AND CONTROLS
p.
53
PART 6
OUTPUT ANALYSIS
p.
57
PART 7
CONCLUSIONS AND SUGGESTIONS FOR FURTHER WORK
p.
87
p.
93
APPENDIX B ASSUMED DIRECT/DIFFUSE SPLITS
p.
95
APPENDIX C CORRECTED WEATHER DATA
p.
97
APPENDIX D MODIFIED SUNPULSE ROUTINES
p. 113
APPENDIX E ENERGY BALANCE EQUATIONS
p. 115
APPENDIX A
TABLE OF RECOMMENDED AVERAGE MONTHLY DECLINATIONS
7
APPENDIX F
SIMULATION PROGRAM FLCW CHART
p. 117
APPENDIX G SIMULATION OUTPUTS
APPENDIX H ELECTRIC RATES FOR VARIOUS U.S.
p. 121
CITIES
p.
135
6
PART 1
INTRODUCTION
The increasing base cost of power and changes in rate
structures since 1973,
illumination
together with a general retreat from high
requirements,
have
regenerated
an
interest
in using
fenestration to lower energy consumption in commercial buildings.
With
the advent of new glazing technologies comes the potential of managing
the solar contribution to the energy required for comfortable working
conditions.
The
complicated
by the
process
buildings" coincides,
solar flux.
of
this
solar
internal gain schedule
management,
however,
is
which in "load dominated
for the most part, with the periods of maximum
The issue in commercial glazing strategies is not the usual
matter of maximizing heat gains and minimizing loses as has been the
basis of the approach to residential glazing.
structures,
rather,
The issue in commercial
is a question of supplying the required daylight,
without significantly adding to the already high heat gains which exist
during daytime occupied hours.
Traditionally, the reduction of cooling loads was considered to be
the principal target in glazing design strategies.
This attitude led to
the use of small aperture size and/or glass with very low transmission
characteristics in an effort to reduce solar heat gain as much as
The result of this approach was to increase the amount of
possible.
The 1981 SERI studies have shown that
purchased lighting energy.
lighting and cooling now demand equal amounts of energy.
Together they
comprise the largest consistent percent of the annual load in standard
offices.
In some climates,
however,
heating
loads during unoccupied
hours can also be significant contributors to total annual energy use.
The fact that heating loads occur primarily during unoccupied hours
makes
that category a difficult target for reduction through solar
management.
Lack of available storage media rather than inappropriate
glazing material is the source of this problem.
New glazing technology and an expanded repertoire of natural
lighting techniques have begun to offer the means of decreasing lighting
loads
without a concommitant
increase
in demand for cooling power.
These new technologies are based on a selective transmission of the
solar spectrum.
Generally these glass types are "tuned" to admit the
visible portion of the spectrun, while at the same time disposing of the
infra-red portions.
These materials can be divided into two classes:
those of fixed transmission characteristics, and those of dynamic transmission characteristics.
Of the dynamic varieties, electro-chromic mat-
erials provide the greatest control flexibility, thus lending themselves
most readily to simply applied control strategies.
tend to have moderate ranges in available sunlight,
In climates which
such as Boston,
fixed transmitters offer a great benefit from daylighting.
However,
glazing materials with controllable dynamic transmission characteristics
could reduce heating loads during unoccupied daytime hours.
time
lighting
loads
during
working
hours
could
be
At the same
substantially
reduced under both dim and bright conditions without suffering increased
cooling loads.
Both of these new materials offer great potential
benefits without the excessive heat gains usually associated with larger
window areas.
is quite clear that a
it
As a result of these possibilities,
general reduction in the quantity of commercial power consumption is
attainable.
of
existing
techniques
The relative benefits in power consumption for the variety
glazing
products
in the
face
is not yet clearly established.
of
Nor is
current
it
daylighting
yet clear what
might be the marginal benefit of glass possessing dynamic transmission
characteristics over these existing technologies.
In order to quantify the relative benefit of glass types which
either exist now or are imminently possible, it is necessary to compare
the impact on total power consumption of each example as a sum of the
simultaneous lighting, cooling and heating loads for a given commercial
archetype.
steps.
The process of developing such a model was done in two
First, sixteen simulation sites within the continental U.S. were
chosen and weather data constructed for each site.
The choice of sites
was based upon areas of reasonable commercial developnent and the expected annual climatic demands in each of the main categories of energy
consumption: lighting, cooling and heating.
This limit to the number of
simulations for each glazing type was set in order to a minimize the
output volume without sacrificing the national scale of the results.
A
representative group of six cities, three heating dominated cities and
three cooling dominated cities,
were chosen
pattern of each parametric comparison,
to illustrate
the load
but the simulation results for
all sixteen cities are included in Appendix G.
develop an appropriate parametric model.
The second step was to
The function of this model was
to establish a uniform method for testing each of the selected glazing
strategies against one another.
The model is based on a typical peri-
meter-zone office with standardized architectural characteristics and
patterns of use.
The remainder of this comparative study consists of a description
of each glazing type chosen for examination and a discussion of the
simulation results.
three groups.
The glazings chosen for comparison are divided into
The first group is made up of the traditional clear and
reflective types, and both single and double glazed configurations of
each are included.
selective
The second group is made up of four different
transmitters
of the fixed variety.
Four different "heat
mirrors" are examined in this group, and they include single, double and
triple
glazed
varieties.
The
third
group
is made
up of
five
electro-optic glazings (ELO 1 to 5) of different transmission ranges.
All glazings in this final group are double glazed units.
Tables 6.1
and 6.2 list the parameters for all glazings.
The comparisons are based on total annual power consumption,
but
the relative contributions of lighting, cooling and heating to the total
load for each glazing type are indicated.
glass area,
The impact
of changes in
azimuth, configuration of thermal mass and heating fuel on
the annual load are also identified.
In addition, the relative impact
of peak kilowatt charges per year are illustrated as equivalent KWH for
all comparisons.
The conversion of peak KW per year into equivalent IWH
was done by multiplying the sum of each month's peak load in KW by the
ratio of $6 per peak KW to $0.10 per KWH.
The assunption here is that
the ratio of peak charge to KWH charge should remain fairly consistent
from city to city even if the absolute rates do not.
appendix H shows a
listing of current KWH rates for various cities throughout the U.S. as
tabulated by the Energy Information Administration in Electric Power
Monthly,form 101, May 1983.
12
PART 2
SIMULATION SITES & WEATHER DATA
The number of simulation sites were restricted to the minimum
points necessary to bracket the different
in which significant commercial developnent
coterminous United States,
Particular attention was given to the northeast coastal
is to be found.
area
with the middle-atlantic
priority.
Washington,
climate types within the
Six
cities
states
and south
(Caribou, ME,
DC, Charleston,
Boston,
SC and Miami,
FL)
representing
MA,
New
second
York,
NY,
were picked from the
available data, as cities which might best illustrate the climatological
picture of the heavily developed eastern seaboard.
section of the country,
The mid-western
from the Appalachian mountains
through the
Mississippi River Valley was given three simulation sites; Madison, WI,
Nashville, TN,
and Columbia,
MO.
The upper plains states in the west
were generally overlooked because of the relatively
developnent,
but the cities of Fort Worth,
TX,
thin commercial
and Great Falls,
MN,
should give clear boundaries of performance at the southerly and
northerly extremes of this area.
The south-western states of Arizona
and New Mexico are simulated by Phoenix and Albuquerque respectively.
The extreme west and coastal states are bracketed by the cities of
Seattle, WA, Ely, NV,
and Santa Maria, CA.
Figure 2.1
shows the
FICM 2.1 The Continental Distribution Of Simulation Sites
distribution of the sixteen simulation sites chosen for this study.
The
climatological
factors
which
are
most
important
to
the
simulations are those which directly impact energy flows through glazing
materials, and through the
opaque materials which make up the remaining
portion of the weather wall in conmerical architecture.
The available
solar radiation together with the ambient outdoor tenperature are the
dominant climatological factors in the calculation of any architectural
energy balance.
As a result, the weather data for the simulations was
designed to account for these factors directly.
the
outdoor air
is
The moisture content of
also an extremely powerful variable
[Henderson,
S.T.,DAYLIGHT AND ITS SPECTRUM,(New York; American Elsevier Publishing
(b., Inc.,1970) pp.23-34].
Although hunidity is not directly accounted
for as an independent data input, there is an implicit accounting for
its impact through variations
inputs.
Both
radiation
and
in both the radiation and temperature
temperature
vary
according
to
daily
atmospheric clearness.
The weather data used for each simulation is a modified version of
the approach developed by Gordon Tully in his "Sunpulse"
simulation
program for TI-59 calculators [Tully, Gordon, "The 'Sun-Pulse'
concept -
A Simple Approach to Insolation Data" (Newark, Delaware, Proceedings of
the
5th National
Passive Solar conference,
1980)].
The "Sunpulse"
program compresses hourly Typical Meteorological Year ('IMY)
solar gain
and daily temperature data into a small number of mathmatically variable
The weather data is designed to supply
inputs for each month.
insolation and temperature data for seven representative days per month.
The "Sunpulse" data system was chosen because it
hourly measurements
supplied
by TMY data
is based on the real
rather
than
mathmatical
approximations, and because its "seven day per month" simulation format
makes it extremely compatible with the ordinary weekly commercial
schedule.
length of
The error, due to intermittent holidays and variations in the
each
month,
is therefore minimized
in comparison
with
alternative systems such as the "Bin Data" approach which calls for a
seven day simulation
for each two month period.
Also,
"Sunpulse",
generated according to the sinusoidal distribution of sunshine over the
given day, allows the flexibility to more realistically represent the
variable
conditions
which
normally
occur
during
any
given
day.
Simulations which are based on average data are not variable enough to
realistically model the demand on the lighting system, nor the resultant
impact on heating and cooling loads due to the heat content of the electric lights.
The typical hourly meteorological data is reduced, by "Sunpulse" to
only 24 numbers per month: IT, IM, IK and 7 CLRNS, 7 temperature average
and 7 temperature range numbers. The outdoor temperatures are compressed
by the monthly derivation of a 24 hour average temperature and an
average daily temperature range for each month.
monthly average temperature and range,
In addition to a single
"Sunpulse" supplies an average
daily temperature and range for each day of the month with an associated
CLRNS.
An average daily temperature and range could be derived for each
of the seven representative CLRNS inputs.
Each of the seven simulated
days per month in this application, therefore, were given a specific and
unique average temperature and range.
The temperatures for each day are
also sinusoidally distributed according to the hour angle relative to
noon, of the hour under consideration.
They are, however,
distributed
over a full 24 hours with the minimum and maximum tempertures occurring
at 2h00 and 14h00,
respectively, so that the maximum temperature minus
the minimum equals the temperature range for that day (see figure 2.2).
The solar gains are compressed by the monthly derivation of 1.) a
greatest hourly gain in Btu/hr (called IM for insolation maximum), 2.) a
greatest average daily gain in Btu/day (called IT for insolation total
and 3.)
seven "clearness" numbers (CLRNS)
which represent daily in-
solation totals for each of the seven representative days as a percent
of the clearest day in each month.
square foot of receiving surface area.
Both IM and IT are in units per
In addition to these nine basic
inputs, there is an adjustment variable (IK)which represents the
TDPERATRE DISTRIJIOIMS
D
BOSTON
MARCH
4
E
T1P
G
R
E 3&E
S 34-TAY.x36.4
F
8
9 It911 12 13 141516S 17 18 19 29 21 22 23 24 1 2
3 4
5
6 7
8
10M OF THE DAY
FIGURE 2.2 The Sinusoidal Distribution Of Avera
DailS Teperature AndRag
maximum percent deviation above the given CLRNS which will occur on the
specific average day during the truely typical month.
variations
in
f it
between the assigned
even clearness
IK accounts for
numbers and the
actually measured total daily insolation [Tully, Gordon,"The 'Sun-pulse'
Concept- A Simple Approach to Insolation Data", pp.208-209].
'Ihe insol-
ation data are distributed sinusoidally from sunrise to sunset so that
IM is the Btu/hr at noon, and IT is the total Btu/day (see Figure 2.3)
Two major modifications of the original "Sunpulse" approach were
undertaken for the sake of this simulation model.
the
data
itself, and
the other
insolation data calculated
sur face
f irst
latitudinally
reflection
(8%)
for ground reflectance.
involves
its
involves
'Ihe first
application.
The base
for each city was originally generated on a
tilted
toward
the south,
and was
corrected
from the outermost surface of the glass,
for
but not
Also, the application of each clearness percent
assumed days of uniform clearness throughout,
which generates the
Q.EM DAY MLu.SE
concentric
mooth
curves
shown in Figure 2.4, rather
225t
than days which are made up
~/
E 1254
1
71
9
5/ 8/ 9
4
more realistically of variable conditions.
it
ii 412 13 14 15 16 V7 18 18 29
For any
individual day, the total
HMR OFTHEDAY
I
insolation is given by the
F: (.RNS . 1.
following
formula:
FIGLE 2.3 The Sinusoidal Distribution Of IT And
IMOn A Clear Da In Boston
(CLRNS)
(1+IK)
(CLRNS))],
and
IT
[sin(PI
the ampli-
tude of the curve at noon
(CIM)
is
given
by:
IM (CLRNS) (1+IK (sin)
(PI(CLRNS)).
Because the purpose of
this simulation was to calculate
a umrFaM AVERAE CLENESS
stPiSE DAYS
loads
for
offices of any orientation,
MOMt
T 225+
hourly
U 294t.
it
was necessary to cal-
culate the
insolation
in-
cluding ground reflectance,
incident on surfaces other
T
4
6
5
7
8
9
1
1=2 13 14 15 16
17 18
19 29
than those which are latit-
0.R OF TIC DAY
IT
Fm: CieS
.a
*tM
9.9
CLRS s 9.7
*.N9. 4
Q
CU6
udinally tilted toward the
south.
It was therefore
9.1
necessary to drop IT and IM
FICURE 2.4 The Sinusoidal Distribution Of Uniform
March Clearnss In Boston
onto a horizontal surface,
X7\01
7-
C74Iz
Z4A&7V
e
-b
-
-
Jv20340
A-g:r
w
do
?w
-A230V
M
GV A
A
3 tit
A(1=
0
8 A 4' b
AA4ZCA.2ca
44fMZAJ
Ad
ABJGo47c
X
4c ,acvecj
FIGURE 2.5 Glass Transmission & Absorption Vs. Angle Of Incidence(from Windows
And Envirmwent Pilkington Environmental Advisors Service, i96)
where
insolation curves
could be generated
and then
rotated
to any
surface azimuth or inclination through an application of the standard
correlation techniques shown in Appendix A.
The first step in dropping
the insolation data onto a horizontal surface was to restore the first
surface reflection losses previously subtracted from both IM and IT on
the tilted surface.
This correction was necessary because the trans-
mission figures for each of the glazing materials to be studied already
accounted for this loss.
The graph in Figure 2.5 shows the percent of
energy lost due to first reflection at various angles of incidence.
Because the receiving surface is at the latitudinal tilt, the incident
angles which would be involved fall entirely within the minimum loss
regime of 8%.
Therefore,
both IM and IT in each case could simply be
divided by 0.92 in order to reinstate the reflection losses.
The IM
numbers were easy to correct to the horizontal plane because in each
case a simple 85/15 % split between beam and diffuse light had
originally been assumed in raising the brightest hour in each month from
the horizontal to the tilted surface.
The correction formula used for IM was derived from the formula for
the ratio of radiation on the tilted plane (RBIM)to that on a horizontal
plane [Duffie, J. and W. Beckman, SOLAR ENGINEERING OF THERMAL PROCESSES
(New York: John Wiley & Sons,
1980),
p.
85,
equation 2'15'6].
The
formula is as follows:
HIM = IM/ (0.85 RBIM +0.15)
where:
HIM = the horizontal value of IM
IM = the tilted value of IM at noon divided by
0.92 to restore assumed reflection loss
0.85 = the assumed % contribution of beam sunlight
RBIM = the ratio of beam sunlight on the tilted
surface to that on a horizontal surface
0.15 = the assumed % contribution of diffuse light
from an isotropic skydome.
Furthermore,
is
since IM is given for a latitudinally tilted surface,
and
assumed to occur at noon, the standard formula for RIBM reduces to
the following formula:[Duffie,J,
THERMAL PROCESSES,
p.
16,
and W. Beckman,
equation 1'7'2; p.
12,
SOLAR ENGINEERING OF
table l'6'1; p.11,
equation 1'61]
cos(Dec)/cos(Lat)cos(Dec) + sin(Lat)sin(Dec)
where:
Dec = Declination calculated for the best average
day of each month according to the standard
formula (See Appendix A)
Lat = latitude in degrees of each city considered.
The correction for IT on the horizontal proved to be considerably
more involved.
"Sunpulse" data was brought up to the latitudinal tilt
on an hourly basis before the daily totals were summed, and each hour's
insolation was assigned a direct-diffuse split on a linear scale by
Since the assumed
ratio to the brightest hour in the given time slot.
direct-diffuse split as well as the value of each hour's insolation were
not reported, a method to drop the daily insolation total back onto the
horizontal surface had to be developed.
hour by hour,
Clearly, a recompilation of IT,
according to the original "Sunpulse" method,
on the
horizontal, would be best, but limitations of time and funds obviated
this option.
Instead, an itterative process was chosen which calculated
and summed the integrated hourly increments of IT on a horizontal
surface by using the average zenith angle
[Duffie,J and W. Beckman,
SOLAR ENGINEERING OF THERMAL PROCESSES, p. 13. equation l'6*4].
CosZenith Angle = cos(Dec)cos(Lat)cos(HourAngle +
sin (Dec) sin (Lat)
The summed value for each hour was used to establish the direct-diffuse
split for that hour according to the following rules [Tully, Gordon,
"The
'Sun-Pulse'
concept-
A Simple
Approach
to
Insolation
Data",
pp.206-210]:
1.) if the cosine of the zenith angle (CZNGL)<
0.12, then the direct/diffuse split = 0.0/1.0
2.) if 0.12 < CZNGL< 0.42, then the direct/diffuse
split = from 0.25/0.75 to 0.70/0.30 in steps of
0.05
3.) if CZNGL > 0.42, then the direct/diffuse split
= 0.40/0.60 to 0.85/0.15 in steps of 0.05.
These calculations were carried out for each step of 0.05 until the
average daily insolation on the horizontal surface
(derived from the
corrected IT and the 7 original clearness percents) most closely matched
the average daily horizontal insolation as tabulated by Doug Balcomb
[Johnson,Timothy, SOLAR ARCHITECTURE; THE DIRECT GAIN APPROACH (New
York,
McGraw-Hill
Publishing Co.,
1981),pp.182-199].
A Table of the
chosen average daily direct-diffuse split is found in Appendix B.
The formulae used to convert IT are the same as those referenced for the
IM conversions.
horizontal
With both IM and IT so reconstituted for incidence on a
surface,
the standard
"Sunpulse"
formula
could
again be
applied to generate the curve over the total gain per square foot of
horizontal surface.
The net energy for any hour was then derived by
integration under the curve for that hour.
The general formula for this
integration is:
QSH = -IM(cos)W 2 + IM (cos)W
where:
QSH = total incident energy on the horizontal for
the hour
IM = the amplitude at noon of the sinusoidal
sunpulse curve
W = the hour angle of the hour considered
W2 = the hour angle of the hour considered + 2
The integrated hourly total on the horizontal could then be compared to
a
calculated
extraterrestrial
value for the same hour,
and
thereby
assigned a direct-diffuse split in preparation for bringing the gain
into its proper position of azimuth and tilt.
The direct-diffuse split
was established according to the correlation formulae proposed by Orgill
and
Hollands
(1977) [DuffieJ.
and W. Beckman,
SOLAR
THERMAL PROCESSES, P. 71, EQUATION 2'10*1].
1.0 - 0.249Kt
Id = 1.557 - 1.84Kt
for Kt<0.35
for 0.35<Kt<0.75
I
for Kt>0.75
0.177
Where:
Id = % diffuse light
-I-
Kt = Clearness difined as the ratio of terrestrial
to extraterrestrial insolation on the
horizontal
ENGINEERING OF
In addition to these correlation formulae, corrections for low angles of
incidence were added in order to prevent the overestimation of direct
light during the extremes of the solar day.
This addition was necessary
because, due to the use of one average solar day length per month, arbitrarily high sunrise and sunset hour gains were occassionally calculated relative to the actual extraterrestrial sunlight available.
situation, under the original correlation formulae,
This
would have led to
the overestimation of the direct component, and therefore astronomically
high incident energy on the office skin.
simply states that if
This additional correction
the ratio of terrestrial to extraterrestrial
is
greater than or equal to 0.9, then the direct/diffuse split is to be
Cosines of less than 0.12
determined by the cosine of the zenith angle.
result in a 100% diffuse condition and cosines of 0.12 to 0.42 inclusive
result in a 30% diffuse condition and,
finally for cosines of greater
than 0.42 the diffuse component is assumed to be only 15%.
The incident
energy on the architectural fascade was then calculated using the
formula for calculating the ratio of total insolation on a tilted
surface
to that on the horizontal surface
including a component for
ground reflection proposed by Liu and Jordon (1963) [Duffie,J.,
Beckman,
SOLAR ENGINEERING OF THERMAL PROCESSES,
p. 86, equation 2*15'8]
R = Ib Rb + Id (1 + cos(tilt) + (1 - cos(tilt) P
I
I
2
2
where:
R = Total radiation on a tilted surface
Total radiation on a horizontal surface
Ib = % Beam Sunlight
Rb = Beam radiation on a tilted surface
Beam radiation on a horizontal surface
Id = % diffuse light
P = Ground reflectance
and W.
A listing of the corrected IM and IT inputs is given in Appendix C.
The second modification added to the "Sunpulse" format was a
mechanism for establishing frontal cloud cover, which divides any given
day of uniform average clearness
(those falling between 20% and 80%)
into two parts: one completely clear, and the other more densely cloudy
than the day-long average.
The combination of these two parts yields a
total daily energy which is equal to the energy available under uniformly cloudy conditions.
The solar day for this case was assumed to be
made up of two separate gain curves, the sum of whose enclosed area was
set equal to the area under the uniformly cloudy curve.
The hour of the
frontal switch (FH) was arbitrarily established by the solving of
integration:
CFHNGL = (IT(CIM)/IM(PI)/ALSD) -
(IM-CFIM)/(CFIM-IM)
where:
CFHNGL = the Cosine of the hour angle of the hour of
frontal switch
IT = Total insolation on a clear day
CIM = the amplitude of a uniformly cloudy day (CIM =
IM(CLRNS) (1+IK)sin(PI)CLRNS
CFIM = the amplitude of the extra cloudy portion of
the day CFIM = IM(CLRNS) [1-(IK)4sin(PI)CLRNS]
ALSD = the average length of the solar day IT(PI)/2IM
The frontal hour, then was established by one of two different formulae
depending upon whether the clear portion of the day is to be in the
morning or the afternoon.
The formaule are as follows:
Sunrise hour + Arc Cos (CFHNGL) PI/ALSD
or
Sunset hour - Arc Cos (CFHNGL) PI/ALSD
where:
Sunrise = 12 - ALSD/2
Sunset = 12 + ALSD/2
PI/ALSD= the conversion from hour angle to hour
OFVMRIAU.L a.E~E
SIFJ.SE DAYS
It should be noted, that
the amplitude of the extra
cloudy portion of the day
also
(CFIM) was
somewhat
S 7-
arbitrarily established to
F
function optimally with the
data for the 16 chosen sim-
Its broad
ulation sites.
applicability to other cities,
therefore
limited.
may
1
HOUR OFTHE DAY
IT
m
12smtifor
s
is
345
7s
2
Cnditions
FIGLE 2.6 The Modified Sun-Puise Curve For
Variable Clearness Of Average 0.4
be
If an IK number
of sufficient size is input into the equation for CFIM, a negative solar
flux results.
The formula should be adequately applicable to any of the
sites listed in the original "Sunpulse" literature, although in a very
few cases it may produce cloudy hours with impossibly small solar gains.
Figure 2.6 shows the comparison between the original and the modified
curves,
both of which enclose equal area.
Finally, a random number
generator was used to set a switch which decided between either a clear
morning with a cloudy afternoon, or conversely, a cloudy morning and a
clear afternoon.
The purpose of this change was to create variable
lighting conditions, through a given day in order to more realistically
simulate conditons which would affect the interior lighting loads in the
modeled office.
Refer to Appendix D for a full listing of the modified
"Sunpulse" routines in Machine Basic.
26
PART 3
SIMULATION PROGRAM AND STRATEGY FOR SWITCHABLE GLAZING
The main simulation program combines calculated hourly weather data
with a given set of architectural parameters, and applies them through a
variety of glazing strategies. The temperatures in a four node thermal
network,
and the auxilliary lighting loads for three separate zones are
then calculated.
Heating,
cooling
generate monthly and annual totals.
to
and lighting loads are summed
Itterative routines are also in-
stalled to record annual, seasonal and monthly peaks.
The annual total
energy consumption in combination with the appropriate peak loads can be
used to generate an estimate of the total operating cost per unit area of
glazing installed.
The four node thermal network used by the simulation is shown in
Figure 3.1.
The four nodes each assume a uniform distribution of energy
through the surfaces and elements which they represent since the sunlight
is diffused.
Also, the equations defining the energy flows presuppose a
consistent time step of one hour.
Should either of these conditions
become altered, the equations will no longer provide valid represenations
of the thermal network in the office bay.
The air temperature node #1 (TA)
has had a
capacitance of 3 Btu/OF
attached to it in order to account for the storage capacity of the office
furniture, and of the light weight gypsum board on the walls.
The
techniques for distribution of solar energy passing through the window,
Heat of
liahts
Heat of equipment
Sensible Heat of Occucants
To
= Outdoor
TA
=
Indoor air temDerature
=
Rug temperature
TS1
TS2
UAW
f
UAR
US
CR
CS
air temperature
Temperature of top 2" of Slab
= Temperature of bottom 2" of Slab
=
= Total conductance of weather wall and infiltration Btu/hr OF
= Total surface film conductance of Ruc (Rug area x H rug) Btu/hr 0F
= Total conductance of Pug (Rug area x U rug) Btu/hr OF
0
= Total conductance of Slab (Slab area x U slab) Btu/hr F
= Heat capacity of air (for sheetrock and furniture) Btu/ OF
= Heat capacity of rug Btu/ OF
= Heat capacity of slab Btu/ OF
= Ventilation air
FIGURE 3.1 The Four Node Thermal Network
described below, and the assumed reflectivities of the ceiling and walls,
80%
and
70%
respectively,
assure
a
diffusing
thorough
and
even
This even distribution tends to
distribution of incoming solar energy.
minimize the error of a single node system.
There will be stratification of hot air at the ceiling to some
degree, particularly with the given 10' ceiling height, which might lead
but the ventilation
to some distortion in the real air temperatures,
system, which operates continuously, might be assumed to minimize this
potential source of error.
Furthermore, if the ceiling is uniformly
covered with an accoustical material,
then there will be little surface
capacitance in this area to trap stratified heat.
As long as the air is
kept moving, then, the constant mixing should make the one node approach
accurate for the air temperature.
The heating, cooling and lighting
energy supplied by the mechanical systems, finally, is attached directly
to the air temperature and capacitance.
Therefore, these systems can
only heat the remaining three nodes in the network indirectly by
convection.
The node assigned to the floor covering (TR) also assumes an even
distribution of the available solar energy, and an even thermal contact
with the room air and its associated elements.
conductance,
The surface film
capacitance and U value associated with the floor covering
determine the nature of the thermal interaction between the floor
covering and the adjacent nodes in the air above and slab below.
surface
A
film conductance of 1.5 Btu/OF was chosen to account for the
combined effects of convection and radiation from the floor surface.
The
capacitance and U values of the floor surface vary according to the type
of architectural finish chosen.
In general, the capacitance of the
assumed covering is minimal.
The program has therefore been designed to
accept such a range of variation in the parameters which define the floor
covering.
Nodes 3 (TS1)
and 4 (TS2) are devoted to calculating the uniformly
distributed temperatures at two levels within the slab.
Because of the
natural tendency toward an exponential temperature gradient through the
slab, two nodes are devoted to the 4 inch slab floor in order to
approximate this distribution.
The floor slab is assumed to be thermally
supported from underneath by a perfect insulator.
This assumption is
reasonable because there will generally be an insulative accoustical
treatment below each floor slab, and below that,
another heated space.
Appendix E lists the energy balance equations for each node, and outlines
their algebraic solution which is contained in the main program.
main program is described by the flow charts in Appendix F.
The
Each of the
program sections illustrated in Appendix F is described in detail below.
The strategy designed to trigger the switch of electro-optic
glazing materials was formulated
under the assumptions
that:
a)
the
system should be automatic, and b) the controls should be simple enough
to
incur
minimal
additional
cost.
The
controls
consist
of
two
thermostats, a light level sensor and an electronic outdoor thermometer.
The thermostats measure temperatures in the air and on the floor surface.
These two controls, like the thermal network, are based on the assumption
that an even and uniform distribution of solar and purchased
energy
throughout the air, its associated room elements and the floor surface is
prevalent.
The thermostat in the air records the temperature and
contains the cooling set points (730/800).
The floor surface thermostat
monitors the floor surface temperature.
The light level meter measures
the light level at the back of the office.
The signals from each of the
sensors, together with the outdoor temperature, determine when the
electro-optic glass should be switched to its "dark", less transmissive,
state.
The essential intent of the switching strategy is that daylighting
The glazing material will only be
concerns are of first priority.
switched during working hours if minimun light levels will continue to be
Furthermore, on dim days (which require electric lighting) the
met.
glazing is held in the clear state in order to avoid intensifying the
gloom of dim external conditions.
Figure 3.2 shows the relative merit of
switching only if full daylighting can still be accomplished after the
switch as compared to switching regardless of daylighting concerns (for
64 sq.ft. of glass in a south facing office).
The second priority to be
determined is whether the office is experiencing summer or winter conditions.
This distinction in "thermal mode"
winter heating conditions,
it
is -necessary because under
is advisable to keep whatever mass is in
the office as warm as possible, without overheating the air.
summer cooling conditions, however,
During
it would be better to keep the mass
as cool as possible by rejecting as much light and heat as is possible.
Generally, therefore, the glazing is kept in the "bright" state as much
as possible in the winter, and in the "dark" state as much as possible in
the summer.
The determination of winter versus summer conditions is performed
hourly on the basis of a calculated balance point tenperature, based on
the nighttime heating thermostat and modified by the amount of storage
capacity in the office.
This modified balance point tenperature is then
SWITCH WITHOT
AYLTGHTING PRIORITY
SWITCH WITH DAYLGHTING PRIORITY
PEAK KW/YR IN EQUIVALENT KWH
BOSTON
25.
2000--
15W -
50W -
ELD--
II
ED-2
aED-3
ELD-1
EU-4
ELD-2
E0D-3
I"!
ED-4
0.0-5
PHOENIX
MADISON
I7W
a.0-i
0.0-2
0.0-3
0.0-4
W.-5
SEATTLE
IiI
0.D-i
0.D-2
0.03
0.D-4
UD-5
0.0-1
a.0-2
0.0-3
La.-
F.0-4 W
-5
FT. WORT H
U
FIGLE 3.2 Switching Stategies For Glazing With &Without Daglighting Priorits
0.03
0.0-'
XD-5
compared to the outdoor temperature.
If it is greater than the outdoor
temperature in that hour, winter conditions are assumed; if the balance
point is the lesser, then summer conditions are assumed for that hour.
The formula for the modified balance point temperature is:
TB = THEATN -[(QS+IGN)/(UAW+CA)]-[(.6XQSXH/UAR +
CR)/CS]
where:
THEATN = the nighttime thermostat setting
= total solar gain for the hour
QS
= total internal gain for the hour
IGN
= total heat loss coefficient (UA) for the
UAW
office including infiltration
= heat capacity of the sheet rock and
CA
furniture in the office attached to the
air temperature
= the percent of total solar gain
0.6
distributed to the floor surface
= heat capacity of floor covering
CR
= heat transfer rate of floor covering x
UAR
area
= heat capacity of floor slab under floor
CS
covering
Since the formula is recalculated hourly, it allows an interfingering of
surmer and winter conditions through the swing seasons of spring and
fall, but remains quite consistently in one mode or the other during the
true winter and summer seasons.
It is also objective enough to accept
different floor finishes of different heat capacities and U values,
which bring the floor slab into differing degrees of involvement with
the thermal swings of the office.
Under winter conditions, the glazing is assumed to be in the clear
(bright) state until either the air temperature has risen to the cooling
set point (730 when occupied and 800 when not) or until the floor
covering rises to 1100 F.
In many climates,
the second thermostat in
the floor covering is not necessary as the floor surface never arrives
at 1100 before the air temperature arrives at the cooling set point.
It
is only in clear, sunny, hot cities such as Phoenix, that such a control
appears truely necessary, and in these climates, it
is only of critical
importance with floor coverings that have small U values and capacitance
such as rugs.
Because a rug is the most commonly used floor covering in
commercial buildings, and since the base comparisons are all made with a
rug
floored office,
cases.
this thermostat was consistently applied to all
In the winter, each hour's energy balance is calculated with the
glazing "bright",
and then the internal air temperature is compared to
the cooling set point.
If the air temperature is above this point, and
if daylighting can still be accomplished in the "dark" state, according
to the lighting level measured in the rear of the office,
then the
glazing is switched "dark" and that hour's energy balance is recalculated
in this state before the appropriate loads are recorded.
This
recalculation of the "previous" hour assumes that the anticipation of
the thermostat would trigger the switch during the hour under consideration, and that the recalculation of the whole hour is more accurate
than assuming that overheating is allowed for a full hour before the
switch occurs.
If on the other hand, summer conditions have been determined, then
the glazing is assumed to be switched to the "dark" state at all times
except during working hours when the "bright" state is either necessary
to accomplish daylighting, or when it
supplementary lighting.
is dim enough outside to require
During non-working hours,
the glazing is always "dark".
in the summer,
then
This mechanism is based on the idea that
only the energy which is absolutely necessary for lighting should be
admitted in the first place, since excess sunlight can only contribute
to the cooling loads during this season.
The additional savings produced by this seasonal variation in
switching strategy as compared to one which operates exclusively on the
basis of air temperature is quite small.
if
of controls,
warranted.
It
The extra complexity and cost
the switch were to be fully automatic,
would not be
is conceivable that the seasonal switch on/off strategy
could be done manually with both the dwell and anticipation being established over a short period of trial and error in a real office.
The
essential purpose of the given strategy was to provide one which would
be objective enough to function equally well in all the cities to be
simulated in this study, and to establish, as effectively as possible,
the upper limit to the savings for the two step pattern of switchability
(on-off) which was proposed.
PART 4
ARCHITECTURAL CHARACTERISTICS AND OCCUPANCY REQUIREMENTS
The architectural aspects of the parametric model were pared down
to those concerned with a single representative perimeter office bay
with a single exposure.
The office is seen as the smallest heating,
cooling and lighting unit within a perimeter core commercial building
prototype of undefined height.
This approach was taken because core
loads are constant and neither affect nor are affected by the loads
experienced
in adjacent offices.
also assumed that the energy
is
It
demand implications of any given glazing strategy will be contained
entirely within the attached office space.
it
is
This assuntion implies that
not necessary to consider the loads of an entire building,
containing many such office units,
in order to establish the relative
benefit of one glazing strategy over another in terms of energy use per
square foot of glass.
The office used to compare glazing strategies in all simulations is
rectangular in plan with 12 feet of width along the weather wall, a 16
foot depth and a 10 foot ceiling height.
The walls, floor and ceiling
are considered to be adiabatic with regard to adjacent spaces.
office is daylit from one side only,
The
and the glazings are generally
defined as wall to wall strip windows of varying heights.
shows the basic office bay in plan and section.
Figure 4.1
These dimensions were
rnu
FIGURE 4.1 The Gerric Perimeter Office: Plan And Section
chosen
in
because
part
they
are
perimeter/core office configurations.
generally
representative
of
The depth of 16 feet, however,
because such a
was chosen primarily because of daylighting concerns,
depth poses no serious problem with regard to either the penetration or
level of light, when using light shelves or reflectorized louvers for
the distribution of light [Rosen, James, "NATURAL DAYLIGHTING AND ENERGY
CONSERVATION: INNOVATIVE SOLUTIONS FOR OFFICE BUILDINGS, Masters Thesis(
Cambridge,
Ma.,
Architecture,
Massachusetts
1982),
Institute of Technology,
since
Finally,
p. 64].
Department of
a relatively
even
the solar energy is
distribution of light is feasible at this depth,
also evenly distributed by reflection and diffusion from the louvers to
the various room elements.
The office can be faced in any direction because of the flexibility
built into the solar calculation subroutine (south at 00,
north at 1800,
west at 900,
However,
any given simulation can
consider only one orientation at a time.
Any office around the
perimeter
examined,
of
and east at 2700 ).
the
given
commercial
structure
can
be
individually
except those occupying a corner position, with walls facing
two orientations at once. By so doing, it is possible to establish, with
a high degree of clarity and accuracy, the impact of orientation on the
relative benefit of the glazing strategies examined.
The interior finishes were designed to represent customary patterns
of color and material type.
treatment which was assumed
The ceiling was given an accoustical
to be 80% reflective
absorptive to sound at middle frequencies.
to light,
and 90%
This treatment also provided
the conceptual function of isolating the office below from any thermal
impact from the energy flows in the floor slab of the office above.
The
walls were assumed to be 5/8 inch gypsum board, and a capacitance of 3
Btu/ 0 F was attached to the room air to account for its mass effect.
The
sunlight is well enough distributed, and the gypsum board is thin enough
to cause almost no thermal inertia and thus,
one can assume that the
temperatures of the air and dry wall will swing together.
This configuration
painted with a finish of 70% matt reflectivity.
represents an off-white,
flat finish paint, and although bright white
(80% reflectivity) would enhance the daylight
space,
The walls are
levels throughout
the
the former was chosen in order to keep the finishes on the
conservative side of what is ordinarily found in contemporary office
spaces.
This
issue
is
implicitly
calculations and is therefore,
in
the
daylighting
like the basic dimensions of the office,
a difficult parameter to change easily.
features are sufficiently
included
However,
common configurations
these architectural
to be valuable,
and
changes to them are small in their impact on the value of any given
glazing strategy.
The floor was treated as an area where easy parametric changes
might be valuable.
The reflectivity of the floor to daylight was fixed
permanently at 40%, but the type of floor finish used over the concrete
slab may be easily modified in terms of the thermal mass and its
resistence to heat flows in and out of the slab below.
ordinarily found in office spaces,
assuming a rug over the slab.
capacitance
were
5:
THE
SECOND
the base simulations were all run
The U value of the rug, and its thermal
established by experience gained
Building V [Johnson,Timothy E.,
YEAR'S
Architecture, 1979)p.58].
Because rugs are
from MIT's
Solar
and Edward Quinlan, "MIT SOLAR BUILDING
PERFORMANCE"(Cambridge,Ma.,MIT
Department
The application of the rug significantly
of
:E:: RUG COVERED SLAB
TILE COVERED SLAB
PEAK K/YR IN EQUIVALENT KWH
T
0
A
L
COOLING CLIMATES
00-
EATING CLIMTES
300 --
K
W
H 200. -
Y
R
V WSTON
MIADISON
SEATTLE
MIMI
PNOIX FT. WORTH
FIGURE 4.2 Total Annual Loads With Rug Vs. Tile Covered Slab
AssuMing Clear-DG
damps the interaction of the massive concrete floor, though it does not
entirely eliminate its impact.
It is possible to largely eliminate the
damping which resulted from the rug by substituting vinyl tiles.
The
tiles had a noticeable impact on the participation of the floor slab in
the thermal swings experience by the office,
particularly in heating
climates due to their increased U vlaue of 20 Btuh/ 0 F ft2 [ASHRAE
HANDBOOK AND PRODUCT DIRECTORY;
Inc.,
1981) p. 26'10, Table 13].
1981 FUNDAMENTALS
(New York,
ASHRAE
Figure 4.2 shows the relative impact
of a rug versus tile floor for south-facing offices with 64 sq.ft. of
double glazing in representative cities.
The tiles were assuned to
retain a 40% reflectivity to light, but the potential qualitative
problem of specular reflections from their surface was not considered.
Window sizes were also easily varied, although the implications of
glass area with regard to daylight distribution and the assumed electric
lighting controls (described in detail below) have not been thoroughly
tested.
The ordinary office window is on the order of four feet in
height (48 sq.
ft.) but this area is
lighting levels on dim days.
inadequate to meet the minimun
Figure 4.3 illustrates the differences in
total loads for a south facing rug floored office with strip windows of
48, 64 and 72 sq.ft. respectively, as marked.
It was decided,therefore,
to increase the glazing area in order to accomplish full daylighting on
average overcast days (350 fc),
assuming a visible transmission of 81%,
and an effective distribution of daylight into the office.
This step
was taken in order to illustrate the point that a reduction of window
size for the sake of smaller cooling loads is not necessarily the best
approach, and also to more completely evaluate the relative benefits of
the more recent glazing materials under optimum daylighting conditions
[Rosen, James "Natural Daylignting and Energy Conservation:
Solutions for Office Buildings",
creased window area,
added.
pp.
11-20].
Innovative
In addition to the in-
a new feature for daylight distribution was also
This feature consists of replacement window blinds which are
both inverted,
in comparison to ordinary blinds, and reflectorized on
the top surfaces
in order to provide more even distribution,
deeper penetration of daylight into the office.
and a
Figure 4.4 illustrates
the configuration of both the older type and the assumed type of blinds.
The illustration in figure 4.5 compares the daylight distribution under
cloudy day conditions which results from an untreated window to one
which employs the assuned system.
From these comparisons,
it
is clear
that the relative uniformity of distribution which results from these
TOTAL ANJAL LOAD IN KWH
PEAK K/YR IN EQUIVALENT K
BOS
T
0
T
A
L
K
0
H
E
Yi
Alo
-
qf
9l
f
q
f
9
CLEAM G
EL-5
t/LT-TG
PHOENIX
mem
32*
288w
Im
2564
*I -
CLEmAI
RtT-TG
ELO-4
I-
I miii
CLEDG
CEAR G
FICLE 4.3 Total Annual Loads Lkder Various Window Amas
&
I
lWLT-Tc
Hlt/LT-TC
I *I
I
I
E-5
ELW-5
FIGRE 4.4 Old Vs. New Stale Window Blinds For Daglight Distribution
blinds
is
requisite
daylighting.
contrast
to
the
effective
use
of
solar
energy
for
The high lighting levels near the window and the great
between
levels,
front
to
rear,
(200 to
30
fc)
in the
undistributed condition will cause qualitative as well as quantitative
problems within the office.
Qualitative issues such as contrast glare,
due to the excessive brightness at the window,
working conditions and occupant discomfort.
will cause adverse
As a result quantitative
issues will then receive a negative impact due to a need for increased
illumination levels at the rear of the office in order to overcome the
contrast glare.
These increased lighting levels can only be accom-
plished by turning on at least some if not all the interior lights.
result, then,
is an increased lighting cost.
The
Furthermore, uneven dis-
tribution of sunlight can, even with new glass technologies, create "hot
spots" near the windows.
This uneven distribution of heat,
together
with the additional heat from purchased lighting can dramatically affect
DAYLIGHT DISTRIJTION WITH REFLECTIVE BLINDS
DAYLIGHT DISTRIBUTION WITHOUT BLINDS
HORIZONTAL
SKY ILLUMINATION
1214 Fc
-
10-
0BE I
MK 2
0
0L
FIGLE 4.5 Daylight Distributions With And Without Reflective Blirs
the need for air conditioning and hence the total energy cost of the
office.
It
is therefore assumed that distributive blinds are installed
on all windows as a prerequisite to changes in glazing strategy.
window area was established
Station protractor
in accordance
calculation
techniques,
The
with the British Research
which,
together
with the
minimum required illumination of 30 foot candles in the back of the
established the base window area to be 64 square feet.
room,
represents a
12 foot wide strip window,
This area
5.7 feet in
approximately
height.
The occupancy schedule was structured to maintain a normal work
week for 52 weeks per year.
There were no provisions made for regular
short term breaks in the ordinary commercial schedule such as vacations
or national holidays.
However,
since any given year
is
relatively
balanced with breaks, and since vacation days generally comprise no more
T
0 406T
A
R
L 3WP
N.
L y
-.
A
U
H
---. BOSTON
.
- -.
L..
0
..
9
I
JA
I
I
FEB M
I
APR
I
MAY
I
I
I
I
I
I
J14 JUL AUG SEPT OCT NOV
9-.. SEATTLE
-.... PHOENIX
I
DEC
MoNTH
FIQE 4.6 Representative MonthlV Loads
than 3% of the work days, their impact should not qualitatively alter
the comparisons to be made between glazing systems.
reality,
In practical
this aspect of the occupancy schedule might produce payback
periods which are slightly longer (no more than 3%) than the data below
might indicate.
The normal work week begins on day 2 of the seven day simulation,
and ends on day 6.
Day 1 and 7 are sunday and saturday respectively.
When coupled with the weather data, this schedule produces a consistent
pattern of clear sundays and cloudy saturdays.
Day 1 of the simulation
is
saturday,
always given a CLRNS of one, while day 7,
draws CLRNS variables on the order of 50% or less.
consistently
The effect of
changing this pattern was not studied, but again the impact should be
relatively small and consistent across glazing types.
If
the monthly
total loads for any glazing system in any city are graphed, there is a
noticable dip in February and a peak in March (see Figure 4.6).
It is
very likely that the occupancy schedule together with the pattern of
clear versus cloudy days and the relative shortness of February produce
this apparent aberation.
It was ignored in this analysis.
The daily work schedule begins at 8h00 and ends at 18h00.
All of
the thermal and illumination requirements are met at 8hoo and are
maintained until 18hoo.
The building, then, is assumed to be completely
unoccupied all day on days 1 and 7, and between 18h00 and 8hoo on days 2
through 6.
During working hours, the thermostats are set to 68OF for heating
and to 73 0 F for cooling.
A variety of unoccupied thermostat settings
(setbacks) were examined, and the results are shown in Figure 4.7 for
both rug floored and tile floored, south facing offices with 64 sq.ft.
of double glazed windows.
The impact of setbacks should be parallel for
other glazing types.
It is interesting to note that the additional savings due to "deep"
setbacks are small for a rug covered floor,
for a tile floor.
heating or cooling
and virtually non-existant
In this situation, a protracted demand for purchased
energy,
at the beginning of the occupied
hours,
reduces the benefit from off hour savings, especially since the daytime
energy gains are generally greater than what can be stored or lost to
the outdoors.
The purchased energy necessary to cool or reheat the mass
displaces the heat of internal loads which must then be removed by the
chillers in either case, later in the day. Although allowable setbacks,
particularly for offices with little direct participation of internal
mass,
such as those with rug covered floors, could be "deeper",
the
setbacks established for all simulations were 550 for heating, and 850
for cooling. These settings were chosen because they reap the majority
of the potential savings,
and,
perhaps more importantly,
because they
fall easily on the conservative end of normal practice.
The illumination requirements assumed in the model follow the
THERMOSTAT SETBACXS IN KEY AR FOR HEATING/CM.ING
NO SETBACXS
SETEC=S
G8
SETACS a 55/85
PEAK KW/YR IN EGJIVALENT KWi
COOLING CLIMTES
T 54.0
HEATING CLIMTES
T\
AN'
SK ST jjEFW
RK OERDSA
T 50000
T
A
L
COOLING CLIMATES
K
H
A
R
2900
+m
TILE COVEED SLAB
FIGWE 4.7 The Relative Savings For Thermostat Setbacks Assuming Clear-D
current trend toward lower minimum ambient levels with local task
lighting as required.
it
Since the assumed office is not large (16 x 12),
is likely that most work stations would be located closer to the
windows than to the back wall.
be devoted
will
For this reason the rear of the office
to circulation functions.
since
Furthermore,
work
stations are assumed to be near the windows, and since the windows have
been enlarged,
for the base runs, no specific requirement or internal
gains were established for task lighting.
The minimum requirement of 35
foot candles will generally be exceeded on the work plane.
The model is
designed, finally, to maintain these minimum levels only during working
hours
(8h00 to 18h00).
There is no lighting requirement or load
established outside of these times or on weekends.
The internal gain schedule also follows working hours.
The gains
are considered to be constant through the workday, and are sized to be a
reasonable representation of the gains which would be associated with an
office of a similar size to the model.
these
There are three components to
internal loads; the heat of lights, equipment and people.
The
connected lighting load is assumed to be 1.5 watts per square foot of
floor area.
When lights are required, a maximum of 5.1 Btu's per square
foot of lighted floor area is added to the internal load.
The heat gain
for equipnent is assumed to be one watt or 3.414 Btu's per square foot
of floor.
The occupant gains were established for one person according
to the ASHRAE Fundamentals recommendation of 320 Btu/hr of sensible heat
gain[ASHRAE HANDBOOK AND PRODUCT DIRECTORY,
23,
p.
25'17 Table 16].
1981 FUNDAMENTALS,
Chapter
There is no accounting of latent loads due to
either people or ventilation air.
The impact of latent loads would
certainly boost cooling loads in most areas, but fenestration strategies
will only affect sensible heat gains.
Therefore, since the latent heat
of vaporization does not change the relative behaviors of the glazing
materials, it can be ignored.
The
ventilation
schedule
is
the
only
one
of
the
occupancy
requirements which was designed to be constant through working as well
as non-working hours.
The fixed hourly ventilation rate for the office
space was established,
according to Mass State Code at 0.1
square foot per occupant[ASHRAE
FUNDAMENTALS
6].
(New York,
At this rate,
ASHRAE,
cfm per
HANDBOOK AND PRODUCT DIRECTORY,
Inc.,
1977
1977) Chapter 21, p.21'14, Table
the office receives 1152 cu.
ft. of outdoor
ventialtion air per hour, or 0.6 air changes per hour.
A variable
ventilation system to reduce the air exchange rate during unoccupied
hours was considered, but because of the cost of the required controls,
and because few commercial buildings have such controls installed,
constant volume system was chosen for the model.
Such a variable
ventilation system uniformly increased cooling loads,
loss of nighttime cooling during the swing seasons.
a
probably due to
This increase makes
such a system a potential deficit in cooling dominated climates,
although savings due to reduced heating loads in colder climates
outweighed the annual increase in cooling loads for these cities.
Ventilation
systems with the
appropriate controls,
and particularly
those which were based on the "economizer cycle" model,
however,
substantially reduce heating loads during unoccupied hours.
could
Figure 4.8
shows the effect on heating loads of reduced off-hour ventialtion rates.
The figure is based on double glazing, but the relative impact should be
the same for each window type studied.
VARIABLE VOLMES IN KEY ARE FOR OCCUFIED/L90CCUPIED OMS
CONSTANT VOLUME VENTILATION (1152 efh)
VARIABLE VOLUME VENTILATION (1152/192 cfh)
PEAK KWYR IN EGUIVALENT Kim
T 5006.
COLING CLIMATES
40
HEATING CLIMATES
10*0
0-
BOSTON
MADISON
SEATTLE
MIAMI
PHOENIX
RUG COVERED SLAB
COOLING CLIMTES
4000-r
HEATING CLIMATES
Iw+
BOSTON
MADISON
SEATTLE
MIAMI
FT.WORTH
TILE COVERED SLAB
FIGURE 4.8 The Relative Savings For Constant Vs. Variable Ventilation Rates
Assuming Clear-DG
52
PART 5
AUXILIARY POWER SYSTEMS & CONTROLS
The auxiliary heating system for the parametric model was assumed
to be in-duct electric resistence heaters.
The choice of an all
electric system was made in order to allow the total loads to be easily
expressed as a single unit to facilitate eventual cost comparisons.
Furthermore,
because of the higher operating cost of electric heat, it
provides an appropriate "worst case" under which to estimate the best
potential savings for any given window system.
controlled by a standard thermostat,
and it
The heating coils are
is assumed that the units
are capable of delivering precisely the number of Btuh needed at an end
use efficiency of 100%.
However,
since purchased steam or fossil fuel
heat are approximately one half the cost of electricity, the impact of
non-electric heating plants can be estimated with consistent units, by
simply dividing the heating load in half and adding it
total load.
as KWH to the
The model was designed to allow heating loads to be
excluded from total KW demand,
during winter months.
which often changes peak load charges
Accordingly, Figure 5.1 shows the rough impact of
non-electric heat on the total peak loads for the representative cities.
The office represented in the figure is a low mass (rug floor) office
with south facing, clear double glazing.
ELECTRIC HEAT U/RUG COVERED SLAB
STEAM HEAT W/RUG COVE
SLAB
ELECTRIC HEAT W/TILE COVERED SLAB
STEAM HEAT W/TILE COVERED SLAB
-
PEAK Ku/YR IN EQUIVALENT K
T
0
T
A 30L
K 8
E
R
BOSTON
MADISON
SEATTLE
GRWH ASSLES STEAM HEAT CMPOENT a 1/2
ELECTRICAL SOURCE ERGY FOR EUIVALENT 1iI
FIGM 5.1 Electric Vs. Steam Heat Expressed In Equivalent
Assumin Clear-DG
h
The air conditioning systen is assumed to be a standard chiller and
air handling system with a system coefficient of performance (COP) of 2
including fan power.
'Ihe cooling loads for all simulations therefore
represent one half of the total number of cooling Btu's in a given time
period.
power
A COP of 2 was chosen in an effort to roughly account for fan
(which is not otherwise accounted for) .
The reduction of pot-
entially higher COP's for comrmercial chillers to the established system
COP of 2,
therefore,
implicitly attaches the cost of ventilation and
cooling fan power to the cost of air conditioning.
any resultant error in total loads is
study.
It is expected that
of little importance
to this
Because "economizer cycles" are still relatively uncommon in
conmercial buildings, and because the retrofit costs are generally
prohibitive, there is no provision made in the model for such a system.
Should the issue of variable ventilation rates become important to the
analysis of other strategies, however, chiller efficiency and fan power
could necessarily become powerful and independent variables, and the use
of a "system COP" would then no longer be an adequate expresseion of
energy use.
The cooling system, finally, is also operated by a standard
thermostat, and is capable of exactly meeting any hour's demand.
The lighting system is assumed to be a flourescent system capable
of maintaining a minimum of 35 foot candles on the work plane from a
connected load of 1.5 watts per square foot of floor area.
The basic
office of 192 square feet was divided into 3 discrete lighting zones
Each zone is
running parallel to and in from the weather wall.
64
square feet and all three zones are controlled by a single central
photocell.
The sensor is connected to simple on/off switches which
deliver a full 1.5 watts/sq.ft.
to their respective
zones whenever
daylight levels during occupied hours drop below 30 foot candles.
Daylight levels are allowed to fall to 30 foot candles before back up
lighting is added in order to insure that back up is truely necessary,
assuming that the rear of the office will be devoted to circulation, and
assuming that each zone of electric lighting will make some contribution
to lighting levels in the adjacent zone.
Lighting loads are calculated
hourly according to the daylight admitted by the given glass, and
assuning that daylight has the same or a slightly higher efficiency than
flourescent lighting.
Under this assunption, if the average "daylight"
levels in Btu per square foot of floor falls below 5.1 Btu (1.5 watt)
per square foot, as measured by the central sensor,
each zone is evaluated and,
if
necessary,
then the level in
the lights for each of the
zones are turned on.
The total Btu/hr added to each zone is then added
to the internal gains for that hour.
The daylighting distribution
system of inverted blinds, described above, establishes the distribution
of daylighting Btu's between the extreme points at the front and rear of
the office.
According to the tests carried out by Jim Rosen,
the dis-
tribution ratios (DR) for daylight in the front and rear of the office,
expressed as a ratio to the mid- point, are 1.3 and
.67
respectively
during conditions of overcast skies at any orientation
[Rosen,James
"Natural Daylighting and Energy Conservation: Innovative Solutions for
Office Buildings",
p. 74].
Therefore,
since an average solar flux of
5.1 Btu/sq.ft of floor area is assumed to provide the minimun lighting
levels
(30 fc)
in the back of the office,
Btu/sq.ft. (5.1 x .67)
each zone.
an actual level of 3.4
establishes the minimum daylight requirement for
The triggers for each zone,
as read at the central sensor,
then are set at 3.4 Btu/ft divided by the distribution ratio for each
zone (See Figure 4.5).
The electric lights, then, will come on indep-
endently for each zone,
from back to front.
If the available daylight
falls below 5.1 Btu/ sq ft at the center point, the lights in the rear
third of the office will come on.
If the daylight level at the sensor
falls below 3.4 Btu per sq.ft, then the center third of the office is
added,
and finally, if the threashold of 2.6 Btu/sq ft in the center of
the office is passed,
added.
then the third nearest the windows will also be
PART 6
OUTPUT ANALYSIS
The glazings chosen for analysis as base case examples represent
three generic types: Clear glass, reflective glass and static selective
transmitters (heat mirrors that primarily reflect the near I.R.).
Single and double glazed configurations are examined for each category,
and
triple
category.
glazed
configurations
are
also
examined
in the
third
In all cases, single and double glazing units consist of one
glazing layer of the categorical type, with the second layers,
being made of clear float glass.
present,
if
The third layer in triple
glazed units is a polymer substrate which carries the selective coating
between two layers of clear glass.
All of the main glass comparisons
are made under a common set of assumptions: 1) that the office space
behind them is low in mass (rug covered slab),
at a constant rate,
3) that it
2) that it
is ventilated
is electrically heated and cooled by a
constant volume ventilation system, 4) that the system COP's are 1 for
heating and 2 for cooling, and 5) that the glass area is 64 square feet.
These assumptions are discussed in detail above in Parts 3 and 4.
Differences in total energy cost between glazings,
therefore,
grow from their respective interactions with the ambient outdoor temperature,
spectrum.
and with the visible and infra-red portions of the solar
Figure 6.1 illustrates the solar spectrum, and its four main
SO.AR SPECTRUM, AM 1.5
75t -"
5W6-
400
60
80
100
12*
1400
16
18M
20W
2200
2400
ra
VISIBLE
NEAR I-R
FIGURE 6.1 The Major Couponents Of The Solar Spectrum
components.
Glass is on the order of 90% opaque to ultra-violet light,
so the portions which are most relevant to the energy flow in buildings
are the visible, and infra-red portions.
The infra-red (IR) portion may
be subdivided into the short wave length variety (near-IR) and the long
wave variety (far-IR) .
human eye.
Both infra-red components are invisible to the
38.8% of the total solar energy is contained in the visible
portion of the spectrum, with the bulk of the remainder being carried in
the near IR band.
Both the visible,
and near IR portions,
however,
eventually "degrade" into simple, heat energy (far IR) when absorbed by
surfaces, indoors and out.
The far-IR, which is derived from both the
visible and the invisible portions of the spectrum,
can help reduce
unoccupied heating loads, but is generally a negative contributor due to
increased cooling loads during those working hours that demand cooling.
Heat absorbing glass, as a category, was not examined here because
its performance as a commercial glazing is not significantly better, and
in some climates can be worse than clear glass. The relative heat gain
through most absorptive glass is almost as large as clear glass, and
lower transmission of visible light increases internal gains through a
higher the demand for purchased lighting thereby doubly contributing to
cooling loads.
These aspects of absorbing glass generally make its
energy balance very unfavorable within internal-load dominated spaces.
The thermal resistances of both clear and tinted glass are the same (the
identical values for conduction gains and losses illustrate their common
U value) so no savings can be made in the conductive component of either
heating
or
differentials.
cooling
loads
resulting
from
ambient
temperature
The relative solar heat gains of clear and tinted glass
are shown in figure 6.2 for both summer and winter conditions.
The
higher sum of the convective and radiative components for tinted glass
results from its additional absorption heating during the daytime.
The
hours of maximum heat gain and the hours of maximum internal gain, due
to the occupancy schedule, are generally coincident.
The portion of the
visible spectrum which is converted to heat within the glass can become
a double deficit when it
causes a demand for auxilliary lighting.
Electric lights will contribute at least 5.1 Btu (1.5 watts) per square
foot of illuminated floor to the internal gain schedule,
carefully organized energy conserving designs.
even in very
The category of tinted
glass, therefore, has not been specifically examined in this study, but
it is reasonable to assume that the total load performance of any
analyzed glazing compared with tinted glass can be roughly estimated by
its comparison to clear glass.
WINTER
SUMMER
7',r #75*'F
owr T 970o
Tor - 25'1
T,,
w 70'F
24 7
TRANSM1.55iON
AND REFLECT/ON
20/
2/67
S7
2
/7
- 52
239
97%
4A/N
CCNVGCTION
CONOUC7ON
/ 67
- C1.5AR lLA-
68% 'VA/N
2417
227
107
/07
q7
73
-52
2* /73
2/3
96%/ 4A/N -NE5AT
/02
AGSC0PI-1-
cI;4S
4f/%-qAl
24f
qz/
38/
75
75
52
2q
w7
%W~4
-J
58% 4AIN
AND
TNHERMAL RADIATiON
- REFLECT/N4A55
-52
V7
19%4AIN
FIGURE 6.2 Solar Heat Gains Thru Different Types Of Glass(from The Solar Home
Book, Aderson & Riordan, Brick House, Anover Ma)
Figure 6.2 also illustrates the relative solar heat gains for the
second base case category: reflecting glass.
reflectorized
glass
is
a "broad spectrum"
This traditional type of
reflector
which does not
distinguish between the visible and near-IR bands of the spectrum as the
fixed "selective transmitters" described below do.
Again,
there is no
noticeable difference in the conductive gain and loss relative to clear
glass.
In addition, the combined convective and radiative components of
the total heat gain are significantly higher than clear glass due to the
extra absorption heating even in extremely reflective glass.
great
increase in the reflected ccmponent,
But the
relative to clear glass,
produces a significant savings in terms of total heat gain.
similarity in U values
conditions)
The
(shown by the conduction losses under winter
between reflective and clear glass
is
due to the clear
protective overcoat applied directly to the reflective layer to prevent
tarnishing.
This overcoat raises the otherwise low emissivity of the
reflective coating to nearly that of clear glass leaving the U value
essentially unchanged.
Reflective glass,
then, promises significant
reductions in cooling loads due to a decrease in the solar heat gains
during occupied hours.
Since a large percentage of the total energy
consumption in conercial buildings, even in heating climates, is due to
cooling requirements during occupancy,
reflective glass represents a
significant competitor in strict economic terms.
visible portion of the spectrum produced
coatings, however,
The decrease in the
by traditional
reflective
does increase the lighting load relative to other
available glazings, and the apparent "gloominess" of the darkened view
through standard broad-spectrum reflective glass can lead to an increase
in purchased lighting from a pshychological tendency to respond to this
"gloom" by increasing the interior illumination.
turned on under these circumstances,
The lights are often
even when they are not strictly
necessary for the maintenance of minimum light level requirements.
It
is also likely, furthermore, that traditional reflective glass will soon
be widely outlawed, as has already occurred in San Fransisco, because of
the increased glare and incident solar energy experienced by neighboring
buildings.
The result of this dubious future, then, is a reduction in
its true competitive value,
should
therefore,
like
and traditional reflective (silver) glass
tinted
glass,
also
be
reviewed
with
some
scepticism.
The third category of base case glazings consists of static
selective
transmitters,
called
heat
relatively new in the marketplace,
mirrors.
These
glazings
are
and are not yet in common usage.
However, their ability to reflect the majority of the infra-red portion
of the solar spectrum without severely reducing the visible portions
together with their significantly improved U values give them strong
commercial potential compared
type.
to reflective glass of the traditional
Selective transmitters do reject the unwanted IR light and a
portion of the visible light by reflection, and as a result these
glazings may also experience the criticisms leveled at traditional reflectorized glass; contributing to the glare and overheating experienced
by the surrounding buildings and landscape.
However,
the quantity and
quality of the reflected light from the heat mirror group is not of the
same order as that of the ordinary reflectors, and the excessive heat
and glare problems should not prove to be such a critical issue within
the "heat mirror" group.
This point, however,
should be noted in the
comparisons between these fixed and the switchable transmitters, since
ZI
K
Ideal Transmittance
2.0
1.5
1.0
(15
2.5
20
10
3
30
WAVELENGTH (micrometers)
Visible
Thermal, Long Wave Infrared
Short Wave Infrared
FIGUE 6.3 The-Spectral Response Of Selective Transnitors
it is possible to minimize the externalities of glare and thermal
from any type of glazing
pollution which results, to varying degrees,
with
fixed
reflective
properties.
Figure
6.3
illustrates
their
reflectivity across the different wave lengths in the useful part of the
solar spectrum.
Several glazings are examined from this category, and each falls
into one of two general types of heat mirror coatings.
The first type
uses high transmission coatings which admit a larger portion of the
visible spectrum than do the low transmission coatings, which constitute
the second type.
Three high transmission glazings are examined.
The
representatives of this group are a single glazed configuration, called
HM-HT-SG in the analysis, a double glazed configuration,
finally a triple glazed configuration
transmission heat mirror (HM/LT-TG)
,
HM-HT-TG.
HM-HT-DG,
and
The only low
studied here is triple glazed. Low
rEATING LOAD
COCLING LOAD
LIGHTING LOAD
.
PEAK KW/YR IN EQUIVILENT KWI
ND-Jh
SWnH
.
UVAUE
1.e 0.58 4.3 e.ii
UVALUE
1.6 0.58 0.30 0.10
U VALUE
0.58 .3 0.10
U VALUE
1-0 e.58 .30 .1#
U VALE
i.e e. 6.30 .le
UVALE
FIQE 6.4 Anuaal Loads For Various U Values Assuming The Tranmission Of
Clear-DC: HEATING CLIMATES
HEATING LOAD
COOLING LOAD
LIGHTING LOAD
PEAK KW/YR IN EDUIVILENT KWH
WORTH
SMUTH
1.4 0.58 0.30 0.10
1.0 0.58 0.30 0.10
U VALE
U VALLE
PHOENIX
45W-.,
44W0 -
II
35W0 306.- 25W -26W4
15W9 low0-50.-
1.0 0.56 *.30 0.10
U VALLE
1.0 0.58 0.30 0.10
U VALLE
1.0 0.58 0.30 0.10
U VALLE
1.0 0.58 0.30 0.10
U VALE
FIGLRE 6.5 Amal Loads For Various U Values Assuming The Transmission Of
Clear-DC: COOLING CLIMATES
HEATING LOAD
CALING LOAD
LIGHTING LOAD
PEAK KW/YR IN EQUIVILENT KIH
momT
SFrH
.81 0.73 0.62 0.43 6.16
*.si 0.73 0.62 0.43 0.16
VISIBLE TRANSMISSION4
VISILE TRASIMISSIO
0.81 0.73 0.62 6.43 0.16
0.81 0.73 0.62 0.43 0.16
VISIBL
VISIBLE TRNNSISSION
TRANI5ION
406.-
SEATTLE
3W.
25* -
LL
low
C
C
C
C
C
6.81 0.73 0.62 0.43 0.16
VISIBLE TRANSISSION
6.81 0.73 0.62 0.43 0.16
VISIBLE TRANSMISSION
FICLEE 6.6 AnnuaI Loads For Various Visible Transmissions Assuming The U
Value kid Effective Transmissions Of Clear-DC: HEATING CLIMTES
[1~) HEATING LOAD
COO.ING LOAD
LIGHTING LOAD
-
PEAK KU/YR IN EQUIVILENT KWH
Scums
*.68 0.50 0.34 0.26 0.15 0.09
ORTH
0.68 0.50 6.34 0.26 0.15 0.09
EFFECTIVE TRANSMISSION
EFFECTIVE TANSMISSION
EFFECTIVE TRANSMISSION
EFFECTIVE TRANSMISSION
0.68 0.50 0.34 0.26 6.15 6.09
0.68 6.50 0.34 0.26 0.15 0.09
EFFECTIVE TRANSMISSION
EFFECTIVE TRANSMISSION
FIGLE 6.8 Arual Loads For Various Effective Transmissions Assuming The
U Value And Visible Transmission Of Clear-DC: HEATING CLIATES
HEATING LOA
cg0ING LOA
LICHTING LO
PEAK KW/YR IN EOUIVILENT KWH
Scum
0.68 0.50 0.34 0.26 0.15 0.99
EFFECTIVE TRANSMISSION
S.68 0.50 0.34 0.26 6.15 0.99
EFFECTIVE TRANSMISSIN
.68 0.50 0.34 0.26 0.15 0.09
EFFECTIVE TRANSMISSION
NORTH
0.08 0.50 0.34 0.26 6.15 0.09
EFFECTIVE TRAPMISSION
9.68 0.50 0.34 0.26 0.15 0.99
EFFECTIVE TRANSMISSION -
0.68 0.50 0.34 0.26 0.15 0.09
EFFECTIVE TRANSMISSION
FIGLEE 6.8 kaal Loads For Various Effective Transmissions Assuming The
U Value And Visible Transmission Of Clear-DC: HEATING CLIMATES
HEATING LOAD
COOLING LOAD
LIGHTING LOAD
PEAK KU/YR IN EDUIVILENT KW
smum
rO71
450M
40*
30*
250
15*
low
InC
MIMII
C C
MIMII
C
0.68 0.50 0.34 0.26 0.15 0.9
0.68 0.50 0.34 0.26 0.15 0.09
EFFECTIVE TRASISSION~
EFFECTIVE TANSMISSION
0.68 0.500.34 0.26 0.15 0.09
EFFECTIVE TANSMISSION
EFFECTIVE TANSMISSION
0.68 0.50 0.34 0.26 6.15 0.09
0.68 0.50 0.34 0.26 0.15 0.09
EFFECTIVE TN5ISSIN
EFFECTIVE TRNSMISSION
FICIK 6.9 Anual Loads For Various Effective Transmissions Amsumir
U Value An
The
Visible Trasaission Of Clear-DC: COOLING CLIMATES
transmission heat mirrors admit less visible and near-IR light than the
high transmission variety, and as a result the effective heat gain for
this configuration is the lowest of the heat mirror group.
6.1).
(See Table
The reduction of visible and near-IR light decreases the
effective heat gain because the visible portion of the spectrum contains
nearly half of the energy in the solar spectrum,
contains only heat (see Figure 6.1).
and the near-IR
The increased reflectivity
(non-overcoated) of low transmission coatings also brings about a slight
decrease to the U value over HM/HT-TG due to its lower emissivity.
Both
of the triple glazed heat mirrors (HT and LT) are constructed of two
outer lights of clear glass with a plastic substrate suspended between
them that carries the heat mirror coating.
therefore as the third glazing layer,
The coated substrate acts,
and it
is
this feature which
accounts for the bulk of the increased thermal resistance compared to
the
double
glazed
heat
mirrors.
Differences
in thickness
and
composition of the selective coating account for the remainder since the
clear glass used in all of the units is equivalent in thickness and
makeup.
Glass Type
Visible
Transmission
1. Clear SG
2. Clear DG
3. Reflective SG
4. Reflective DG
5. HM/HT-SG
6. HM/HT-DG
7. HM/HT-TG
8. HM/LT-TG
TABLE 6.1
0.86
0.81
0.20
0.18
0.61
0.56
0.68
0.49
Effective
Transmission
0.84
0.68
0.36
0.27
0.44
0.40
0.52
0.34
U Value
Winter
U Value
Summer
1.11
0.58
1.02
0.46
0.43
0.32
0.25
0.24
1.04
0.61
1.02
0.52
0.42
0.32
0.28
0.32
Glazing Parameters: Fixed Transmitters
EATING LOAD
COMING LOAD
LIGHTING LOAD
PEA K/YR IN EGJIVM.ENT KIe
MMC.6GX NWC.-OG
mir-
UCT.-OG
1wH-6G
FICLRE 6 10 Aiuai Louad Comparism
Ifl/lI-O
IH#-Tc
WWI-vo
WIfl-Tc
For Base Glazings: HEATING CLIMATES
WMT-Tc
EATING LOAD
COOLING LOAD
LIGHTING LOAD
PEAK KW/YR IN EJIVALENT KII
MIAMI
ieer
S E
SE
S E
Ng E W
25 -
Co
VC
cflc
nbcrc
T
C
-i
0.E*-K
SEu
N
C
L
L
C
5 E
WuCT.-SC
CCC
ULECT.
-PC
WUT-SC
CCC CCC C
W
T-DG
WHffT-TC
icl
.EM-DC
LECT.-S9 lEECT.-DG
FIG1E 6.11 Annal Lod Coaprisorm
wM i-DG
WNWT-SC
WT-TC
For Base Glazins: COOLING CLIMATES
HPWLT-TC
Table 6.1 lists the parameters for each static glazing type used
The effective transmission listed for all glazings
in this analysis.
have been corrected to account for absorption heating, and average
angles of incidence.
With the exception of clear glass,
values were supplied by the manufacturer.
the original
The values for clear glass
are taken from in the 1981 ASHRAE Fundamentals Handbook.
Figures 6.4 to 6.10 illustrate the effect on lighting, cooling,
heating, and peak load of variations in U value, visible transmission
and effective transmission. In each case, the values of double glazing
are assumed for the parameters which are not varied.
The graphs
illustrate the effect of each parameter change for both south and north
facing offices.
The patterns which develop clearly illustrate the
optimum average values for each orientation and climate
type,
and
should aid in the process of "tuning" glazing parameters to be climate
and orientation specific.
The graphs in Figure 6.10 and Figure 6.11
illustrate the annual KWH load in both absolute and equivalent terms.
The total annual peak loads are accounted for by converting peak KW per
year into equivalent KWH.
This conversion is made by multiplying the
sun of the monthly peak loads with the ratio of a $6 per peak KW to the
base charge of $0.10 per KWH.
The figures also illustrate the affect
of azimuth at the four cardinal points as indicated at the head of each
bar (see Appendix G for a table of numeric values).
Annual heating,
cooling and lighting loads for each base glazing at all azimuths are
characterized,
where applicable,
by plain blocks marked H, C, and L
respectively.
In heating climates (Figure 6.10) the glazing U vlaue proves to
be the most significant factor in load reduction.
In all three cities,
clear-DG
glass
shows
a greater
savings
than
reflective-SG
relative to the load for clear-SG at all orientations.
glass
The graph of
reflective-DG glass compared to clear-DG shows some additional savings
on the south, east and west fascades.
But the additional increment of
savings is small compared to that produced by the U value decrease
and clear double glazed (DG)
between clear single glazed (SG)
units.
The savings shown at these orientations are due to the increased
reflectivity of these glazings.
The result is the reduction of cooling
loads caused by the excess sunlight, particularly at the near infra-red
end of the spectrum,
transmitted by the clear glass.
The increased
in the north facing office clearly
lighting load for reflective-DG
loss of visible
light with
traditional
reflective
illustrates
the
glazings.
The impact of this loss is significant enough to make
clear-DG glass the better performer of the two in offices with a
northerly exposure.
The selective transmitter group (heat mirrors) generally shows a
better performance over the traditional group of options,
with the
possible exception of north facing clear-DG glass in overcast heating
climates,
such
transmission,
as
Seattle.
Even
in this
triple glazed heat mirror (HM/HT-TG)
case,
however,
high
does nearly as well
with only a slightly increased demand for cooling power.
This increase
in the cooling load is generally due to a decreased heat loss rate
(smaller U value) which exacerbates overheating during occupied hours
in the winter.
An office equipped with an inexpensive means of cooling
by ventilation with outdoor air during these months,
would stand to
benefit from the use of heat mirror (HM/HT) instead of clear glass even
in this limited case.
Among the options listed in the fixed selective transmitter group,
the high transmission triple glazed variety generally appears to be the
best choice for north facing windows, with the low transmission, triple
glazing providing the best option at the remaining orientations.
The
restriction of available solar energy to only the diffuse component on
the north side requires higher overall visible transmissions in order
to meet the lighting needs at this orientation.
however,
At other orientations,
the available beam sunlight is capable of producing cooling
loads large enough to warrant the slight increase in lighting loads
which lower static transmissions producein the long term loads.
transmission, double glazing (HM/HT-DG)
High
also shows great promise, and
this configuration has the added benefit of a direct application of the
selective coating on the glass surface.
Direct deposition eliminates
the polymer substrate carrying the reflective coating in the
glazed units.
triple
As the long term stability of these films in use has not
been established,
the double glazed units could prove to be the more
durable of the two.
Also, a slight reflectivity increase in the
coating of the double glazed units (HM/HT-DG)
would reduce the cooling
loads (due to a reduced transmission of visible and near-IR energy) and
could also decrease heating loads somewhat due to the slight decrease
in U value which results from the higher non-overcoated reflectivity.
In most climates, a decreased U value also produces an increased
cooling load, and the trade off between heating reductions and cooling
increases, once established,
could be minimized through the creative
use of overcoating to "tune" the U value of the finished unit.
changes would produce a low transmission,
These
double glazing capable of
displacing the low transmission, triple glazing as the best performer
for south, east and west facing offices.
The high transmission version
could similarly be "tuned" to be the best performer on the north
fascade.
The single glazed heat mirror generally proved to be the poorest
performer of the group.
The relatively poor energy balance,
and an
extra maintenance cost due to condensation on the glass surface would
likely eliminate
this configuration as a serious contender for any
orientation in all but extraordinarily dry climates.
Except in certain
special retrofit applications, and in hot, dry climates, single glazed
windows of any variety are not advisable; current trends indicate a
general movement toward double glazing of one variety or another in all
climates.
The traditional single pane windows are extremely vulnerable
to radiant energy loss or gain which can cause significant occupant
discomfort, resulting in higher thermostat settings during the heating
season and lower ones in the sumer. The heat mirror coatings on single
pane glass can seasonally minimize the problem of radiant loss or gain,
but, as a result, they are more prone to condensation problems during
one season or the other because of temperature and humidity differences
across the glass. The season of highest condensation potential depends
upon which side of the glass carries the coating, because the glass
will tend to run at the ambient temperature that exists on the uncoated
side.
The
relative performance of the heat mirror group in cooling
climates (Figure 6.11)
heating climates.
follows the same general pattern as it does in
Low transmission, triple glazed heat mirror performs
best at all orientations including north facing fascades, but again the
double glazed , high transmission configuration is very close in
In these climates, an increase in reflectivity to
overall performance.
both visible and near-IR light, without a concommitant decrease in U
value would turn the double glazed heat mirror into a clear winner
A decrease in U value is undesirable in cooling dominated
overall.
climates, because the value (in cooling terms) of what little heat loss
may occur by conduction out is thereby reduced.
outside
temperature
importance
differentials
in cooling
of conduction to a small
heating climates.
The smaller,
climates
fraction of its
inside,
reduce
the
importance
in
The U value decrease that is associated with higher
reflectivities can be limited
by varying the degrees of overcoating
the selective film thereby increasing its emmissivity.
The switchable,
electro-optic glazings (ELO 1 to 5) are illus-
trated in Figures 6.12 and 6.13 for heating climates and cooling
cl imates respectively.
The graphs are constructed against the same
scale as the static glazings, and the load graphs for the heat mirror
group have been repeated at the end of each electro-optic group to
allow for easy visual comparisons.
Table 6.2 lists the parameters used
in simulating each of the proposed electro-optic glazings.
The tables
in Appendix G contain a tabulated summary of the various loads which
Glass
Type
Effective
Transmission
Clear
ELO-1
ELO-2
E10-3
ELO-4
ELO-5
TABLE 6.2
0.61
0.61
0.61
0.54
0.35
Visible
Transmission
Clear
0.73
0.73
0.73
0.70
0.50
Effective
Transmission
Switched
0.34
0.26
0.15
0.14
0.09
Glazing Parameters: Switchable Glass
Visible
Transmission
Switched
0.62
0.43
0.16
0.16
0.11
U
Value
Winter
U
Vale
Summer
0.33
0.33
0.33
0.32
0.30
0.33
0.33
0.33
0.31
0.30
HEATING LOAD
COM.ING LOAD
LIGHTING LOAD
PEAK KW/YR IN EMJIVALENT KU
BOSTON
N
NS E W NS E W
E0L-1
EU.-2
ms E W
ELO-3
E00-4
N S E W N S EW
/T-SG
E0-5
M/HT-DG
S E W
N S E W
M/HT-TG
HM/LT-TG
MADISON
N S EW
ELD-I
EL-2
EL0-3
ELO-4
MHT-SG
EL-5
S EW
/HT-DG
M/HT-TG
4/LT-TG
SEATTLE
N SE
W NSE W N
S EW
EW
SEW
S
E
ELD-2
E00-3
E0.-4
ED-5
S E W
W
H H
ELO-i
SEW
HT77
W/HT-SG
H
HM/HT-DG
FICuK 6.12 Anual Load Coparisons For Electro-Optic Glaztrns: EATING CLIMATES
H
HM/HT-TG
H
HM/LT-TG
fEATING LOAD
COING LOAD
LIGHTING LOAD
PEAK KU/YR INEGJIVA.ENT K14
MIAMI
T
T 45W T
A 3500 -
L306
SE
K25W%
S E
E W
N
H 2W
N
S E
w
NS E W N
S
W
S E
W
S EW
SE
S
S E W N
S E
NN
I
NL
E
A lo
R5
O
C
c
KO-1
Cc
ELD-2
CcCc
EUD-3
c c cc
ELO-4
CC
c c c c
C
CC C
M/MT-SG
/HT-DG
ELD-5
C
C
MHT-TG
C c
Ri/LT-TG
PHOENIX
T
-
L3
3
S6
02U * -
E
w
E
S EW
H2046..
SEW
-W
N
E W
N
N
SE
W
E
N
N
E
A
c
ELO-i
C
ELD-2
ELD-3
ELO-4
C CCC
Eli-5
CCCC
H-SG
cc
ifM/r-G
jM/r7-TG
H./iT-TG
FT.WORTH
T
0
T
400 -
A 35
-
3K
-
K
20S-
Alo-
SS
S
EW
N
W
SE
E NS E
ELO-2
ELD-3
ELO-4
S
NS E W N
N
Ctt
c
C
CCc c c
EL0-i
W
ELO-5
HM/NT-SG
N
N
c CC C e
HM/HT-DG
FICLM 6.13 Annual Load Comparisons For Electro-Optic Clazings: COOLING CLIMATES
Ci±-iC
HM/HT-TG
cc
HM
/LT-TC
E
used in simulating each of the proposed electro-optic glazings.
Each of the proposed glazings is a sealed, double pane unit
capable of maintaining
two different stable transmissivities of both
visible and near IR light.
The ability to vary the transmission
characteristics
impulse allows a choice of
by electrical
energy flow rates into the office space.
conditions,
and any heating
loads,
two solar
Purchased lighting under dim
on extremely cold or unoccupied
periods of low internal gains, can be minimized in the clear state.
The
dark state can then be initialized simply in order to dispose of the
unwanted extra energy available in the clear state when internal loads
and
the solar intensity outside make this additional
unnecessary.
energy
(heat)
The inediacy of the energy management potential with such
optical control is best suited to spaces with short term time constants.
Clearly, any energy rejected at the windows cannot contribute to later
thermal loads, and by the same token, any other energy management
strategies which dampen the amplitudes of daily thermal loads will tend
to reduce the value of switchability compared to any of the fixed
transmission glazings
Lighting loads are the most "instantaneous" and undampable of the
various loads,
and switchability should show its best potential here.
Limits to the range of switchability set the ceiling on possible
reductions in this area.
A narrow range of switchability between the
clear and switched states will tend to cause the need for a reduction of
clear state transmissions out of defference to the energy content
ofaverage conditions.
The daylighting effectiveness under the extremely
dim conditions of early hours, and overcast days would therefore be
reduced.
It should be noted however that lighting requirements,
as in this simulation,
beginning at 8h00 and ending at 18h00
little
impact from conditions at the daily extremes
cause
in solar flux.
Little overall increase in lighting loads over clear glass was found in
the simulation results, so the penalty for reduced initial transmissions
is
small.
The lower level of transmissions in the switched states of
these "low transmission" switchers may raise the psychological
with regard to interior-exterior
issue
contrast as has been identified
in
This qualitative issue
applications of traditional reflectorized glass.
should be explored thoroughly before "deep" switchability is seriously
considered.
The brightest days will call for "darkened" glass, thereby
producing the greatest possible indoor to outdoor constrast.
Cooling loads are quite immediate in their peaks, and except for
economizer cycles, which still require fan power,
there are very few
strategies available to "spread out" or dampen the amplitude of these
peaks.
Heat storage mass has some effect, but in climates which cannot
effectively cool the mass through losses during unoccupied hours,
is very little positive mass affect.
(See Figure 4.2)
there
The mass simply
heats up under these circumstances and then effectively supports the
cooling loads later in time.
Cooling loads are, in fact, the load on
which switchability has its most dramatic effect.
The reduction (shown
in Figures 6.10 to 6.13) is clearly visible for all climates and
orientations.
This result also illustrates the excessive brightness of
ordinary conditions, in these climates,with regard to the energy demand
in load-dominated spaces.
Heating
mass,
are
loads,
not
which are
dramatically
effectively
affected
by
dampable with
the
best
additional
performing,
electro-optic glazing when compared to the heat mirror group.
The low
clear-state transmissions,
set the
demanded by daytime cooling loads,
heat gain capabilities initially to a level very similar to the
transmissions of the heat mirror group.
The predicted U values of the
switchable glazings, however, are a bit higher.
In the harsher heating
climates, this factor can actually increase the heat loads due to extra
conduction losses. These losses in combination with the reduction in
storable
heating
energy which occurs during the switched state can produce
loads
under
switchable strategies
attainable with static heat mirrors.
which
exceed
the
loads
In the case of heating-dominated
climates (connoted by the graphs of clear-SG) an economizer-cycle would
help control daytime overheating in the air in order to keep the glazing
in the clear state longer.
The extra gain which would result,
if
effectively stored in the available mass, could then contribute toward a
further reduction ofthe unoccupied heating loads in contrast to static
gjazings.
As with the base case glazings, these types show some variation in
their
relative
performance
at
different
azimuths,
but
switchable
glazings are capable of maintaining a much more stable load structure
with
regard
to
orientation
than
glazings
of
fixed
Uniformity in the loads could produce secondary benefits
properites.
from cost
reductions in the design and implimentation of required HVAC systems.
This potential saving is not accounted for in the comparison.
As with the selective transmitters of the static type, the
switchable transmitters with the best performance overall, are those
which begin with lower transmissions in the unswitched or "clear" state.
This result springs from the fact that the average daily condition
provides considerably more light and energy (through the assumed 64 ft2
window) than is necessary to just meet the lighting loads.
This extra
light, whether visible (38.8% of the total spectral content) or near-IR,
represents a potentially large addition to the cooling load under even
average conditions.
Since the window area of 64 ft2 was established
according to normal minimum conditions,
the average condition is very
likely to provide a great deal more energy through the larger window,
than is- necessary under these conditions.
Although a large window
greatly exaggerates this issue, simulations run to compare high and low
transmission coatings on 48 ft2 windows still exhibited a similar though
reduced comparative result (Figure 4.3).
It is interesting to note that
the reduction of comparative savings for switchable glazings
primarily to load reductions in the base glazings.
is
due
The decrease of
energy consumption with reduction of glass area is very small for the
switchable glazings. 'Ihis load stability offers an incredible potential
flexibility to designers using electro-optic glass.
By using such
glazings, the architect is using the glazing which universally produces
the lowest possible annual loads,
even if by small margins,
but more
importantly, a new freedom with regard to glass area is available.
The
importance of this relative insensitivity to window area should not be
overlooked.
In cooling climates, ELO-5, which exhibits the lowest initial
transmissions, is the best performer of the group for all but the north
fascade.
In heating climates, however,
ELO-4 which provides a slightly
higher heat gain potential due to higher transmissivities in both
states,
performs better than ELO-5 at the sunny orientations.
ELO-2
does the best job under the diffuse light conditions on the north side.
These results suggest that switchability should be "tuned"
to
differences in both climate and orientation in order to maximize its
performance.
With such improvements,
electro-optic glazing materials
could make a much more noticable reduction of total loads. However,
added
performance
climates
is
of
the
proposed
switchable
glazings
in
the
heating
somewhat disappointing in comparison to low transmission
glazings of the static variety.
Apparently, the variation in ambient
outdoor temperature is wide enough to minimize the impact of any changes
in solar intensity over the course of a full year thereby preventing the
proposed
strategy
for
changability
from
making
any
remarkable
improvement in total loads when compared to static heat mirrors.
average
temperatures on clear winter days,
maximum,
according to the original "sunpulse" data,
when solar
than the temperatures associated with cloudier periods.
flux is
The
at a
tend to be lower
The opacity of
water vapor to far-IR light would in fact tend to raise temperatures on
cloudy days,
while the increased reradiation of far-IR through clear
skys tends to depress terrestrial temperatures on clear days [Henderson,
S.T.,
DAYLIGHT AND ITS SPECTRUM (New York, American Elsevier Publishing
Co.,Inc.,
loss,
1970) pp. 33-34).
There would therefore be an increased heat
due to lower outdoor ambients,
on clear days when the increased
solar flux would otherwise exacerbate the occupied cooling loads.
As a
result, the cooling peaks during periods of maximum solar gain are often
mitigated by increased heat loss rates due to lower ambient temperatures
and increased reradiation of far IR light.
Switchable glazings do show
some reduction in cooling loads in comparison with static heat mirrors,
but the majority of these savings are defrayed by the increased heating
loads.
This increase results from a reduction in energy available to
the storage mass in the switched state together with U values which are
slightly larger than those assumed for the heat mirror glazings.
The
net effect of these mechanisms is an overall decrease in the potential
savings for switchability in heating climates
Improvements in the "climatological tuning" of U values and
transmission, however, would likely produce an improved savings picture
In addition to these changes, if an increase in
in all climates.
flexibility with regard to the switching strategy and range were
accomplished,
produced.
a
significant
improvement
in
performance
Rather than a simple two-way switch,
could
be
glazings with a
"multi-stage" switch would offer the ability to admit exactly the amount
of energy necessary for lighting plus any energy which could be stored
or used against unoccupied heating loads.
directly subtracted from cooling loads.
most to gain from these improvements,
some improvement
The excluded energy would be
Again, hot climates have the
but heating climates should see
in both cooling and lighting loads.
The two step
switchers are less flexible, occassionally admitting extra energy for
the sake of daylighting when the switched state would make supplemental
lighting necessary.
Figure 3.2 indicates the value of this daylighting
priority to two stage switchers.
Although the effect is
small for
glazings with higher transmissions, the trade-offs become noticable when
lower transmissions are involved.
A "sliding switch" would minimize
this tendency and produce an enhanced ability to manage the immediate
solar energy flows through the office.
In cooling dominated climates, on the other hand,
glazings offer a relatively handsome potential savings.
electro-optic
An initially
low transmitting glazing with a "deep" switch (one which offers a
dramatic reduction in the transmission of both visible and near-IR light
in its switched state) such as ELO-5 promises handsome reductions in
comparison to the best performers from the static group on the sunny
fascades.
This improved performance is due to its ability to control
the normal amount of beam sunlight which strikes the building on all but
the north side.
The north facing fascades in hot climates,
in cooler climates,
like those
do not experience the swings in total solar flux
which puts switchabiltiy at a premium in other orientations.
Two stage
switchable glazings, therefore seen to have little if any role to play
in
north facing
conditions.
A
offices
"sliding
irrespective
switch"
of the ambient
unit
with
higher
climatological
"clear-state"
transmissions might prove to be a better performer than the proposed
units at this orientation.
Such switchability would certainly provide
additional savings as in heating climates,
at the sunny orientations.
The increment added in hot, climates with large variations in the beam
component of sunlight, such as Miami,
could be significant if the range
of variability is climatologically tuned.
PART 7
CONCLUSIONS AND SUGGESTIONS FOR FURTHER WORK
Glazings with switchable transmission properties show promise as
load control devices in all climates, and as load reduction devices in
The relative insensitivity of switchable
cooling dominated climates.
glazing to changes in glass area and azimuth together with their
consistently low load profile (@ 10 KW/sq.ft. per year) and reduced peak
load make them a potentially attractive tool from a load management
perspective.
"two-phase"
In cooling load dominated climates, single step or
switchable
glazings
potential for the assumed
.
show
significant
load
reduction
The load reduction for a south facing
office using ELO-5 in Phoenix is on the order of 30% when compared to
reflective double pane; the best performer from the base case group for
a southern orientation
in Phoenix.
Even in climates which involve
significant heating loads such as Boston, overall load reductions of 10%
or more are possible in south facing offices.
In
strictly
commercial
terms,
the
marginal
utility
of
the
switchable transmitters included in this study is limited in cold
climates, but worthy of consideration in hot climates.
The unit savings
for switchable glazings in Boston (including equivalent peak charges) in
comparison to a low transmission, fixed heat mirror is only on the order
of 4.2 KWH/sq.ft. per year.
This unit savings is clearly small enough
that under current rate structures, there is little margin for the extra
production costs of switchability.
At most,
in such climates,
the
market value of 20.5 KWH per unit area provides a rough estimate of the
limit to a viable marginal cost to the consumer.
This limit represents
the best annual savings in KWH resultant from a 64 ft
given configuration,
and
2
window with the
switchability,
times the five year payback
period expected by commercial developers.
If smaller window areas are
assumed,
the annual KWH savings, per unit area, decreases.
savings in equivalent KWH for a 48 ft
2
window is
The yearly
approximately 2.3
KWH/ft2 per year as opposed to 4.1 KWH/ft 2 per year for 64 ft2 windows.
In hotter climates such as Phoenix,
however,
switchability increases to 11.2 KWH/sq.ft.
the value added by
per year,
producing a five
year simple savings ceiling of 56 KWH/ft 2 . if a window area of 64 ft2 is
assumed..
The market value of this savings in operating cost for the
best performing switchable
transnitter
(ELO-5)
performing fixed transmitter (reflective-DG)
compared
to
the best
in Phoenix shows a promise
worthy of continued development.
These comparisons of electro-optic glazings to reflective glass
clearly provide
the harshest
possible
evaluation
of
switchability.
Clear glass continues to be widely used in all climates,
and in many
cases, the range of choice considered is restricted to a decision
between single or double glazed versions of this glass.
electro-optic glazings
savings expand
are compared to clear-DG glass
to considerably more encouraging
heating and cooling dominated climates.
If the
the potential
dimensions
in both
This more optimistic comparison
is further legitimized by the potential future restrictions which may be
the trend begun in San
brought to bear against reflective glass if
Francisco becomes more general.
A comparison of the best performer from the electro-optic group by
climate (ELO-4) for heating dominated climates,
This savings represents a
per sq.ft. of glass on the order of 20 KWH.
five
compared
improvement
fold
low-transmission heat mirror.
to
the
shows an annual savings
savings
garnered
against
ibis increased savings for south facing
offices would, therefore, push the simple savings ceiling up to a viable
100 KWH/
ft
2
over five years.
In cooling dominated climates, the best
performing switcher (E10-5) experiences a nearly equal increase in five
year simple savings potential.
In hot climates, the savings relative to
clear-DG glass climbs to 38.8 annual KWH per ft2 of glass which produces
an annual simple savings ceiling determined by the market value of 194
KWH per ft2 . These latter potential savings relative to clear-DG glass,
together with the wide spread usage of clear glass and the uncertain
future of both forms of reflective glass, argue more strongly in favor
of a significant commercial potential for switchable glazing materials.
Continued developnent,
then, may be,in fact,
quite warranted for all
climates, and not an issue relevant only to exceptionally hot climates
such as Phoenix.
Switchable glazings
,
used as windows, seen to perform best in
offices of light weight construction,
or in offices which are heavily
treated with accoustical materials, including rug covered floors behave
like light weight construction, due to the lack of exposed (uninsulated)
mass area available for heat storage.
As a result, these strategies do
offer alternative design solutions for controlling the sensitivity of
such spaces to the wide swings in energy flow common to commercial
architecture.
be
an
The increased flexibility in design restrictions should
attractive
feature
of
switchability
to
the
architectural
community.
Areas for continued research which seem to show promise exist in
both
the properties
behavioral
and application
of electro-optic materials.
aspect of switchability which needs
further
A
examination
concerns the number of stable phases which are available for control. A
two-phase (on-off) switch limits the range of control over the energy
flow which
creates
potentially dramatic
cooling and lighting loads.
trade-offs between
heating,
This issue may be particularly important in
higher mass offices where controlling the air temperature deprives the
mass of some extra potential energy.
In this same vein, further
exploration on the effects of an "economizer cycle" for cooling during
the winter months in cool climates, could prove useful in maximizing the
overall
performance
of
even
two-phase
switchers
in
offices
with
significant amounts of storage capacity.
From the applications perspective, there is a need for further work
on switchable glazings used as variable shading devices rather than as
the glazing components examined in this study.
Shading devices are
limited in their ability to control the diffuse and reflected components
of
incident
solar
Longmore,DAYLIGHTING
P.Petherbridge
(
Publishing
London,
Heinemann
Co.,
and
J.
1966)
the beam component,
which provides the greatest
part of the variability in solar gains,
might be quite effectively
pp.516-5231.
However,
energy[HopkinsonR.G.,
controlled by such devices throughout most temperate climates.
Also,
since well designed shading devices are capable of shading twice their
own area in window below , the unit area savings could significantly
increase at all the simulation sites.
Furthermore,
the fact that such
devices are easily isolable thermally from the weather wall of the
building gives a greater degree of flexibility to the types of compounds
which may effectively be used.
The
entire
range
of
qualitative
effects
finally, deserves further attention and study.
from
switchability,
This analysis has made
no attempt to truely evaluate these issues, and the potentially great
positive affect of increased window area may in fact improve the market
potential of such glazings for the sake of more comfortable and
attractive working conditions.
The qualitative issues which appear most
important revolve around the value of the extra natural light which can
be admitted by switchable glazings,
under dim conditions without great
penalties from increased cooling loads under average conditions.
extreme brightness,however,
Under
the "deep" switching capability which makes
the best quantitative showing under the assumed conditions, may see a
diminished value due to the potential
transmission.
"gloom" of too little visible
Further work, therefore, on the psychological threasholds
regarding the reduction in visible light of various wave lengths is a
critical aspect of effective window design.
transmission,
finally,
is
important
non-switchable glazing designs if
issue in their application.
to
This aspect of selective
both
switchable
and
occupant comfort is held to be of
92
APPENDIX A
RECCMMENDED AVERAGE MONTHLY DECLINATION
For the Average Day of the Month
Month
n for ith
Day of Month'
Date
n, Day of Year'
6, Declination
59 + i
17
47
75
April
May
June
90+ i
120 + i
151 + i
105
135
162
9.4
18.8
23.1
July
August
September
181 +
212 + i
243 + i
198
228
258
21.2
13.5
2.2
October
November
December
273 + i
304 + i
334 + i
288
318
334
January
February
March
i
31 + i
i
-20.9
-13.0
-2.4
-9.6
-18.9
-23.0
* The average day is that day which has the extraterrestrial radiation closest to
the average for the month. See Section 1.8.
b These do not account for leap year; values of a from March onward for leap
years can be corrected by adding 1.Declination values will also shift slightly.
Rocn1e i Average Day for Each Mouth and Values of a by Monds
[from Klei (1976)]
94
APPENDIX B
ASSUMED DIRECT-DIFFUSE SPLITS FOR HORIZONTAAL CORRECTION OF IT
<
C2NGL
<
JAN
FEB
APR
JLI
MAY
JUL
AUG
SEP
OCT
NOV
45/55
60/40
45/55
60/40
45/55
60/40
70/30
85/15
55/45
70/30
50/50
65/35
70/30
85/15
25/75
40/60
40/60
55/45
40/60
55/45
45/55
60/40
55/45
70/30 -
DEC
AIbuQuemrue
0.12
0.42
0.42
45/55
60/40
45/55
60/40
40/60
55/45
45/55
60/40
45/55
60/40
0.12
0.42
0.42
45/55
60/40
45/55
60/40
40/60
55/45
45/55
60/40
60/40
75/25
0.12
0.42
0.42
50/50
65/35
45/55
60/40
40/60
55/45
60/40
75/25
35/65
50/50
35/65
50/50
70/30
85/15
35/65
50/50
40/60
55/45
40/60
55/45
45/55 45/55
60/40 60/40
0.12
0.42
0.42
45/55
60/40
60/40
75/25
50/50
65/35
60/40
75/25
40/60
55/45
40/60
55/45
50/50
65/35
40/60
55/45
60/40
75/25
45/55
60/40
60/40
75/25
50/50
65/35
40/60
55/45
40/60
55/45
50/50- 50/50
65/35 65/35
50/50
65/35
50/50
65/35
40/60
55/45
40/60
55/45
55/45
70/30
50/50
65/35
50/50
65/35
45/55
60/40
35/65
50/50
35/65
50/50
70/30
85/15
50/50
65/35
65/35
80/20
60/40
75/25
35/65
50/50
50/50
65/35
40/60
55/45
40/60
55/45
60/40
45/55
43/55
60/40
70,30
85/15
65/35
80/20
70/30
85/15
35/65
50/50
50/50
65/35
45/55
60/40
45/55
60/40
Boston
50/50
65/35
Carf bou
Columble
0.12
0.42
0.42
40/60
55/45
45/55
60/40
45/55
60/40
55/45
70/30
40/60
55/45
0.12
0.42
0.42
50/50
65/35
50/50
65/35
45/55
60/40
40/60
55/45
40/60
55/45
0.12
0.42
0.42
45/55
60/40
65/35
80/20
70/30
85/15
70/30
85/15
40/60
55/45
0.12
0.42
0.42
40/60
55/45
45/55
60/40
40/60
55/45
60/40
75/25
40/60
55/45
Ely
40/60
55/45
Fort
r
35/65
50/50
Greut Fad Is
70/30
85/15
35/65
50/50
MadIson
0.12
0.42
0.42
0.12
0.42
0.42
0.12
0.42
0.42
50/50
65/35
55/45
70/30
65/35
80/20 85/15
70/30
85/15
50/50
65/35
80/20
65/35
80/20
65/35
80/20
65/35
80/20
40/60
55/45
A5/55
60/40
40/60
55/45
40/60
55/45
65/35
80/20
65/33
65/35
65/35
80/20
40/60
55/45
55/45
70/30
65/35
80/20
70/30
85/15
70/30
85/15
35/65
50/50
55/45
70/30
35/65
60/40
70/30
85/15
35/65
60/40
35/65
60/40
35/65
60/40
70/30
35/65
50/50
"Iami
80/20
New York
0.12
0.42
0.42
40/60
55/45
60/40
75/25
45/55
60/40
70/30
85/15
35/65
50/50
35/65
50/50
70/30
85/15
35/65
50/50
40/60
55/45
55/45
70/30
40/60
55/45
45/55
60/40
0.12
0.42
0.42
50/50
65/35
70/30
85/15
65/35
80/20
70/30
85/15
45/55
60/40
40/60
55/45
65/35
80/20
60/40
75/25
70/30
85/15
50/50
65/35
65/35
80/20
45/55
60/40
0.12
0.42
0.42
55/45
70/30
50/50
65/35
35/45
70/30
70/30 45/55
85/15 60/40
35/65
50/50
35/65
50/50
40/60
55/45
45/55
60/40
65/35
80/20
55/45
70/30
60/40
75/25
35/65
50/50
35/65
50/50
70/30
85/15
70/30
85/15
70/30
85/15
70/30
85/15
70/30
85/15
40/60
55/45
35/65
50/50
35/65
50/50
70/30
85/15
70/30
85/15
50/50
65/35
40/60
55/45
65/35
80/20
60/40
75/25
seett10
0.12
0.42
0.42
70/30
85/15
45/55
60/40
wasi i ngton OC
0.12
0.42
0.42
60/40
75/25
50/50
65/35
65/35
80/20
65/35
80/20
50/50
65/35
35/65
50/50
96
APPENDIX C
CORRECTED WEATHER DATA
ALBUQUERQUE
JAN.
1
CLRNS= 1.0
TAV = 34
TRNG = 23
2
0.9
33
22
3
1.0
34
23
4
0.8
36
25
5*
6
0.8 0.5
36
33
25
15
7
0.1
37
19
FEB.
1
CLRNS= 1.0
TAV = 37
TRNG = 30
IK
IT
= 0.03
= 1350
IK
IT
= 0.09
IM
= 217
JM
= 266
MAR.
1
CLRNS= 1.0
TAV = 49
TRNG = 26
IK
= 0.07
IT
IM
= 2262
= 316
MAY
1
CLRNS= 1.0
TAV = 64
TRNG = 32
2
1.0
49
26
3
0.9
42
27
4
0.8
42
21
5
0.a
42
21
6
0.6
41
19
7
0.3
46
13
'IM
2
1.0
64
32
3
1.0
64
32
4
0.9
68
29
5
0.9
68
29
6
0.7
66
24
7
0.5
63
22
JUN.
1
CLRNS= 1.0
TAV = 74
TRNG = 30
IK
IT
= 0.09
IM
= 381
IM
= 379
3
0.9
77
26
4
5
0.9 0.9
77 ' 77
26
26
6
0.7
75
24
7
0.5
73
21
AUG.
1
CLRNS= 1.0
TAV = 77
TRNG = 27
= 0.18
= 2939
IK
IT
= 0.12
= 2661
IM
= 366
IM
= 346
IK
= 0.06
IT
IM
= 2339
= 328
NOV.
1
CLRNS= 1.0
TAV a 45
TRNG = 24
2
1.0
69
24
2
1.0
45
24
3
0.9
68
24
3
0.8
42
26
4
0.9
68
24
4
0.9
44
27
5
0.9
68
24
5
0.8
42
26
6
0.8
65
20
7
0.5
65
13
6
7
0.7 0.6
43
45
20 .20
6
0.6
42
19
7
0.4
34
18
2
1.0
58
29
3
1.0
58
29
4
0.9
55
27
5
0.9
55
27
6
0.8
57
23
7
0.6
53
24
2
1.0
74
30
3
1.0
74
30
4
0.9
75
31
5
0.9
75
31
6
0.8
73
25
7
0.7
67
20
2
1.0
77
27
3
0.9
75
26
4
1.0
77
27
5
0.9
75
26
6
0.7
74
23
7
0.5
70
20
2
1.0
62
30
3
0.9
57
25
4
0.9
57
25
5
0.9
57
25
6
0.8
56
27
7
0.3
50
19
2
1.0
37
26
3
0.9
33
22
4
0.9
31
22
5
0.8
39
17
6
0.6
39
23
7
0.2
37
15
= 3016
IK
IT
SEP.
1
CLRNS= 1.0
TAV = 69
TRNG = 24
5
0.8
36
22
= 366
= 0.10
= 2987
-2
2.0
82
29
4
0.9
39
25
= 0.03
= 2648
IK
IT
JUL.
1
CLRNS= 1.0
TAV = 82
TRNG = 29
3
0.9
39
25
= 1808
APR.
1
CLRNS= 1.0
TAV = 58
TRNG = 29
IK
IT
2
0.9
39
25
OCT.
1
CLRNS= 1.0
TAV = 62
TRNG = 30
IK
IT
= 0.09
= 2429
IM
= 356
DEC.
1
CLRNS= 1.0
TAV w-37
TRNG = 26
IK
IT
= 0.08
= 1413
IK
IT
= 0.08
= 1271
IM
= 228
IM
= 204
BOSTON
JAN.
1
CLRNS= 1.0
TAV = 19
2
0.9
26
TRNG = 13
15
IK
= 0.06
3
0.8
29
4
0.5
27
5
0.2
33
6
0.2
33
7
0.1
34
9
13
9
9
10
FEB.
1
CLRNS= 1.0
TAV = 37
TRNG = 14
IT
= 844
IK
IT
IM
= 139
IM
MAR.
1
CLRNS= 1.0
TAV = 35
TRNG = 17
2
0.9
36
17
3
0.7
32
17
4
0.7
32
17
5
0.4
39
13
6
0.1
35
6
7
0.1
35
6
APR.
1
CLRNS= 1.0
TAV = 48
TRNG = 15
= 0.10
= 1759
IK
IT
= 0.20
= 2172
IM
= 247
IM
= 291
2
1.0
3
0.8
4
0.8
5
0.5
6
0.2
7
0.1
TAV
= 57
57
63
63
57
52
44
WRNG = 17
17
21
21
19
12
4
JUN.
1
CLRNS= 1.0
TAV = 62
TRNG = 15
IK
IT
= 0.07
= 2475
IK
IT
= 0.07
= 2631
IM
= 313
IM
= 330
1
JUL.
CLRNS= 1.0
TAV = 70
TRNG = 18
2
0.9
76
19
3
0.8
78
21
4
0.7
73
17
5
0.6
71
16
6
0.4
72
14
7
0.1
67
10
AUG.
1
CLRNS= 1.0
TAV = 68
TRNG = 19
IK
= 0.04
!K
= 0.09
IT
= 2612
IT
= 2104
IM
= 343
IM
= 284
SEP.
1
CLRNS= 1.0
TAV = 64
TRNG = 19
2
0.9
61
16
3
0.8
65
17
4
0.8
65
17
5
0.6
65
19
6
0.4
61
12
7
0.3
58
7
OCT.
1
CLRNS= 1.0
TAV = 51
TRNG = 17
IK
IT
= 0.14
= 1975
IK
IT
= 0.15
= 1425
IM
= 257
IM
= 205
NOV.
CLRNS=
TAV =
TRNG =
IK =
IT
=
IM
=
1
2
1.0 0.9
45
44
13
12
0.08
883
145
3
0.7
39
12
4
0.6
46
14
5
0.3
46
10
6
0.1
47
9
7
0.3
46
10
DEC.
1
CLRNS= 1.0
TAV = 30
TRNG = 14
IK
3
0.7
33
14
4
0.6
35
15
5
0.3
31
16
6
0.1
45
13
7
0.3
31
15
2
0.9
48
17
3
0.7
52
19
4
0.6
46
15
5
0.4
49
18
6
0.2
45
11
7
0.2
45
11
2
0.9
71
22
3
0.9
71
22
4
0.8
70
19
5
0.7
73
21
6
0.4
69
12
7
0.2
53
8
2
0.9
73
22
3
0.8
75
18
4
0.8
75
18
5
0.6
73
14
6
0.5
70
13
7
0.1
62
6
2
0.8
56
18
3
0.8
56
18
4
0.6
53
19
5
0.4
58
17
6
0.2
48
10
7
0.1
58
7
2
0.9
26
11
3
0.7
34
12
4
0.5
36
10
5
0.3
34
9
6
0.1
34
9
7
0.1
34
9
= 0.09
= 1252
= 194
IK
IT
MAY
1
CLRNS= 1.0
2
0.9
32
11
= 0.11
IT
= 730
IM
= 125
CARIBOU
1
JAN.
CLRNS= 1.0
TAV = 7
TRNG = 17
IK
= 0.22
IT
IM
= 679
2
0.8
7
27
3
0.7
8
24
4
0.5
6
13
5
0.4
16
17
6
0.3
16
20
7
0.1
27
18
2
0.8
10
23
3
0.6
9
25
4
0.5
14
21
5
0.5
14
21
6
0.4
16
27
7
0.1
33
19
2
0.9
33
20
3
0.9
33
20
4
0.6
36
21
5
0.4
38
12
6
0.4
38
12
7
0.2
36
6
2
0.9
64
27
3
0.8
61
28
4
0.7
60
23
5
0.5
58
18
6
0.5
58
18
7
0.3
57
13
2
AUG.
1
CLRNS= 1.0 0.9
TAV = 64 .65
28
TRNG = 27
3
0.8
59
22
4
0.7
64
24
5
0.6
60
23
6
0.3
59
16
7
0.1
59
12
2
0.7
40
21
3
0.6
46
12
4
0.4
43
12
5
0.3
43
13
6
0.1
45
10
7
0.1
45
10
2
0.9
18
21
3
0.7
7
20
4
0.5
16
20
5
0.4
15
18
6
0.2
28
11
7
0.1
21
21
IK
IT
IM
= 102
MAR.
CLRNS=
TAV =
TRNG =
IK
=
FEB.
1
CLRNS= 1.0
TAV = 1
TRNG = 25
2
1
1.0 0.8
28
25
24
21
0.07
3
0.8
25
21
4
0.6
26
15
5
0.6
26
15
6
0.4
22
14
7
0.1
29
9
= 0.11
= 1218
= 187
1
APR.
CLRNS= 1.0
TAV = 37
TRNG = 19
IT
= 1776
IK
IT
= 0.10
= 2152
IM
= 249
IM
= 288
MAY
1
CLRNS= 1.0
TAV = 59
TRNG = 32
IK
2
0.9
53
26
3
0.7
55
22
4
0.7
55
22
5
0.4
47
15
6
0.3
49
12
7
0.1
44
9
1
JUN.
CLRNS= 1.0
TAV = 67
TRNG = 27
= 0.14
= 2556
IK
= 0.17
IT
IT
= 2591
IM
= 316
IN
'
= 314
1
JUL.
CLRNS= 1.0
TAV = 69
TRNG = 28
2
0.9
66
22
3
0.9
66
22
4
0.7
64
18
6
5
0.5 .0.4
65
62
17
12
7
0.2
62
8
IK
IT
= 0.01
= 2532
IK
IT
= 0.07
= 2146
IM
= 304
IM
= 288
1
SEP.
CLRNS= 1.0
TAV = 57
TRNG = 21
IK
IT
= 0.22
= 1726
IM
=237
1
NOV.
CLRNS= 1.0
TAV = 31
TRNG = 16
2
0.9
52
23
3
0.8
55
24
4
0.6
53
19
5
0.4
54
24
6
0.2
55
10
7
0.1
55
15
OCT.
1
CLRNS= 1.0
TAV = 45
TRNG = 24
IK
IT
IM
2
0.7
29
15
3
0.5
29
13
4
0.4
29
10
5
0.3
39
13
6
0.1
33
10
7
0.2
32
13
= 0.16
= 1380
= 193
1
DEC.
CLRNS= 1.0
TAV = 10
TRNG = 14
IK
= 0.05
IT
= 772
IK
IT
= 0.10
= 551
IM
= 130
IM
= 93
CHARLESTON
JAN.
1
CLRNS= 1.0
TAV = 37
TRNG = 24
2
0.9
45
22
3
0.8
49
23
4
0.6
52
19
5
0.3
55
21
6
0.2
51
15
7
0.1
50
6
FEB.
1
CLRNS= 1.0
TAV = 43
TRNG = 22
IK
IT
= 0.20
= 1284
I
IT
= 0.16
= 1601
IM
= 202
IM
252
MAR.
1
CLRNS= 1.0
TAV =58
TRNG =23
2
0.9
52
17
3
0.9
52
17
4
0.8
53
24
5
0.6
65
23
6
0.5
59
18
7
0.1
59
16
APR.
1
CLRNS= 1.0
TAV = 63
TRNG = 26
IK
IT
= 0.08
= 1949
IK
= 0.10
IT
= 2435
IM
289
IM
= 330
MAY
1
CLRNS= 1.0
TAV = 69
TRNG = 20
2
0.9
72
19
3
0.9
72
19
4
0.8
70
19
5
0.7
71
18
6
0.~7
71
18
7
0.3
7215
JUN.
1
CLRNS= 1.0
TAV = 76
TRNG = 22
IK
IT
= 0.06
= 2425
IK
IT
a 0.04
= 2434
IM
= 328
IM
= 318
1
JUL.
CLRNS= 1.0
TAV = 81
TRNG = 18
IK
IT
IM
2
0.9
81
19
3
0.9
81
19
4
0.8
78
17
5
0.8
78
17
6
0.5
78
16
7
0.3
76
10
AUG.
1
CLRNS= 1.0
TAV = 81
TRNG = 16
= 0.05
= 2330
IK
IT
= 0.06
= 2054
= 305
IM
= 283
1
SEP.
CLRNS= 1.0
TAV = 74
TRNG = 23
2
0.9
76
19
3
0.9
76
19
4
0.8
73
17
5
0.7
77
19
6
0.6
75
16
7
0.3
73
11
1
OCT.
CLRNS= 1.0
TAV = 62
TRNG = 22
IK
IT
= 0.05
= 1899
IK
IT
= 0.09
= 1665
IM
= 278
IM
= 251
NOV.
1
CLRNS= 1.0
TAV = 53
TRNG = 22
2
0.9
54
22
3
0.9
54
22
4
0.8
57
24
5
0.8
57
24
6
0.6
63
19
7
0.4
53
19
1
DEC.
CLRNS= 1.0
TAV = 43
TRNG = 28
IK
IT
= 0.09
= 1260
IK
IM
= 213
IM
IT
100
= 0.12
= 1140
= 195
2
0.9
46
22
3
0.8
47
26
4
0.7
53
22
5
0.6
49
20
6
0.3
54
18
7
0.1
50
13
2
1.0
63
26
3
0.9
68
24
4
0.8
61
22
5
0.6
69
20
6
0.5
67
19
7
0.4
60
12
2
0.9
78
19
3
0.9
78
19
4
0.8
78
16
5
0.7
79
17
.6
0.5
72
13
7
0.4
68
12
2
1.0
81
16
3
0.9
78
17
4
0.9
78
17
5
0.8
79
14
6
0.6
78
13
7
0.2
71
8
2
1.0
62
22
3
0.9
58
24
4
0.7
67
20
5
0.7
67
20
6
0.4
68
12
7
0.1
67
6
2
1.0
43
28
3
0.8
48
24
4
0.7
53
24
5
0.5
50
19
6
0.2
52
20
7
0.1
56
11
COLUMBIA
1
JAN.
CLRNS= 1.0
TAV = 17
TRNG = 16
2
0.9
28
27
3
0.7
29
18
4
0.6
35
24
5
0.3
35
16
6
0.2
30
17
7
0.1
49
21
FEB.
1
CLRNS= 1.0
TAV = 38
TRNG = 23
IK
IT
= 0.08
= 1097
IK
IT
= 0.14
= 1437
IM
= 177
IM
= 222
1
MAR.
CL'INS= 1.0
TAV = 39
TRNG = 23
2
1.0
39
23
3
0.9
39
23
4
0.6
40
23
5
0.4
49
27
6
0.2
43
17
7
0.1
37
13
1
APR.
CLRNS= 1.0
TAV = 55
TRNG = 24
IK
IT
= 0.14
= 1859
IK
IT
= 0.18
= 2407
IM
= 273
IM
= 318
1
MAY
CLRNS= 1.0
TAV =65
TRNG =26
2
1.0
65
26
3
0.9
68
26
4
0.8
69
26
5
0.7
62
21
6
0.6
67
18
7
0.1
63
16
1
JUN.
CLRNS= 1.0
TAV = 75
TRNG = 23
IK
IT
= 0.12
= 2628
IK
IT
= 0.13
= 2686
IM
=334
IM
= 345
1
JUL.
CLRNS= 1.0
TAV = 77
TRNG = 25
2
1.0
77
25
3
0.9
77
24
4
0.9
77
24
5
0.8
78
21
6
0.7
76
19
7
0.3
75
14
1
AUG.
CLRNS= 1.0
TAV = 77
TRNG = 24
IK
IT
= 0.14
= 2568
IK
IT
= 0.08= 2421
IM
= 322
IM
= 315
1
SEP.
CLRNS= 1.0
TAV = 68
TRNG = 24
2
0.9
63
27
3
0.9
63
27
4
0.8
71
20
5
0.6
69
23
6
0.4
65
13
7
0.4
65
13
1
OCT.
CLRNS= 1.0
TAV = 51
TRNG = 26
IK
IT
= 0.06
= 1990
IK
IT
= 0.14
= 1579
IM
=-277
IM
= 234
2
1
NOV.
CLRNS= 1.0 0.9
45
TAV = 44
23
TRNG = 23
IK
= 0.16
= 1196
IT
IM = 187
3
0.7
55
23
4
0.7
55
23
5
0.4
48
16
6
0.2
36
8
7
0.2
36
8
101
1
DEC.
CLRNS= 1.0
TAV = 29
TRNG = 22
IK
= 0.20
IT
IM
= 960
= 162
2
0.9
22
19
3
0.9
22
19
4
0.6
29
12
5
0.3
35
20
6
0.1
37
14
7
0.3
35
20
2
1.0
55
24
3
0.8
63
28
4
0.7
53
19
5
0.6
59
20
6
0.2
45
12
7
0.2
45
12
2
1.0
75
23
3
0.9
74
17
4
0.7
74
18
5
0.7
74
18
6
0.4
73
16
7
0.5
66
11
2
1.0
77
24
3
0.9
76
24
4
0.9
76
24
5
0.8
77
21
6
0.5
77
18
67
9
2
0.9
52
27
3
0.9
52
27
4
0.8
59
25
5
0.5
59
22
6
0.4
61
15
7
0.1
60
17
2
0.8
26
20
3
0.7
34
24
4
0.5
35
17
5
0.5
35
17.
6
0.1
33
12
7
0.1
33
12
7
0.1
ELY
JAN.
1
CLRNS= 1.0
TAV = 24
TRNG = 30
IK
IT
IM
2
0.9
13
28
3
0.8
25
29
4
0.6
21
23
5
0.5
25
19
6
0.5
25
19
7
0.1
45
13
= 0.24
= 1219
= 193
MAR.
1
CLRNS= 1.0
TAV = 36
TRNG = 30
FEB.
1
CLRNS= 1.0
TAV = 29
TRNG = 27
IM
2
1.0
36
30
3
0.8
36
28
4
0.8
36
28
5
0.7
39
27
6
0.6
30
22
7
0.3
31
18
APR.
1
CLRNS= 1.0
TAV = 43
TRNG = 34
IK
IT
= 0.01
= 2615
IM
= 294
IM
= 341
= 0.19
= 2970
IM
= 364
1
JUL.
CLRNS= 1.0
TAV = 69
TRNG = 41
lK
= 0.12
IT
= 2933
IM
= 360
SEP.
1
CLRNS= 1.0
TAV = 58
TRNG = 34
IK
2
0.9
53
35
3
0.9
53
35
4
0.8
53
29
5
0.7
52
27
6
0.6
48
24
7
0.3
45
20
JUN.
1
CLRNS= 1.0
TAV = 62
TRNG = 38
IK
IT
IM
2
1.0
69
41
3
1.0
69
41
4
0.8
69
39
5
0.8
69
39
6
0.7
66
33
7
0.4
68
29
2
1.0
58
34
3
0.9
62
30
4
1.0
58
34
5
0.8
60
28
6
0.7
56
27
7
0.6
57
23
= 203
IM
= 203
2
1.0
43
34
3
0.9
47
34
4
0.8
43
31
5
0.7
40
18
6
0.5
39
17
7
0.4
33
10
2
1.0
62
38
3
1.0
62
38
4
0.9
61
32
5
0.9
61
32
6
0.7
54
28
7
0.6
52
20
2
1.0
65
35
3
1.0
65
35
4
0.8
67
29
5
0.9
71
28
6
0.6
66
28
7
0.5
63
20
2
1.0
46
33
3
0.8
43
33
4
0.9
43
38
5
0.8
43
33
6
0.6
49
26
7
0.3
43
22
2
0.9
21
24
3
0.9
21
24
4
0.8
21
22
5
0.6
34
17
6
0.4
27
24
7
0.1
33
6
= 364
OCT.
1
CLRNS= 1.0
TAV = 46
TRNG = 33
IM
IM
7
0.2
29
17
= 0.04
= 2646
IM = = 340
IK
IT
= 0.13
= 1277
6
0.6
25
16
IK
IT
= 0.11
= 2227
IK
IT
5
0.6
25
16
= 0.02
= 2883
AUG.
1
CLRNS= 1.0
TAV = 65
TRNG = 35
IT
NOV.
1
CLRNS= 1.0
TAV =.35
TRNG = 35
4
0.9
32
22
= 234
= 0.04
= 2137
IK
IT
3
0.9
32
22
IK
= 0.06
IT . = 1527
iK
IT
MAY
1
CLRNS= 1.0
TAV = 50
TRNG = 37
2
0.9
32
22
2
0.9
31
28
3
0.8
31
30
4
0.8
31
30
5
0.6
37
22
6
0.5
34
25
7
0.3
38
19
DEC.
1
CLRNS= 1.0
TAV = 11
TRNG = 29
IK
IT
IM
102
= 0.09
= 1791
= 176
= 0.05
= 1068
= 176
FORT WORTH
JAN.
1
CLRNS= 1.0
TAV = 45
TRNG'= 24
2
0.9
41
25
3
1.0
45
24
4
0.6
52
23
5
0.4
43
19
6
0.2
41
11
7
0.1
46
18
FEB.
1
CLRNS= 1.0
TAV = 54
TRNG = 33
IK
IT
= 0.11
= 1247
IK
IT
= 0.12
= 1644
IM
= 202
IM
= 260
MAR.
1
CLRNS= 1.0
TAV = 54
TRNG = 27
IK
IT
= 0.16
= 1994
IM
= 297
MAY
1
CLRNS= 1.0
TAV = 70
TRNG = 22
2
1.0
54
27
3
0.9
56
20
4
0.8
43
25
5
0.7
61
21
6
0.3
57
19
7
0.2
53
13
APR.
1
CLRNS= 1.0
TAV = 65
TRNG = 27
IK
IT
IM
2
0.9
75
19
3
0.9
57
19
4
0.8
71
20
5
0.8
71
20
6
0.4
71
13
7
0.2
63
11
JUN.
1
CLRNS= 1.0
TAV = 83
TRNG = 21
IK
IT
= 0.13
= 2726
IM
= 337
IM
= 343
3
1.0
86
22
4
0.9
86
21
5
0.9
86
21
6
0.8
88
20
7
0.4
84
15
AUG.
1
CLRNS= 1.0
TAV = 83
TRNG = 22
IK
IT
= 0.08
= 2513
IK
IT
= 0.09
= 2466
IM
= 330
IM
= 323
SEP.
1
CLRNS= 1.0
TAV = 83
TRNG = 24
2
0.9
75
22
3
0.9
75
22
4
0.9
75
22
5
0.7
72
18
6
0.6
72
18
7
0.5
69
16
OCT.
1
CLRNS= 1.0
TAV = 67
TRNG = 25
IK
IT
= 0.04
= 2079
IK
IT
= 0.10
= 1750
IM
= 307
IM
= 258
NOV.
CLRNS=
TAV =
TRNG =
(K =
1
1.0
61
26
2
0.9
58
25
3
0.9
58
25
4
0.8
54
21
5
0.6
57
17
6
0.3
55
10
7
0.3
55
10
DEC.
1
CLRNS= 1.0
TAV = 42
TRNG = 24
0.10
= 1335
IK
IT
IT
= 0.11
= 1172
IM
= 224
IM
= 200
103
4
0.8
47
20
5
0.4
53
16
6
0.2
49
14
7
0.3
40
10
2
1.0
65
27
3
0.9
60
24
4
0.7
67
18
5
0.5
62
16
6
0.2
64
12
7
0.2
64
12
2
1.0
83
21
3
0.9
81
20
4
0.8
82
19
5
0.8
82
19
6
0.7
76
17
7
0.4
77
13
2
1.0
83
22
3
0.9
85
24
4
0.9
85
24
5
0.8
86
21
6
0.7
81
17
7
0.4
82
12
2
1.0
67
25
3
0.9
63
28
4
0.9
63
28
5
0.7
72
17
6
0.4
71
15
7
0.1
67
13
2
1.0
42
24
3
0.9
51
27
4
0.7
47
19
5
0.5
47
18
6
0.2
53
13
7
0.1
46
8
= 328
= 0.12
= 2547
2
1.0
86
22
3
0.8
47
20
= 0.16
= 2385
IK
IT
JUL.
1
CLRNS= 1.0
TAV = 86
TRNG = 22
2
0.9
52
29
GREAT FALLS
1
JAN.
CLRNS= 1.0
TAV = 34
TRNG = 15
2
0.8
16
19
3
0.8
16
19
4
0.6
27
11
5
0.4
35
12
6
0.3
25
24
7
0.1
4
32
FEB.
1
CLRNS= 1.0
TAV = 29
TRNG = 23
IK
= 0.07
IK
= 0.03
IT
IM
= 724
= 104
IT
= 978
IM
= 166
1
MAR.
CLRNS= 1.0
TAV = 34
TRNG = 19
2
0.9
35
18
3
0.8
35
20
4
0.8
35
20
5
0.6
31
17
6
0.4
26
15
7
0.1
28
8
1
APR.
CLRNS= 1.0
TAV = 47
TRNG = 28
= 0.06
= 1707
IK
IT
= 0.06
!T
IM
= 229
IM
= 290
IK
MAY
CLRNS=
TAV =
TRNG =
IK =
1
2
1.0 0.9
57
61
32- 27
0.04
3
0.9
57
27
4
0.7
55
20
5
0.6
54
19
6
0.4
47
16
7
0.2
50
8
IT ~ = 2541
IM
= 315
1
JUL.
CLRNS= 1.0
TAV = 73
TRNG = 30
2
1.0
73
30
3
1.0
73
30
4
0.9
69
28
5
0.8
76
28
6
0.7
71
25
7
0.4
65
17
1
JUN.
CLRNS= 1.0
TAV = 65
TRNG = 26
IK
IT
= 0.15
= 2723
IM
= 337
1
AUG.
CLRNS= 1.0
TAV = 72
TRNG = 31
= 0.13
= 2721
IK
IT
= 0.14
= 2384
IM
= 328
IM
= 299
IK
IT
= 0.02
= 1867
IM
= 251
1
.NOV.
CLRNS= 1.0
TAV = 37
TRNG = 16
2
0.9
62
25
3
0.9
62
25
4
0.8
65
28
5
0.7
56
19
6
0.4
54
14
7
0.3
43
8
1
OCT.
CLRNS= 1.0
TAV = 54
TRNG = 28
IK
IT
IM
2
0.9
34
20
3
0.7
46
17
4
0.6
43
20
5
0.5
32
14
6
0.3
33
17
7
0.3
33
17
4
0.7
23
27
5
0.6
23
18
6
0.5
30
14
7
0.5
30
14
2
0.9
37
20
3
0.8
51
28
4
0.7
46
25
5
0.6
50
20
6
0.4
34
12
7
0.4
34
12
2
0.9
69
30
3
1.0
65
26
4
0.8
62
25
5
0.6
66
20
6
0.5
61
22
7
0.3
54
9
2
1.0
72
31
3
0.9
68
25
4
0.8
64
26
5
0.7
68
26
6
0.7
68
26
7
0.3
55
16
2
0.9
60
21
3
0.7
42
19
4
0.7
42
19
5
0.5
51
22
6
0.3
36
16
7
0.1
26
8
2
0.8
17
15
3
0.7
29
16
4
0.6
38
17
5
0.5
31
18
6
0.3
23
19
7
0.1
38
7
= 0.06
= 1447
= 198
1
DEC.
CLRNS= 1.0
TAV = 32
TRNG = 19
IK
= 0.03
IK
IT
= 796
IT
= 0.14
= 595
IM
= 123
IM
= 97
104
3
0.8
26
14
= 2099
lK
IT
1
SEP.
CLRNS= 1.0
TAV = 60
TRNG = 27
2
0.9
29
16
MAD ISON
JAN.
CLRNS=
TAV =
TRNG =
IK =
=
IT
IM =
2
1
1.0 0.8
-4
13
21
19
0.10
926
153
3
0.7
11
20
4
0.5
16
16
5
0.4
21
14
6
0.2
27
11
7
0.1
34
14
FEB.
CLRNS=
TAV =
TRNG =
IK
=
IT
=
IM =
1
2
1.0 0.9
13
14
21
20
0.10
1206
196
3
0.8
20
11
4
0.6
23
15
5
0.4
26
12
6
0.4
26
12
7
0.3
27
6
MAR.
CLRNS=
TAV =
TRNG =
IK =
IT =
IM =
1
2
1.0 0.9
17
27
16
22
0.12
1805
275
3
0.9
27
22
4
0.6
33
19
5
0.5
31
13
6
0.2
31
17
7
0.1
33
13
APR.
CLRNS=
TAV =
TRNG =
IK =
IT
=
IM =
1
2
1.0 0.9
47
44
30
25
0.19
2197
301
3
0.7
50
27
4
0.6
50
20
5
0.5
50
20
6
0.3
47
12
7
0.3
47
12
1
2
MAY
CLRNS= 1.0 0.9
TAV =60
65
28
TRNG = 28
IK = 0.11
IT = 2568
IM = 318
3
0.8
61
26
4
0.8
61
26
5
0.5
58
22
6
0.4
54
17
7
0.1
50
10
JUN.
CLRNS=
TAV =
TRNG =
IK =
IT
=
IM =
1
2
1.0 0.9
66
71
23
25
0.12
2504
323
3
0.9
71
25
4
0.8
74
19
5
0.6
66
20
6
0.5
62
16
7
0.5
62
16
1
2
JUL.
CLRNS= 1.0 1.0
TAV =73
73
24
TRNG =24
IK = 0.01
IT = 2526
IM =320
3
0.9
73
26
4
0.8
73
19
5
0.8
73
19
6
0.5
70
14
7
0.2
67
11
AUG.
CLRNS=
TAV =
TRNG =
IK =
IT
=
IM =
1
2
1.0 0.9
68
66
24
26
0.062215
289
3
1.0
68
24
4
0.8
68
23
5
0.8
68
23
6
0.6
71
19
7
0.2
67
15
SEP.
CLRNS=
TAV =
TRNG =
IK =
IT
=
IM =
2
1
1.0 0.9
61
62
24
26
0.10
1691
252
3
0.9
62
24
4
0.9
62
24
5
0.7
70
21
6
0.5
60
24
7
0.3
65
14
OCT.
CLRNS=
TAV =
TRNG =
IK =
IT
=
IM =
1
2
1.0 0.9
45
48
29
25
0.10
1461
213
3
0.9
48
25
4
0.6
57
23
5
0.3
52
17
6
0.3
52
17
7
0.1
53
23
OV.
CLRNS=
TAV =
TRNG =
IK =
=
IT
IM =
1
2
1.0 0.8
39
37
22
21
0.10
1013
160
3
0.6
30
14
4
0.4
31
14
5
0.2
38
11
6
0.1
39
15
7
0.2
38
11
DEC.
CLRNS=
TAV =
TRNG =
IK =
IT
=
IM =
1
2
1.0 0.9
23
22
19
21
0.12
731
125
3
0.7
22
15
4
0.5
27
17
5
0.3
27
14
6
0.1
28
9
7
0.1
28
9
105
MIAMI
JAN.
CLRNS=
TAV =
TRNG =
IK
2
1
1.0 0.9
65
70
18
16
0.08
IT
=
1490
IM
=238
1
MAR.
CLRNS= 1.0
TAV = 75
TRNG = 14
IK
IT
= 0.13
= 2094
IM
=
2
1.0
75
14
3
0.9
70
16
3
0.9
74
11
4
0.7
68
16
4
0.8
71
14
5
0.6
68
16
5
0.7
73
12
6
0.5
74
12
6
0.6
71
11
7
0.2
64
13
7
0.2
72
8
306
FEB.
1
2
3
4
5
6
7
1.0
63
19
0.8
73
14
0.8
73
14
0.7
74
13
0.6
71
11
0.5
69
16
1
2
1.0 1.0
75
75
14
14
0.06
3
0.9
75
12
4
0.9
75
12
5
0.8
73
13
6
0.7
76
15
7
0.6
74
13
CLRNS= 1.0
TAV = 63
TRNG = 19
IK
IT
= 0.08
= 1712
IM
= 274
APR.
CLRNS=
TAV =
TRNG =
IK =
IT
= 2352
IM
= 329
3
0.9
78
4
0.8
77
5
0.7
79
6
0.6
77
7
0.2
77
TRNG = 13
14
IK
= 0.01
IT
= 2496
IM = 347
14
11
10
10
8
1
JUL.
CLRNS= 1.0
TAV = 82
TRNG = 14
2
0.9
82
14
3
0.9
82
14
4
0.9
82
14
5
0.7
80
14
6
0.7
80
14
7
0.4
79
11
2
0.9
82
11
3
0.9
82
11
4
0.9
82
11
5
0.7
82
11
6
0.6
80
10
7
0.6
80
10
OCT.
1
CLRNS= 1.0
1
MAY
CLRNS= 1.0
TAV = 78
!K
= 0.04
IT
IM
= 2297
2
0.9
73
TRNG = 12
13
IK
= 0.06
IT
= 1458
IM
= 242
2
3
4
5
6
7
0.9
81
13
0.9
81
13
0.8
81
14
0.7
80
15
0.5
80
10
0.4
81
7
AUG.
1
CLRNS= 1.0
2
0.9
3
0.9
4
0.9
5
0.8
6
0.7
7
0.5
TAV
= 84
83
83
83
85
82
81
TRNG
IK
IT
IM
= 13
12
= 0.08
= 2214
= 290
12
12
12
9
13
2
0.9
3
0.9
4
0.7
5
0.7
6
0.5
7
0.1
= 78
76
76
77
77
79
74
TRNG = 13
12
12
11
11
8
6
IT
IM
= 0.03
= 1961
= 283
1
NOV.
CLRNS= 1.0
TAV = 74
JUN.
1
CLRNS= 1.0
TAV = 82
TRNG = 15
IK
= 306
1
SEP.
CLRNS= 1.0
TAV = 82
TRNG = 13
IK
IT
IM
2
0.9
78
TAV
= 0.10
= 2388
= 313
IK
= 0.04
IT
= 1873
IM
= 276
3
0.8
73
4
0.8
73
5
0.8
73
6
0.7
73
7
0.6
73
1
DEC.
CLRNS= 1.0
TAV =.57
2
1.0
57
3
0.8
72
4
0.8
72
5
0.6
69
6
0.7
70
7
0.3
72
14
14
14
13
12
TRNG = 22
22
14
14
16
14
14
106
IK
=.0.11
IT
IM
= 1333
= 220
NASHVILLE
1
JAN.
CLRNS= 1.0
TAV = 30
TRNG = 19
lK
IT
IM
IK
IT
= 0.16
= 1894
IM
= 279
1
MAY
CLRNS= 1.0
TAV = 61
TRNG = 24
IK
IT
= 0.10
= 2535
IM
= 338
1
JUL.
CLRNS= 1.0
TAV = 80
TRNG = 21
IM
IT
IM
IT
IM
5
0.2
47
12
6
0.1
41
12
7
0.1
41
12
FEB.
1
CLRNS= 1.0
TAV = 36
TRNG = 24
IK
IT
IM
2
0.9
47
27
3
0.9
47
27
4
0.6
52
22
5
0.3
48
13
6
0.2
53
17
7
0.1
52
15
IT
IM
2
0.9
70
27
3
0.9
70
27
4
0.8
69
26
5
0.6
74
16
6
0.4
65
17
7
0.1
66
9
2
1.0
80
21
3
0.9
79
18
4
0.8
79
19
5
0.8
79
19
6
0.7
75
15
7
0.3
77
14
2
1.-0
72
26
3
0.8
71
22
4
0.8
71
22
5
0.6
73
23
6
0.4
72
14
7
0.3
67
11
= 280
2
0.8
52
23
3
0.8
52
23
4
0.6
52
19
5
Q.3
61
15
6
0.2
50
14
= 0.11
= 1226
= 195
7
0.1
48
10
IM
= 327
1
OCT.
CLRNS= 1.0
TAV = 57
TRNG = 29
IM
107
7
0.2
46
17
2
1.0
58
27
3
0.8
58
25
4
0.8
58
25
5
0.7
62
23
6
0.4
59
17
7
0.4
59
17
2
0.9
77
22
3
0.9
77
22
4
0.9
77
22
5
0.8
75
20
6
0.7
78
16
7
0.5
74
15
2
0.9
77
21
3
0.9
77
21
4
0.8
78
20
5
0.8
78
20
6
0.6
76
15
7
0.4
77
16
2
0.9
59
22
3
0.9
59
22
4
0.8
64
29
5
0.6
61
17
6
0.3
66
13
7
0.2
57
10
2
0.9
35
23
3
0.8
42
20
4
0.4
33
14
5
0.2
55
12
6
0.1
42
9
7
0.1
42
9
= 0.12
= 1574
= 236
1
DEC.
CLRNS= 1.0
TAV = 38
TRNG = 23
lK
6
0.2
46
17
= 0.09
= 2454
= 329
= 0.04= 2223
IT
5
0.3
44
18
= 311
IK
IT
IT
IM
4
0.5
45
20
= 0.15
= 2184
AUG.
1
CLRNS= 1.0
TAV = 75
TRNG = 20
IK
3
0.7
46
23
= 231
1
JUN.
CLRNS= 1.0
TAV = 70
TRNG = 26
IK
IT
IM
2
0.3
35
27
= 0.15
= 1436
ArR.
1
CLRNS= 1.0
TAV = 58
TRNG = 27
IK
= 0.12
= 1980
1
NOV.
CLRNS= 1.0
TAV = 42
TRNG = 19
IK
4
0.5
42
21
= 0.01
= 2401
= 309
1
SEP.
CLRNS= 1.0
TAV = 72
TRNG = 26
IK
3
0.7
41
25
= 0.04
= 1088
= 178
1
MAR.
CLRNS= 1.0
TAV = 43
TRNG = 24
IK
IT
2
0.9
38
22
= 0.02
= 1014
= 178
NEW YORK
1
JAN.
CLRNS= 1.0
TAV = 28
TRNG = 13
2
0.9
23
13
3
0.7
32
16
4
0.5
32
9
5
0.2
36
7
6
0.2
36
7
7
0.1
38
9
1
FEB.
CLRNS= 1.0
TAV = 23
TRNG = 17
IK
= 0.08
IK
IT
= 918
IM
= 152
IT
IM
1
MAR.
CLRNS= 1.0
TAV = 34
TRNG = 14
2
0.9
39
18
3
0.8
42
17
4
0.7
41
15
5
0.4
39
12
6
0.1
41
11
7
0.1
41
11
= 0.10
IK
IT
IM
= 1729
= 248
IT
1
MAY
CLRNS= 1.0
TAV = 59
TRNG = 13
lK
IT
IM
1
1.0
76
15
IT
IM
3
0.8
61
14
4
0.8
61
14
5
0.5
59
9
6
0.4
59
12
7
0.1
59
7
IT
IM
2
0.9
73
17
3
0.8
75
17
4
0.7
72
15
5
0.6
73
15
6
0.4
76
13
7
0.1
70
12
IT
1M
2
0.9
63
18
3
0.8
66
15
4
0.7
68
16
5
0.6
72
15
6
0.2
66
12
7
0.1
63
10
IM
= 262
1
NOV.
CLRNS= 1.0
TAV = 43
TRNG = 9
2
0.8
43
12
3
0.6
50
18
4
0.5
45
13
5
0.3
48
10
6
0.2
52
12
7
0.1
51
10
2
0.9
55
16
3
0.8
47
18
4
0.6
55
12
5
0.5
60
13
6
0.2
50
10
7
0.3
47
9
2
0.9
68
16
3
0.9
68
16
4
0.8
71
20
5
0.6
68
15
6
0.5
67
17
7
0.2
66
9
2
1.0
73
14
3
0.8
76
13
4
0.8
76
13
5
0.7
75
12
6
0.5
77
13
7
0.2
71
9
2
0.9
54
13
3
0.7
57
16
4
0.6
55
15
5
0.4
60
16
6
0.3
58
12
7
0.1
62
12
2
0.8
39
12
3
0.7
33
13
4
0.4
36
11
5
0.2
36
12
6
0.1
39
11
7
0.1
39
11
= 0.16
= 1442
= 220
1
DEC.
CLRNS= 1.0
TAV = 37
TRNG = 14
= 0.08
= 0.07
IK
IT
IM
= 993
IT
= 827
=
IM
= 143
108
7
0.1
34
11
= 0.04
= 2025
= 281
IK
164
6
0.2
40
12
= 0.09
= 2388
= 317
1
OCT.
CLRNS= 1.0
TAV = 58
TRNG = 15
IK
IT
= 0.09
= 1851
5
0.4
33
15
= 0.15
= 2168
= 301
1
AUG.
CLRNS= 1.0
TAV = 73
TPNG = 14
IK
4
0.5
37
15
= 207
1
JUN.
CLRNS= 1.0
TAV = 66
TRNG = 17
IK
0.04
2449
= 325
1
SEP.
CLRNS= 1.0
TAV = 66
TRNG = 15
IK
2
1.0
59
13
= 0.11
= 2421
= 326
JUL.
CLRNS=
TAV =
TRNG =
=
IK
IT
=
QI
lM
3
0.7
31
19
= 0.19
= 1246
1
APR.
CLRNS= 1.0
TAV = 51
TRNG = 14
IK
2
0.8
28
17
PHOENIX
JAN.
1
CLRNS= 1.0
TAV = 55
TRNG = 26
iK
IT
IM
IT
IM
5
0.8
50
22
6
0.7
52
25
7
0.2
51
13
FEB.
1
CLRNS= 1.0
TAV = 54
TRNG = 29
IT
= 0.03
= 1654
= 213
IM
= 268
2
1.0
65
32
3
0.9
59
29
4
0.9
59
29
5
0.9
59
29
6
0.7
60
29
7
0.3
64
17
APR.
1
CLRNS= 1.0
TAV = 70
TRNG = 27
= 0.07
= 2178
IK
IT
= 0.05
= 2639
= 312
IM
= 348
1
1.0
79
42
2
1.0
79
42
3
1.0
79
42
4
1.0
79
42
5
0.9
80
30
6
0.9
80
30
7
0.7
75
26
0.00
= 2906
= 369
1
JUL.
CLRNS= 1.0
TAV = 93
TRNG = 25
IK
4
0.8
50
22
IK
MAY
CLRNS=
TAV =
TRNG =
IK
=
IT
IM
3
0.9
53
27
= 0.04
= 1312
1
MAR.
CLRNS= 1.0
TAV = 65
TRNG = 32
IK
2
1.0
55
26
JUN.
1
CLRNS= 1.0
TAV = 88
TRNG = 30
lK
IT
IM
2
1.0
93
25
3
1.0
93
25
4
0.9
96
20
5
0.9
96
20
6
0.8
90
18
7
0.5
89
17
= 0.04
= 2838
IK
IM
= 354
IM
1
SEP.
CLRNS= 1.0
TAV = 87
TRNG = 24
IK
IT
= 0.02
= 2183
IM
= 311
NOV.
1
CLRNS= 1.0
TAV = 63
TRNG = 22
IT
2
1.0
87
24
3
1.0
87
24
4
0.9
84
24
5
0.9
84
24
6
0.9
84
24
7
0.9
84
24
IT
IM
2
0.9
61
23
3
0.9
61
23
4
0.9
61
23
5
0.8
58
24
6
0.8
58
24
7
0.6
63
13
6
0.6
55
21
7
0.6
55
21
2
1.0
70
27
3
1.0
70
27
4
1.0
70
27
5
0.9
69
28
6
0.9
69
28
7
0.6
56
17
2
1.0
88
30
3
1.0
88
30
4
0.9
88
27
5
1.0
88
30
6
0.9
88
27
7
0.8
90
23
2
1.0
92
22
3
1.0
92
22
4
1.0
92
22
5
0.9
88
21
6
0.9
88
21
2
1.0
76
27
3
0.9
71
32
4
0.9
71
32
5
0.9
71
32
6
0.8
72
31
7
0.4
71
21
2
1.0
51
27
3
1.0
51
27
4
0.9
48
30
5
0.8
56
27
6
0.7
58
23
7
0.2
49
16
7
0.4
88
20
= 273
1
DEC.
CLRNS= 1.0
TAV = 51
TRNG = 27
= 0.04
= 1364
IK
IT
= 0.01
= 1226
IM
= 240
IM
= 202
109
5
0.9
54
25
= 0.04
= 1870
IT
IK
4
0.8
54
24
= 0.04
= 2580
= 333
OCT.
1
CLRNS= 1.0
TAV = 76
TRNG = 27
IK
3
0.9
54
25
= 0.02
= 2919
= 373
AUG.
1
CLRNS= 1.0
TAV = 92
TRNG = 22
IT
2
1.0
54
29
SANTA MARIA
JAN.
1
CLRNS= 1.0
TAV = 44
TRNG = 29
IK
IT
IM
2
1.0
44
29
3
0.9
48
33
4
0.8
47
26
5
0.7
53
19
6
0.4
53
13
7
0.2
54
14
= 0.10
= 1164
= 194
MAR.
1
CLRNS= 1.0
TAV = 52
TRNG = 24
2
1.0
52
24
3
0.9
55
19
4
0.8
55
23
5
0.7
53
12
6
0.6
53
17
7
0.2
51
10
FEB.
1
CLRNS= 1.0
TAV = 55
TRNG = 32
IK
IT
= 0.15
= 1657
IM
= 250
APR.
1
CLRNS= 1.0
TAV = 56
TRNG = 27
IK
IT
= 0.15
= 2031
IK
IM
= 286
IM
MAY
1
CLRNS= 1.0
TAV = 57
TRNG = 24
IK
IT
IM
IT
2
1.0
57
24
3
0.9
56
17
IM
3
0.9
60
21
5
0.9
61
21
6
0.8
61
20
7
0.5
60
17
IM
4
0.9
60
21
5
0.9
60
21
6
0.8
59
14
7
0.3
61
11
1T
IM
= 292
2
1.0
54
23
3
0.9
57
26
4
0.9
57
26
5
0.8
53
20
6
0.6
56
21
15
= 0.06
= 1190
= 197
IT
IM
110
6
0.4
51
15
7
0.1
55
12
2
1.0
56
27
3
0.9
53
21
4
0.9
53
21
5
0.9
53
21
6
0.6
53
14
7
0.4
54
14
2
1.0
57
20
3
0.9
57
17
4
1.0
57
20
5
0.9
57
17
6
0.8
55
17
7
0.8
55
17
2
1.0
61
.21
3
1.0
61
21
4
0.9
61
19
5
0.9
61
19
6
0.9
61
19
7
0.5
59
15
2
0.9
57
18
3
1.0
59
24
4
0.8
57
25
5
0.8
57
25
6
0.7
61
19
7
0.4
58
11
2
1.0
49
30
3
0.9
53
27
4
0.9
53
27
5
0.7
50
21
6
0.6
52
17
7
0.2
57
11
= 0.13
= 1615
= 250
DEC.
1
CLRNS= 1.0
TAV = 49
TRNG = 30
IK
5
0.6
53
21
= 0.11
= 2369
= 316
OCT.
1
CLRNS= 1.0
TAV = 59
TRNG = 24
IK
4
0.7
49
24
= 0.09
= 2642
= 343
AUG.
1
CLRNS= 1.0
TAV = 61
TRNG = 21
IK
IT
= 0.11
= 2051
NOV.
1
CLRNS= 1.0
TAV = 54
TRNG = 23
IM
4
1.0
61
22
3
0.8
48
24
= 0.10
= 2420
= 320
JUN.
1
CLRNS= 1.0
TAV = 57
TRNG = 20
IT
2
1.0
62
25
IT
7
0.2
55
13
= 340
SEP.
1
CLRNS= 1.0
TAV = 62
TRNG = 25
IK
6
0.5
56
12
IK
3
0.9
61
21
IK
5
0.8
57
16
= 0.19
= 2720
1
2
JUL.
CLRNS= 1.0 1.0
TAV = 61
61
TRNG = 22
22
IK
= 0.12
IT
= 2652
!M = 338
IT
IM
4
0.8
57
16
2
0.9
49
25
= 0.10
= 1043
= 181
SEATTLE
1
JAN.
CLRNS= 1.0
TAV = 33
TRNG = 7
2
0.7
41
10
3
0.3
39
7
4
0.3
39
7
5
0.3
39
7
6
0.2
39
5
7
0.1
42
3
2
0.7
39
11
3
0.4
45
8
4
0.4
45
8
5
0.2
44
7
6
0.2
44
7
7
0.3
43
7
2
0.9
46
15
3
0.8
45
14
4
0.5
47
10
5
0.6
48
14
6
0.3
45
10
7
0.5
47
10
2
1.0
61
20
3
0.8
60
15
4
0.7
59
15
5
0.6
59
16
6
0.5
56
12
7
0.4
57
8
AUG.
1
2
CLRNS= 1.0 1.0
67
TAV = 67
TRNG = 22 .22
3
0.9
66
20
4
0.8
63
18
5
0.7
61
14
6
0.4
60
9
7
0.3
61
9
2
0.8
52
14
3
0.6
49
17
4
0.4
51
12
5
0.2
51
10
6
0.2
51
10
7
0.1
48
7
2
0.6
43
8
3
0.3
38
8
4
0.3
38
8
5
0.2
41
9
6
0.1
44
8
7
0.1
44
8
FEB.
1
CLRNS= 1.0
TAV = 37
TRNG = 12
IK
= 0.01
IK'
= 0.01
IT
IM
= 629
= 88
IT
= 968
IM
= 148
2
0.8
3
0.6
4
0.5
5
0.3
6
0.3
7
0.1
= 50
46
41
40
43
43
38
TRNG = 25
19
13
12
9
9
7
1
MAR.
CLRNS= 1.0
TAV
1
APR.
CLRNS= 1.0
TAV = 50
TRNG = 21
IK
IT
= 0.22
= 1450
IK
IT
= 0.14
= 1837
IM
= 222
IM
= 258
1
MAY
CLRNS= 1.0
TAV = 60
TRNG = 24
2
1.0
60
24
3
0.8
52
17
4
0.7
53
14
5
0.5
49
12
6
0.3
50
10
7
0.2
49
8
1
JUN.
CLRNS= 1.0
TAV = 61
TRNG = 20
IK
IT
= 0.18
= 2459
IK
= 0.11
IT
= 2395
IM
= 291
IM
= 305
1
JUL.
CLRNS= 1.0
TAV = 69
TRNG = 26
IK
IT
IM
2
1.0
69
26
3
0.9
64
23
4
0.9
64
23
5
0.7
58
17
6
0.6
58
16
7
0.2
56
9
= 0.12
= 2566
= 306
1
SEP.
CLRNS= 1.0
TAV = 66
TRNG = 28
IK
iT
IM
2
0.9
59
24
3
0.8
59
21
4
0.7
58
18
5
0.5
57
15
6
0.3
57
8
7
0.3
57
8
= 0.25
= 1591
IK
IM
= 230
IM
IT
2
0.7
48
9
3
0.4
47
9
4
0.4
47
9
5
0.3
46
7
6
0.2
46
8
7
0.2
46
8
= 0.06
IK
IT
IM
= 699
IT
IM
ill
= 0.21
1243
= 177
.=
1
DEC.
CLRNS= 1.0
TAV = 33
TRNG = 15
IK
= 101
= 277
1
OCT.
CLRNS= 1.0
TAV = 56
TRNG = 19
IK
IT
1
NOV.
CLRNS= 1.0
TAV = 46
TRNG = 13
= 0.09
= 2184
= 0.01
= 541
= 86
WASHINGTON D.C.
JAN.
1
CLRNS= 1.0
TAV = 26
TRNG = 20
2
0.9
29
23
3
0.8
33
19
4
0.7
30
21
5
0.3
22
16
6
0.2
42
18
7
0.1
31
15
FEB.
1
CLRNS= 1.0
TAV = 32
TRNG = 26
IK
= 0.12
IK
IT
IM
= 953
= 163
IT
= 0.14
= 1371
IM
= 215
MAR.
1
CLRNS= 1.0
TAV = 41
TRNG = 25
2
0.9
41
23
3
0.8
37
23
4
0.7
52
28
5
0.5
49
25
6
0.3
42
21
7
0.1
42
10
APR.
1
CLRNS= 1.0
TAV = 49
TRNG = 24
IK
IT
= 0.18
= 1748
IK
IT
= 0.17
= 2258
IM
= 263
IM
= 298
MAY
1
CLRNS= 1.0
TAV = 61
TRNG = 22
2
1.0
61
22
3
0.8
67
24
4
0.8
67
24
5
0.6
67
25
6
0.4
61
13
7
0.1
62
11
JUN.
1
CLRNS- 1.0
TAV = 70
TRNG = 29
IK
IT
= 0.10
= 2475
IK
IT
= 0.14
= 2490
IM
= 318
IM
= 322
JUL.
1
CLRNS= 1.0
TAV = 77
TRNG = 26
2
0.9
75
21
3
0.9
75
21
4
0.8
77
19
5
0.7
77
19
6
0.4
76
18
7
0.3
74
10
AUG.
1
CLRNS= 1.0
TAV= = 71
TRNG = 26
IK
IT
= 0.00
= 2424
IK
IT
= 0.14
= 2266
IM
= 291
IM
= 298
1
SEP.
CLRNS= 1.0
TAV = 68
TRNG = 23
IK
IT
= 0.16
= 1858
IM
= 264
NOV.
1
CLRNS= 1.0
TAV = 50
TRNG = 23
IK
IT
IM
2
0.9
69
24
3
0.9
69
24
4
0.7
73
21
5
0.6
69
19
6
0.4
70
17
7
0.2
67
10
OCT.
1
CLRNS= 1.0
TAV = 53
TRNG = 33
IK
IT
IM
2
0.9
43
25
3
0.7
48
29
4
0.5
45
23
5
0.4
48
19
6
0.2
43
17
7
0.3
52
13
= 0.16
= 1064
= 178
112
2
0.9
32
27
3
0.8
34
27
4
0.6
32
17
5
0.3
33
12
6
0.2
36
21
7
0.1
33
14
2
1.0
49
24
3
0.8
60
29
4
0.7
63
20
5
0.5
61
21
6
0.3
53
19
7
0.3
53
19
2
1.0
70
29
3
0.8
71
25
4
0.9
70
23
5
0.7
74
22
6
0.5
69
19
7
0.4
68
13
2
0.9
75
24
3
0.9
75
24
4
0.7
76
21
5
0.7
76
21
6
0.6
74
21
7
0.3
75
13
2
1.0
53
33
3
0.8
59
25
4
0.8
59
25
5
0.6
56
19
6
0.2
60
12
7
0.1
56
11
2
0.9
37
16
3
0.8
35
17
4
0.5
38
16
5
0.4
39
11
6
0.1
37
7
7
0.1
37
7
= 0.07
= 1511
= 222
DEC.
1
CLRNS= 1.0
TAV = 36
TRNG = 13
IK
= 0.16
IT
= 823
IM
= 151
APPENDIX D
MODIFIED SUNPULSE ROUTINES
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
170
180
190
200
210
220
230
240
250
260
270
280
290
300
310
320
330
340
350
360
370
380
390
400
410
420
430
'THIS PROGRAM CALCULATES HOURLY SOLAR GAIN PER SQ.FT. OF RECEIVING
SURFACE AT ANY TILT & AZIMUTH
DEF FNARCCOS (Y)=-ATN (Y/SQR(-Y*Y+1))+1.5708
PI=3.1415927
RAD=57.2958
TILT=90
AZIMUTH=00
GREFLECT=.3
READ CITY$, LATD
FOR MNTH=1 TO 12
READ ITIMIKDA
'DA=RECOMMENDED AVERAGE DAY OF THE MONTH FROM APPENDIX A
DECD=23.45*SIN(.01721418*(284+DA))
DECR=DECD/RAD
LATR=LATD/RAD
TILTR=TILT/RAD
AZIMUTHR=AZIMUTH/RAD
ALSD=IT*PI/(2*IM)
ASR=12-(ALSD/2)
ASS=12+(ALSD/2)
FOR SIMDAY=1 TO 7
READ CLRNS
GOSUB 330
FOR HOUR=1 TO 24
IF HR<FIX(ASR) OR HR>FIX(ASS) THEN QSH=0:GOTO 260 ELSE GOSUB 430
GOSUB 580
NEXT HOUR
NEXT SIMDAY
NEXT MNTH
END
'
'THIS SUBROUTINE SETS THE DAILY AMPLITUDE & HOUR OF CLOUDY FRONT
'
CIM=IM*CLRNS*(1+(IK*SIN(PI*CLRNS)))
CFIM=IM*CLRNS* (1- (IK*4*SIN (PI*CLRNS)))
IF
IK>0
AND
CLRNS<.9
AND
CLRNS
>.2
THEN
CFHNGL
= ( (IT*CIM/IM*PI/ALSD)-IM-CFIM)/(CFIM-IM): MORNFRNT=CINT (RND)
ELSE CFHNGL=0
IF CFHNGL>1 THEN CFHNGL=1
IF CFHNGL THEN GOTO 380 ELSE GOTO 390
IF MORNFRNT THEN FHASR+((FNARCCOS(CFHNGL))*(ALSD/PI)) ELSE
FH=ASS- ( (FNARCCOS (CFHNGL) )* (ALSD/PI))
RETURN
'
'THIS SUBROUTINE CALCULATES THE HOURLY HORIZONTAL INCIDENT SOLAR
ENERGY (QSH)
'
IF FH AND HR<FH AND MORNFRNT=1 THEN CIM=IM
113
440 IF FH AND HR<FH AND MORNFRNT=0 THEN CIM=CFIM
HR<FH
AND
HR+1FH
AND
450
IF
FH
AND
MORNFRNT=0
THEN
CIM=(FH-HR)*IM+(HR+1-FH)*CFIM
460
470
480
490
500
510
520
530
540
550
560
570
580
590
600
610
620
630
640
650
660
670
680
690
700
710
720
730
IF
FH
AND
HR<FH
AND
HR+1>FH
AND
MORNFRNT=0
THEN
CIM=(FH-HR)*CFIM+(HR+1-FH)*IM
IF FH AND HR>FH AND MORNFRNT=1 THEN CIM=CFIM:FH=O
IF FH AND HR>FH AND MORNFRNT=0 THEN CIM=IM:FH=0
IF HR>ASR AND HR+1>ASR THEN 520 ELSE 500
IF HR<ASS AND HR+1>ASS THEN 530 ELSE 510
IF HR>ASR AND HR<ASS THEN 520 ELSE RETURN
QSH=(-CIM*(COS((HR+1-ASR)*PI/ALSD))+CIM)*ALSD/PI:RETURN
QSH=CIM+CIM*COS ((HR-ASR)*PI/ALSD) ) *ALSD/PI: RETURN
QSH= (-CIM*CCS ( (HR+1-ASR) PI/ALSD) ) +CIM*COS ( (HR-ASR)
*PI/ALSD))*ALSD/PI:RETURN
'
'THIS SUBROUTINE CALCULATES HOURLY INCIDENT SOLAR ENERGY (QSI) ON
THE TILTED SURFACE
'
IF HR<ASR AND HR+1>ASR THEN W1=(ASR-12)*.2618 ELSE IF HR>ASR AND
HR<ASS THEN W1=(HR-12)*.2618
IF HR+1<ASS
THEN W2=(HR-11)*.2618
ELSE
IF
HR+1>ASS
THEN
W2=(ASS-12)*.2618
CZNGL=COS (DECR)*COS (LATR) *COS ((W1+W2)/2+SIN (DECR)*SIN (LATR)
CINC=SIN (DECR) *SIN (LATR) *COS (TI LTR) -SIN (DECR) *COS (LATR)
*SIN (TI LTR) *COS (AZMUTHR)+COS (DECR) *COS (LATR) *COS (TI LTR)
*COS ((W1+W2) /2) +COS (DECR) *SIN (LATR) *SIN (TILTR) *COS (AZMUTHR)
*COS ( (W1+W2)/2)+COS (DECR)*SIN (TILTR) *SIN (AZMUTHR)*SIN ( (W1+W2)/2)
IF CINC<0 THEN CINC=0
RB=CINC/CZNGL
I0=1637.7716*(1+.033*COS (.0172142*DA) )*(COS (LATR)*COS (DECR)* (SIN (W2)
- SIN (Wl))+((W2-Wl) *SIN (LATR)*SIN (DECR)))
KT=QSH/I0
IF KT<0 THEN IDI=1
IF KT>0 AND KT<.35 THEN IDI=1-.249*KT
IF KT .35 AND KT<.75 THEN IDI=1.557-1.84*KT
IF KT .75 AND KT<.9 THEN IDI=.177
IF KT>.9 THEN IF CZNGL<THEN IDI=1 ELSE IF CZNGL>.12 AND CZNGL<.42
THEN IDI=.15
ID=IDI*QSH: IB=QSH-ID
QSI=IB*RB+ID*( (1+COS(TILTR) )/2)+(IB+ID)*GREFLECT*( (1-COS(TILTR) )/2)
RETURN
114
APPENDIX E
ENERGY BALANCE EQUATIONS
NODAL EQUATIONS
UAW(TA-Tout) + H(TA-TR)
UAR(TR-TSI) + H(TR-Ta)
CA(TAI-TA) + 0.40SSOL
a
CR(TRI-TR) + 0.60SSOL
UAS(TS1-TS2) + UAR(TS1-TR) = O.5CSCTS11-TS1)
UAS(TS2-TS1) = O.5CS(TS21-TS2)
NODAL DIAGRAM
TERMS:
TM
= Outdoor air temperature
UAW
- Total conductance of Weather Wall and infiltration Btu/hr 07
TA i
= Indoor Air Temperature Last Hour OF
TA
a Indoor Air Temperature in Current Hour OF
CA
= Heat Capacity of Air (for sheetrock and furniture) Btu/hr OF
TR 1
= Rug Temoerature Last Hour OF
TR
= Rug Temperature Current Hour
UAR
= Total Conductance of Rug (Rug area x U rug) Btu/hr OF
H
a Total Surface Film Conductance of Rug (Rug area x I rug) BTU/hr OF
CR
= Heat Capacity of Rug Btu/OF
1311
3 Temperature of top 2" of Slab Last Hour OF
0F
TS 1 = Temperature of top 2" of Slab Current Hour OF
1S 21
a Temperature of bottom 2" of Slab Last Hour OF
13 2
- Temperature of bottom 2" of Slab Current Hour
UAS
=Total Conductance of Slab (Slab area x U Slab) etu/hr OF
CAS
a Heat Capacity of Slab Btu/OF
QSM= Total Hourly Solar Heat Gain Btu/hr
115
OF
SOLUTION:
A.
From Equation #1 for Air Temperature in Current Hour (TA):
TA(UAW+CA+H) = CA(TA1)+0.40SSOL = Tout(UAW+TRH)
TA= CA(TA1)+0.40SSOL+Tout(UAW)+TRH
(UAW+CA+H)
IF:
(UAW+CA+H) = G; CA(TA1) = D; 0.40SSOL = B; Tout(UAW) = E
THEN: TA = D+B+E+TRH
IF:
(D+B+E)/G = K
THEN: TA = K+(TR(H))/G
B.
From Equation #2 for Rug Temperature in Current Hour (TR):
TR(UAR+CR+H) = TA(H)-TS1(UAR) = CR(TR1)+0.60SSOL
IF:
(UAR+CR+H) = I; CR(TR1) = P; 0.6QSSOL = A; TA = K+TR(H)/G
THEN: TR(l)-H(K+TR(H)/G)-TS1(UAR) = P + A
IF:
H 2 /G = S
THEN: TR(I)-H(K)-TR(S)-TS1(UAR) = P + A
AND:
C.
TR(I-S)-TS1(UAR) = P + A + H(K)
From Equation #4 for Temperature of Bottom 2" of Slab in Current
Hour (TS2):
TS2(UAS+0.5CS) = 0.5CS(TS21)+TS1(UAS)
IF:
(UAS+0.5CS) = L; 0.5CS = F; O.5CS(TS21)
THEN: TS2 = (J+TS1(UAS))
D.
From Equation #3 for Temperature of Top 2" of
Hour (TS1):
Slab in Current
TS1(UAR+UAS+0.5CS)-TR(UAR)-TS2(UAS) = 0.5CS(TS11)
UAR+UAS+0.5CS = M; 0.5CS = F; 0.5CS(TS11) = V;
TS2 = (TS21(F)+TS1 (UAS))/L
THEN:TS1(M)-TR(UAR)-UAS (TS21(cF)+TS1(UAS) = V
L
IF:
AND: TS1(M)-TR(UAR)-TS1(UAS )- TS1(F)UAS = V
L
L
IF:
UAS 2 /L= 0; TS1(F)UAS/L = N
THEN: TS1(M-0)-TR(UAR) = V + N
116
E.
From the sum of Equation #2 (TR) and Equation #3 (TS1):
I-S = W; M-0 = R
IF:
THEN: TR(I-S)-TS1(UAR) = P + A + H(K)
TR(W)-TS1(UAR) = P + A + H(K)
BECOMES:
AND: TS1(M-O)-TR(UAR) = V + N
BECOMES: TS1(R)-TR(UAR) = V + N
SO: R(TR)W-R(TS1)UAR = R(P+A+H(K))+R(TS1)UAR-TR(UAR2 ) = UAR(V + N)
THEREFORE:
TR = R(P+A+H(K))+UAR(V+N)
W(R)-UAR2
SUBSTITUTION SUMMARY
0.6QSSOL
0.4QSSOL
CA(TA1)
Tout(UAW)
0.5CS
UAW+CA+H
H+UAR+CR
F(TS21)
(D+B+E)/G
L = UAS+F
M = UAR+UAS+F
N = TS21(UAS)F/L
O = UAS 2 /L
P = CR(TR1)
R = M-O
S = H 2 /G
V = F(TS11)
W = I-S
117
118
APPENDIX F
SIMULATION PROGRAM FLCW CHART
119
120
APPENDIX G
SIMULATION OUTPUTS
The tables below assume the following office parameters:
1. 12 foot width
2. 16 foot depth
3. 10 foot height
4. Rug covered slab
5. Constant volume ventilation
6. Heating thermostat setpoints
A. 680 occupied
B. 600 unoccupied
7. Cooling thermostat setpoints
A. 730 occupied
B. 800 unoccupied
8. Electric heat
9. 64 square foot window area
10.56 square foot opaque wall area (RIO)
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HM/NT SINGLE GLAZED
AZIMUTH
CITY
HEAT
LOAD
KM
COOL
LOAD
KWH
LITE
LOAD
KWH
TOTAL
LOAD
KUN
0.
ANUAL
PEAK MO DY HR
KU
ALBUGUERUE-N~~16.-~1701.5~1222~2010.3-~1.37
BOSTON MA
479.7
890.1
229.3 1598.1
1.41
CARIBOU ME
1152.3
680.5
243.8 2076.6
1.76
CHARLESTON SC
55.9 1409.9
177.3 1642.0
0.99
COLUMBIA MO
395.8 1511.9
169.5 2097.2
1.38
ELY NE
599.6 1248.2
132.5 1980.3
1.54
FORT WORTH TX
77.7 1534.5
163.1 1775.3
1.18
GREAT FALLS MT
734.6
989.1
173.8 1997.5
1.54
MADISON WI
601.9
921.5
207.5 1931.0
1.51
MIAMI FL
0.0 1826.5
160.5 1987.0
1.09
NASHVILLE TN
218.4 1203.2
211.6 1633.2
1.29
NEW YORK NY
400.8
923.3
235.4 1559.6
1.36
PHOENIX AZ
4.0 2183.1
130.2 2317.3
1.22
SANTA MARIA CA
37.4 1229.9
148.1 1414.3
0.93
SEATTLE WA
322.2
749.3
305.7
1376.2
1.33
WASHINGTON DC
425.1 1091.9
212.3 1729.9
1.36
10
12
1
12
12
1
1
12
12
10
1
12
10
10
1
12
AZIMUTH
CITY
HEAT
LOAD
KU
COOL
LOAD
KWH
LITE LOAD
KWH
TOTAL
LOAD
KWH
2 12
6 8
3 8
6 9
6 6
4 6
6 8
6 S
6 8
4 9
6 9
6 9
2 8
3 12
6 9
6 S
SUMMER
PEAK
MO DY HR
KU
PEAK KU/YR
AS EQUIVALNT
KWH
TOTAL
1.37
0.90
1.20
0.95
1.22
1.02
1.00
0.99
0.91
1.09
0.95
0.92
1.22
0.93
0.97
0.91
671.6
752.9
612.3
799.9
723.4
657.7
745.6
761.2
665.8
677.0
703.1
721.8
551.9
737.1
712.9
261.8
2351.0
2896.7
2254.3
2997.1
2703.7
2433.0
2643.0
2692.2
2652.8
2310.2
2262.7
3039.0
1966.1
2113.2
2442.7
PEAK KU/YR
AS EOUIVALNT
KWH
TOTAL
EQUIVAI
KWH
10
10
10
S
10
10
10
8
9
10
10
10
10
10
9
9
2
2
6
2
4
2
2
2
5
4
4
3
2
3
3
4
12
12
S
9
12
12
12
12
11
8
12
12
8
12
12
12
820.1
EGUIVAL
KUH
90.
ANUAL
PEAK MO DY HR
SUMMER
PEAK
MO DY HR
KU
KU
ALBUQUERQUE- ~~407.3~~1397.6~~107.3~~1912.2~~~1.31~~12~~4~~~~1.18~~~7~~2~15~~~~16.22~~~~~~729.4
BOSTON MA
671.1
680.3
225.0 1576.4
1.49
1 2 8
1.01
7 3 15
810.6
2397.0
CARIBOU ME
149!.8
509.5
255.1 2254.4
1.63
1 3 8
1.23
10 6 9
972.8
3127.1
CHARLESTON SC
142.7
1171.5
170.2 1434.4
1.13
1 2 9
0.93
7 4 15
655.4
2139.8
COLUMBIA MO
601.5
996.9
109.9 1796.3
1.45 12 6 6
1.10
9 2 15
927.9
2616.3
ELY NE
926.4
983.4
125.0 2034.9
1.63
1 4 S
1.11
7 3 15
944.0
2978.9
FORT WORTH TX
173.1 1325.2
155.9 1654.3
1.24
1 6 9
1.11
8 5 15
711.1
2365.3
GREAT FALLS MT
998.2
757.6
136.8 1942.6
1.66 12 2 8
1.15
10 6 8
869.2
2810.9
MADISON WI
1095.2
708.8
215.8 2019.9
1.71
1 2 8
0.97
7 2 15
828.7
2849.5
MIAMI FL
0.0 1654.9
151.0 1605.9
0.94
4 2 15
0.94
7 2 9
607.8
2413.7
NASHVILLE TN
322.7
992.4
214.9 1520.1
1.31
1 6 9
0.95
7 2 15
725.7
2245.8
NEW YORK NY
558.4
701.5
234.3 1494.1
1.49
1 2 6
0.90
7 3 15
733.2
2227.4
PHOENIX AZ
64.3 1908.2
124.7 2097.2
1.23
7 2 15
1.23
7 2 15
763.5
2860.8
SANTA MARIA CA
136.4
957.1
136.8 1230.3
1.13
1 2 8
0.90
5 2 15
641.9
1672.2
SEATTLE WA
431.0
553.6
323.7 1309.2
1.37 12 3 9
0.98
10 6 6
765.9
2074.2
WASHINGTON DC
530.1
959.4
214.5 1653.9
1.46
1 5 6
0.95
8 4 15
762.4
2416.3
AZIMUTH
180.
HEAT
COOL
LITE
TOTAL
ANUAL
LOAD
LOAD
LOAD
LOAD
PEAK MO DY
KWM
KWH
KWH
KWH
KU
---------------------------------------H
i----HFi5;----i35--ALBUQUERQUE NM~~561.9~~657.5~~158.1~~1377.4~~~1.37~~1~~2~
BOSTON MA
815.1
401.0
264.0 1480.0
1.51
1 2
CARIBOU ME
1730.1
234.7
297.5 2252.3
1.85
1 2
CHARLESTON SC
194.4
909.1
184.7 1187.2
1.20
1 2
COLUMBIA MO
738.0
533.7
221.3 1493.1
1.47
1 6
ELY NE
1187.2
379.1
175.3 1741.5
1.67
1 2
FORT WORTH TX
226.0
957.6
176.2 1259.8
1.27
1 6
GREAT FALLS MT
1191.9
353.9
226.8 1772.6
1.69
1 3
MADISON WI
1302.5
394.3
242.0 1938.7
1.74
1 2
MIAMI FL
0.6 1279.1
164.3 1444.0
0.96
6 2
NASHVILLE TN
369.8
664.0
232.4 1296.2
1.32
1 6
NEW YORK NY
668.4
449.2
257.9 1375.6
1.53
1 2
PHOENIX AZ
101.9 1201.0
148.2 1451.2
1.04
1 4
SANTA MARIA CA
195.9
437.0
162.1
795.1
1.19
1 2
SEATTLE WA
519.4
261.5
346.1 1127.1
1.39 12 3
WASHINGTON DC
671.2
538.6
231.9 1441.6
1.49
1 5
CITY
AZIMUTH
CITY
ALUERGUE NM
BOSTON MA
CARIBOU ME
CHARLESTON SC
COLUMBIA MO
ELY NE
FORT WORTH TX
GREAT FALLS MT
MADISON WI
MIAMI FL
NASHVILLE TN
NEW YORK NY
PHOENIX A2
SANTA MARIA CA
SEATTLE WA
WASHINGTON DC
HEAT
LOAD
KWH
COOL
LOAD
KWH
LITE
LOAD
KWH
TOTAL
LOAD
KWH
ANUAL
PEAK
KU
SUMMER
PEAK
MO DY HR
KU
HR
PEAK KU/YR
TOTAL
AS EQUIVALNT
EQUIVA:
KWH
KWH
------------y:
~~~~~637.~~~~~~~~
4i.4
~~~0.9~~~~7~
9
8
8
9
8
9
a
8
9
8
3
0
6
6
3
1.05
1.25
0.90
0.92
1.08
0.96
1.18
1.03
0.96
0.89
0.66
0.98
0.55
1.07
0.76
10
10
7
10
10
7
10
10
6
7
10
7
9
10
10
6 9
6 8
2 8
3 S
4 9
6 8
6 8
3 9
2 9
2 9
4 8
4 9
2 17
5 6
2 9
732.3
951.1
603.7
715.5
743.9
619.3
787.5
761.0
543.5
638.1
678.2
590.7
520.8
718.4
697.2
2212.3
3103.4
1790.9
2208.7
2485.4
1879.1
2560.1
2699.7
1987.5
1924.3
2053.8
2041.8
1315.8
1845.5
2138.8
PEAK KU/YR
AS EOUIVALNT
KWH
TOTAL
EQUIVA;
KWH
270.
MO
DY HR
K------------------------------------2777
1317.9
14.3 149.9
1.9
72
573.6
669.7
254.9
1503.2
1.44 12
1366.7
459.8
270.9 2097.4
1.81
1
92.9 1159.3
185.5 1437.8
1.34
7
517.5
959.1
216.0 1692.6
1.49
6
723.9
358.9
171.5 1754.2
1.62
1
117.0 1279.1
174.7 1570.9
1.51
I
868.0
709.1
207.2 1764.2
1.57 12
997.3
662.1
232.7 1892.1
1.54 12
0.0 1679.6
166.0 1345.6
1.36
8
272.1
983.7
226.9 1462.8
1.35
7
499.5
696.6
250.0 1435.1
1.39
1
14.4 1992.5
148.2 2055.0
1.63
7
73.5
396.3
160.0 1129.9
1.17
5
379.6
522.9
335.7 1238.2
1.36
7
510.9
332.6
225.6 1569.1
1.38 12
126
6
3
6
2
4
2
6
6
5
2
6
2
6
2
6
SUMMER
PEAK
MO DY HR
KU
F ---------Mi--------i--i
iui
----------6:
8
158~~~7~~2~9~~~~20.6~~~~~~~~
0.7
3
1.33
6 6 S
971.2
2374.4
8
1.20
10 6 U
838.3
2935.6
5
1.34
7 6 5
732.7
2170.5
8
1.49
6 2 6
924.6
2617.3
U
1.44
7 3 S
837.3
2591.5
S
1.51
6 2 3
309.6
2379.4
9
1.46
7 5 9
649.9
2634.1
9
1.35
7 2 8
330.0
2722.1
8
1.36
6 5 6
792.0
2637.6
5
1.35
7 2 6
815.0
2297.7
9
1.18
8 4 9
780.2
2215.3
8
1.63
7 2 9
346.4
2901.4
8
1.17
5 6 9
601.4
1731.2
9
1.36
7 2 8
902.1
2040.2
9
1.34
6 5 a
817.1
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HM/HT TRIPLE GLAZED
AZIMUTH
CITY
ALBUQUER-UE NM
BOSTON MA
CARIBOU ME
CHARLESTON SC
COLUMBIA
MO
ELY NE
ORT WORTH TX
GREAT FALLS MT
MADISON WI
MIAMI FL
NASHVILLE TN
NEW YORK NY
PHOENIX AZ
SANTA MARIA CA
SEATTLE WA
WASHINGTON DC
HEAT
LOAD
KWH
3-.8
229.9
660.6
10.1
131.6
254.2
14.1
332.8
444.3
0.0
63.5
199.3
0.0
2.0
138.9
214.4
COOL
LOAD
KWH
2163.9
1203.1
998.6
1726.1
1927.0
1715.9
1350.3
1359.8
1255.5
2083.9
1501.2
1225.2
2555.7
1651.0
1054.7
1399.9
LITE
LOAD
KWH
118.0
216.0
231.6
168.6
175.9
127.0
157.3
170.0
193.7
157.2
201.7
222.2
127.6
144.7
268.5
201.3
TOTAL
LOAD
KUM
2340.6
1648.0
1391.0
1904.8
2284.5
2097.2
2021.7
1912.7
1693.5
2241.1
1796.5
1646.8
2633.3
1797.7
1482.1
1915.6
ANUAL
PEAK MO DY HR
SUMMER
PEAK
MO DY HR
KW
PEAK KW/YR
AS EQUIVALNT
TOTAL
EQUIVAl
KWH
1.62
1.31
1.55
1.11
1.47
1.38
1.16
1.40
1.38
1.1e
1.20
1.62
1.10
1.05
1.10
1.47
1.26
1.16
1.16
1.07
1.18
1.12
1.12
1.34
1.12
1.07
1.09
12
12
12
12
12
12
12
12
10
8
12
12
792.8
743.4
798.2
709.5
973.3
760.0
731.7
79.7
732.8
744.2
724.3
731.8
12
12
11
674.0
741.0
735.9
3133.3
2391.4
2689.2
2613.3
3157.8
2857.1
2753.4
2701.4
2676.4
2985.3
2510.8
2379.5
3496.9
2471.7
2223.2
2551.5
PEAK KW/YR
AS EQUIVALNT
KWH
TOTAL
EQUIVAL
KWH
KW
10
12
1
11
10
1
10
12
12
10
12
12
10
2
1
12
1.26
1.34
1.14
1.23
1.26
AZIMUTH
CITY
Ui5UiiiUi-NM
BOSTON MA
CARIBOU ME
CHARLESTON SC
COLUMBIA MO
ELI NE
FORT WORTH TX
GREAT FALLS MT
MADISON WI
MIAMI FL
NASHVILLE TN
NEW YORK NY
PHOENIX AZ
SANTA MARIA CA
SEATTLE WA
WASHINGTON DC
HEAT
LOAD
KWH
COOL
LOAD
KWH
LITE
LOAD
KWH
TOTAL
LOAD
KWH
ALBUQUERQUE NM
BOSTON MA
CARIBOU ME
CHARLESTON SC
COLUMBIA
MO
ELY NE
FORT WORTH TX
GREAT FALLS MT
MADISON WI
MIAMI FL
NASHVILLE TN
NEW YORK NY
PHOENIX AZ
SANTA MARIA CA
SEATTLE WA
WASHINGTON DC
ROSTON MA
CARIBOU ME
CHARLESTON SC
COLUMBIA MO
ELY HE
FORT WORTH TX
GREAT FALLS MT
MADISON WI
MIAMI
NASHVILLE TN
NEW YORK NY
PHOENIX AZ
SANTA MARIA CA
SEATTLE WA
WASHINGTON DC
12
8
9
11
12
9
12
9
6
6
8
9
9
12
3
9
HEAT
LOAD
KWKW
COOL
LOAD
HWH
LITE
LOAD
332.7
500.1
1148.8
110.8
450.2
729.3
123.0
759.2
923.0
507.8
330.2
953.7
641.2
515.5
989.2
465.3
496.6
1416.4
797.4
566.0
1321.1
619.3
396.5
656.9
15.
242.1
267.5
174.3
200.6
165.2
165.9
210.3
229.2
158.4
219.1
242.9
141.1
157.6
321.4
219.1
846.9
0.0
228.9
409.9
48.7
93.6
301.5
416.5
KWKW
TOTAL
LOAD
HWH
1394
1249.9
1746.6
1238.9
1292.0
1410.1
1279.1
1434.9
1571.6
1574.8
1245.4
1217.7
1510.9
870.6
1019.4
1292.5
NEAT
LOAD
KWH
COOL
LOAD
KWH
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
2
2
2
2
4
2
2
2
4
4
4
3
2
3
2
3
8
KWH
813.6
90.
~-214.
~1767.~~101~.~5203~~~~1~.3~~10
15~~~~
300.7
890.9
211.5 1403.0
1.34
1 2 8
941.4
714.2
239.5 1394.1
1.65
1 3 8
64.6 1407.4
161.0 1633.1
1.11
4 2 15
343.4 1245.3
177.6 1766.3
1.34
12 6 3
522.3
1320.8
122.5 1965.6
1.48
1 4 6
75.4 1568.0
149.5 1793.2
1.25
U 5 15
594.8 1003.0
176.9 1774.6
1.50
12 2 8
670.2
923.2
203.4
1796.8
1.53
1 2 3
0.0 1974.4
146.3 2021.3
1.09
4 2 15
170.2 1199.1
199.3 1568.5
1.22
12 6 8
315.8
901.1
219.7
1436.6
1.33
1 2 8
24.2 2188.8
121.4 2334.4
1.36
7 2 15
50.8 1277.8
131.4 1460.0
1.09
5 2 15
224.5
777.6
299.1 1301.2
1.27
12 3 8
344.8 1077.1
203.3
1625.3
1.30
1 5 8
SUMMER
PEAK
MO DY HR
KW
6
1.16
1.15
1.05
1.25
1.27
1.25
1.26
1.11
1.00
1.06
1.04
1.36
1.09
1.17
1.08
0i2i
i~
7 3
10 6
7 4
8 2
7 2
e 5
10 3
7 2
10 6
7 2
7 3
7 2
5 2
10 2
8 4
5~~~i5~~5:15
812.4
8
855.3
15
693.0
15
862.7
15
979.2
15
748.0
16
867.0
15
617.0
15
674.7
15
734.9
15
756.3
15
625.6
15
704.2
16
779.7
15
787.4
2295.4
2749.4
2326.1
2629.0
2944.8
2541.2
2641.6
2613.9
2696.0
2303.4
2192.9
3160.0
2164.1
2080.0
2412.7
180.
ANUAL
PEAK MO DY HR
KW
SUMMER
PEAK
MO DY HR
12
1.39
1.67
1.10
1.34
1.52
1.16
1.54
1.57
1.01
1.23
1.39
1.01
1.07
1.29
1.32
093
0.72
1.17
0.94
0.80
0.97
0.99
1.06
0.99
1.01
0.93
0.75
1.01
0.57
0.71
0.89
128
1 2
1 3
1 4
1 6
1 4
1 6
12 2
1 2
6 2
1 6
1 2
7 6
1 2
12 3
1 6
AZIMUTH
CITY
2
6
3
4
4
4
2
6
6
4
6
6
2
3
6
6
ANUAL
PEAK MO DY HR
KW
AZIMUTH
CITY
0.
a
9
3
e
9
9
6
8
8
3
3
6
9
8
8
KW
728
7 3 8
10 6 8
7 2 6
7 2 8
10
4 8
7 6 8
10 6 9
10 3 8
6 2 8
7 3 8
7 2 6
7 6 8
9 2 17
10 3 9
7 2 6
PEAK KW/YR
AS EQUIVALNT
KWH
TOTAL
EQUIVAI
KWH
6.0194
670.1
749.4
569.2
644.6
670.0
589.3
710.2
699.0
572.3
621.0
632.2
582.5
468.2
639.6
645.9
1920.0
2496.0
1808.1
1936.6
2080.0
1667.4
2144.9
2269.6
2147.2
1866.4
1349.9
2093.4
1338.8
1659.0
1938.4
270.
LITE
LOAD
KWH
TOTAL
A*UAL
SUMMER
PEAK KU/YR
TOTAL
LOAD
PEAK MO DY HR
PEAK
Mo DY HR
AS EOUIVALNT
EQUIYAE
KWH
KU
Km
KWH
KWH
--------------------------------------------------------i-------------;--304.6
900.4
235.6 1440.6
1.50
6 6
1.50
6 6 6
927.1
2367.9
322.0
679.3
256.3 1757.7
1.62
1 3 1
1.36
6 6 a
656.4
2616.0
31.4 1411.2
173.9
1616.5
1.55
4 5
1 9.
7 6
791.0
2407.5
279.2 1229.1
196.6
1705.1
1.66
2 9
1.66
2 6
1000.0
2705.1
369.5 1225.1
162.3
1756.9
1.63
7 2 6
1.63
7 23
995.5
2752.4
34.1
1532.6
167.2
1733.9
1.66
2 8
1.66
2 8
635.4
2619.3
466.3
962.0
195.7
1663.9
1.63
7 5 6
1.63
7 5 8
976.5
2640.5
566.9
682.3
219.4 1638.6
1.51
7 2 8
10.51
7 2 8
920.4
2609.9
0.0 1906.2
161.3
3L
2067.9
1.50
4 6 6
1.48
1 3 53
85.0
2953.0
126.9 1221.2
216.2
1564.3
1.51
5 5 8
1.51
5
8
651.4
2415.7
266.1
902.8
240.4
1409.4
1.34
9 3 6
1.34
9 5 9
935.5
2244.8
0.0 2199.4
143.1
2341.5
1.79
7 270
1.79
7 2 8
998.83340.3
13.6 1242.8
156.3
1412.6
1.52
5 2 8
1.52
5 2
756.6
2169.3
16.6
761.0
311.4
1259.1
1.54
7 2
1.54
7 2
642.9
2102.0
232.4 1062.6
214.5
1559.5
1.46
5 e
1.48
76 5 3
914.4
2473.8
128
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ELECTRO-OPT IC-I
AZIMUTH
HEAT
LOAD
KWH
CITY
ALIUOUEROUE NM
BOSTON MA
CARIBOU ME
CHARLESTON SC
COLUMBIA MO
ELY NE
FORT WORTH TX
GREAT FALLS MT
MADISON WI
MIAMI FL
NASHVILLE TN
NEW YORK NY
PHOENIX AZ
SANTA MARIA CA
SEATTLE WA
WASHINGTON DC
122.9
332.7
869.7
32.2
295.1
422.5
42.7
532.1
595.9
0.0
144.0
290.2
0.5
14.0
210.1
307.1
COOL
LOAD
KWH
1399.1
756.4
569.0
1187.4
1244.5
1036.8
1292.1
329.8
770.9
1549.4
1019.8
791.8
1921.0
1019.8
640.4
918.2
LITE
LOAD
KUM
115.5
207.2
224.7
160.7
172.7
125.0
147.6
160.4
186.7
155.6
195.6
211.5
127.2
141.9
273.7
191.5
TOTAL
LOAD
KWH
1636.5
1296.4
1662.3
1330.3
1712.4
1594.2
1482.3
1522.4
1553.5
1705.0
1359.4
1283.5
1948.7
1175.7
1124.1
1416.8
0.
ANUAL
PEAK MO DY HR
KW
SUMMER
PEAK
MO DY HR
KW
PEAK KU/YR
AS EOUIVALNT
KWH
TOTAL
EDUIVAL
KWH
1.11
1.36
1.64
0.90
1.33
1.48
1.10
1.46
1.44
0.96
1.24
1.30
1.10
0.75
1.26
1.31
1.11
0.73
1.14
0.90
0.99
0.83
0.93
0.82
0.74
0.96
0.83
0.74
1.10
0.75
0.71
0.75
560.1
672.9
717.7
523.9
703.3
622.3
571.4
647.1
675.0
588.9
603.6
626.9
625.7
457.4
657.3
637.0
2196.6
1969.4
2380.0
1904.1
2415.7
2206.5
2053.7
2169.4
2228.6
2293.9
1963.0
1910.4
2574.4
1633.1
1781.4
2053.7
SUMMER
PEAK
MO DY HR
KW
PEAK KW/YR
AS EQUIVALNT
KWH
TOTAL
EGUIVAL
KWH
0.34
1.19
0.86
0.91
0.94
0.92
1.04
0.82
0.89
0135
0.75
1.03
0.73
0.79
0.78
713.2
781.0
570.0
725.5
736.1
598.9
760.4
724.7
545.5
635.5
647.5
634.2
534.5
684.6
673.8
1998.4
2596.5
1825.3
2181.9
2367.1
1991.8
2315.6
2333.3
2100.4
1903.0
1362.8
2403.3
1556.1
1750.5
2036.6
PEAK KW/YR
AS EOUIVALNT
KWH
TOTAL
EGUIVA,
KWH
10
12
1
S
12
1
1
12
12
10
1
12
10
10
1
12
AZIMUTH
HEAT
LOAD
KWH
CITY
BOSTON MA
CARIBOU ME
CHARLESTON SC
COLUMBIA MO
ELY NE
FORT WORTH TX
GREAT FALLS MT
MADISON WI
MIAMI FL
NASHVILLE TN
NEW YORK NY
PHOENIX AZ
SANTA MARIA CA
SEATTLE WA
WASHINGTON DC
434.6
1143.1
99.7
442.8
692.2
121.4
743.1
313.8
0.0
228.0
396.9
46.4
92.5
297.6
433.9
COOL
LOAD
KWH
LITE
LOAD
KWH
505.3
433.5
999.4
205.2
228.9
156.1
171.9
120.9
146.0
171.5
194.6
143.1
191.8
212.7
120.1
126.9
283.2
193.0
841.7
818.0
1125.5
640.7
600.1
1411.8
847.8
605.6
1602.6
302.2
485.0
735.9
TOTAL
LOAD
KWH
1275.2
1805.5
1255.3
1456.4
1631.0
1392.9
1555.2
1608.5
1554.9
1267.5
1215.3
1769.2
1021.6
1065.8
1362.8
1.37
1.71
1.08
12
1
1
12
1
1
1
1
7
1
1
7
1
12
12
1.37
1.54
1.15
1.54
1.56
0.89
1.25
1.35
1.03
1.02
1.30
1.33
HEAT
LOAD
KWH
COOL
LOAD
KWH
LITE
LOAD
KWH
TOTAL
LOAD
KWH
li~iislisa~~iii~~iil~~ii~i~iii~~i:3-~
BOSTON MA
CARIBOU ME
CHARLESTON SC
COLUMBIA MO
ELY NE
FORT WORTH TX
GREAT FALLS MT
MADISON WI
MIAMI FL
NASHVILLE TN
NEW YORK NY
PHOENIX AZ
SANTA MARIA CA
SEATTLE WA
MASHINGTON DC
364.2
216.0
718.2
474.0
341.4
762.3
318.9
353.5
1120.0
599.4
406.0
1054.4
406.3
258.6
233.8
256.0
173.1
195.7
160.3
160.9
204.1
217.0
155.9
210.0
233.1
140.7
151.3
310.1
5A.D
4aS
322.0
1196.5
1815.7
1030.6
1209.0
1367.4
1085.5
1419.2
1563.9
1275.9
1093.0
1127.8
1268.6
693.0
942.4
1190.9
BOSTON MA
CARIBOU ME
CHARLESTON SC
COLUMBIA MO
ELY NE
FORT WORTH TX
SREAT FALLS MT
MADISON WI
MIAMI FL
NASHVILLE TN
NEW YORK NY
PHOENIX AZ
SANTA MARIA CA
SEATTLE WA
WASHINGTON DC
8
10
10
9
8
9
10
7
10
10
10
9
9
12
12
8
8
12
12
8
12
11
8
8
12
8
12
12
12
190.
1
1
1
1
1
1
1
1
6
1
1
12
1
12
12
HEAT
COOL
LITE
TOTAL
ANUAL
LOAD
LOAD
LOAD
LOAD
PEAK
KWH
KWH
KWN
KUM
KU
------------------------K---395.4
579.8
223.4 1203.6
1.37
1005.0
406.5
247.3
1656.8
1.66
53.9
991.6
171.0 1216.4
1.19
369.7
311.2
190.7 1371.6
1.35
505.2
751.8
153.6 1415.6
1.53
66.0 1094.5
159.6 1320.2
1.34
614.2
610.4
189.9 1414.5
1.48
713.3
575.0
211.2 1499.5
1.46
0.0 1433.3
160.5 1594.3
1.22
175.2
352.8
207.6 1235.6
1.25
333.6
595.3
229.0 1163.3
1.31
4.7 1596.4
142.7 1743.3
1.45
34.4
759.3
153.0
946.7
1.04
251.9
461.5
295.1 1003.5
1.27
361.1
722.4
203.3 1286.3
1.32
2
2
6
2
4
2
3
2
5
2
2
3
2
3
3
4
7 3 15
10 6 8
7 ~2 8
3 2 15
10 4 6
3 5 15
10 6 8
10 3 6
7 2 8
7 2 8
7 3 15
7 2 15
5 2 15
7 2 15
S 4 15
SUMMER
PEAK
MO DY HR
Kw
i-~ii~~i-~i~~~~-~ii~~~--
1.41
1.74
1.11
1.39
1.58
1.18
1.59
1.60
0.91
1.26
1.42
0.95
1.06
1.32
1l
AZIMUTH
CITY
6 0
3 3
4 3
6 3
4 0
6 S
3 8
2 8
2 3
6 3
2 3
2 15
2 3
3 3
6 3
ANUAL
PEAK MO DY HR
KW---
598.5
1343.8
139.4
539.3
365.7
162.3
396.3
993.3
0.0
283.5
488.9
73.6
135.4
373.7
10
10
10
90.
ANUAL
PEAK MO DY HR
KU
AZIMUTH
CITY
2 13
6 8
3 a
2 3
6 8
4 8
6 6
6 8
6 9
2 8
6 S
6 3
2 8
3 12
6 3
6 8
2
3
4
6
4
6
3
2
2
6
2
4
2
3
(
8
8
S
8
S
8
3
8
8
8
8
S
8
8
3
0.79
1.19
0.85
0.78
0.98
0.90
1.07
0.92
0.91
0.81
0.64
0.93
0.55
0.91
0.66
10
10
7
10
10
7
10
10
6
7
8
7
9
10
a
-i--~i-----~~~~~~-
6 8
6 8
2 8
3 9
4 8
6 8
6 8
3 8
2 8
2 8
4 17
4 8
2 17
3 3
5 17
682.7
771.0
550.1
658.4
668.4
570.3
714.0
701.4
524.1
610.8
628.6
557.7
476.5
667.2
633.3
MK;
1879.1
2586.8
1580.7
1867.4
2035.9
1655.9
2133.2
2265.2
1800.0
1703.7
1756.4
1926.3
1169.5
1609.7
1324.2
270.
MO DY HR
K
-----------12 6
1 3
7 6
12 6
1 4
3 2
12 6
12 6
3 5
1 6
12 6
7 3
5 6
3 4
13 6
130
3
8
3
8
3
9
3
8
3
s
3
s
6
4
3
PEAK KW/YR
TOTAL
AS EOUIVALNT
EOUIVA
KWH
KWN
---- ------------------------------
SUMMER
PEAK
MO DY HR
1.10
1.14
1.19
1.31
1.27
1.34
1.28
1.17
1.22
1.21
0.97
1.45
1.04
1.20
1.16
6
10
7
3
7
3
7
7
3
7
8
7
5
7
1
6 3
6 3
6 3
2 3
2 8
2 3
5 8
2 3
5 3
2 3
4 3
2 3
6 3
2 3
5 3
757.7
738.9
631.0
306.0
739.3
698.5
735.1
730.6
709.0
697.2
635.4
749.7
503.3
709.1
716.9
1961.3
2397.7
1647.4
2177.5
2205.0
2018.7
2149.6
2230.1
2303.3
1932.9
1043.7
2493.5
1450.0
1717.6
2003.6
ELECTRO-OPTIC-2
0.
AZIMUTH
CITY
AL5UGUERoUE NM
SOSTON MA
CARIBOU ME
CHARLESTON SC
COLUMBIA MO
ELY NE
FORT WORTH TX
GREAT FALLS MT
MADISON WI
MIAMI EL
NASHVILLE TN
NEW YORK NY
PHOENIX AZ
SANTA MARIA CA
SEATTLE WA
WASHINGTON DC
HEAT
LOAD
KWH
146.3
350.8
902.6
36.2
322.6
461.5
51.8
556.1
624.8
0.0
155.8
305.8
2.7
20.8
221.3
324.9
COOL
LOAD
KWH
1092.9
591.3
416.5
977.5
981.1
770.0
1072.7
632.8
594.5
1323.2
838.4
615.9
1520.4
794.1
499.6
737.9
LITE
LOAD
KWH
115.5
207.2
224.7
160.7
172.7
125.0
147.6
160.4
186.7
155.6
195.6
211.5
127.2
141.9
273.7
191.5
TOTAL
LOAD
KWH
1356.7
1149.4
1543.8
1176.4
1476.5
1356.5
1272.1
1349.3
1406.0
1478.8
1189.8
1133.1
1650.3
956.8
994.6
1254.2
ANUAL
'PEAK MO DY HR
KW
0.96
1.36
1.65
0.86
1.34
1.49
1.11
1.47
1.44
0.9
1.24
1.30
0.98
0.72
1.26
1.32
12
12
1
12
12
1
1
12
12
9
1
12
9
12
1
12
AZIMUTH
CITY
ALBUQUERQUE NM
BOSTON MA
CARIBOU ME
CHARLESTON SC
COLUMBIA MO
ELY NE
FORT WORTH TX
GREAT FALLS MT
MADISON WI
MIAMI FL
NASHOILLE TN
NEW YORK NY
PHOENIX AZ
SANTA MARIA CA
SEATTLE WA
WASHINGTON DC
NEAT
LOAD
KWH
COOL
LOAD
KWH
329.0
496.6
1159.7
107.4
453.7
719.8
129.0
759.6
325.3
0.0
235.7
405.1
52.0
103.0
307.4
442.1
914.7
477.0
334.2
941.2
691.2
621.0
955.9
501.3
478.7
1219.7
715.5
499.9
1357.0
631.4
397.1
610.7
LITE
LOAD
KWH
99.0
205.2
223.9
156.1
171.9
120.9
146.0
171.5
194.6
143.1
191.6
212.7
120.1
126.9
233.2
193.0
TOTAL
LOAD
KWH
1341.7
1179.9
1722.7
1104.7
1316.3
1461.6
1231.0
1432.4
1498.6
1362.7
1143.0
1117.7
1529.2
861.3
977.7
1245.8
ALBUQUERQUE NM
ROSTON MA
CARIBOU ME
CHARLESTON SC
COLUMBIA MO
ELY NE
FORT WORTH TX
GREAT FALLS MT
MADISON WI
MIAMI FL
NASHVILLE TN
NEW YORK NY
PHOENIX AZ
SANTA MARIA CA
SEATTLE WA
WASHINGTON DC
HEAT
LOAD
COOL
LOAD
KWH
415.2
600.2
1347.1
141.4
540.2
874.5
163.3
399.8
995.4
0.0
286.8
488.9
77.1
139.1
376.3
503.4
499.2
322.7
186.6
637.7
428.8
284.7
690.9
279.0
308.2
1006.1
539.2
357.8
960.8
350.7
227.3
431.2
KWH
LITE
LOAD
KWH
146.5
233.6
256.0
173.1
195.7
160.3
160.9
204.1
217.0
155.9
210.0
233.1
140.7
151.3
310.1
207.0
TOTAL
LOAD
KWH
1059.9
1156.6
1789.7
952.2
1164.7
1319.5
1015.1
1380.8
1520.6
1162.0
1036.0
1079.6
1179.6
641.1
913.7
1141.6
BOSTON MA
CARI3OU ME
CHARLESTON SC
COLUMBIA MO
ELY HE
FORT WORTH TX
GREAT FALLS MT
MADISON WI
MIAMI FL
NASHVILLE TN
NEW YORK NY
PHOENIX AZ
SANTA MARIA CA
SEATTLE WA
WASHINGTON DC
HEAT
LOAD
KWH
COOL
LOAD
KWH
LITE
LOAD
KWH
TOTAL
LOAD
KWH
401.8
1016.1
54.5
331.1
523.4
72.4
622.3
720.8
0.0
179.7
343.7
9.1
38.9
255.6
365.4
478.0
321.6
341.0
663.2
590.7
936.6
484.5
471.4
1242.8
725.8
494.7
1366.1
616.9
337.3
612.6
226.4
247.3
171.0
190.7
153.6
159.6
139.9
211.2
160.5
207.6
229.0
142.7
153.0
295.1
203.3
1103.2
1585.0
1066.4
1240.0
1272.7
1168.6
1296.7
1403.4
1403.3
1113.1
1067.3
1517.9
608.7
938.7
1131.3
8
6
8
9
8
8
3
9
9
8
8
0.66
0.63
1.15
0.62
0.78
0.64
0.86
0.68
0.62
0.88
0.73
0.66
0.98
0.60
0.61
0.67
10
7
10
8
10
10
8
9
7
9
7
8
9
10
7
3
2
3
6
2
4
2
2
2
3
2
2
6
2
3
2
5
12
18
8
8
12
12
8
12
18
9
9
17
6
12
16
17
ANUAL
PEAK MO DY HR
KW
SUMMER
PEAK
MO DY HR
KW
1.22
1.38
1.71
1.09
1.37
1.55
1.16
1.55
1.56
0.85
1.25
1.36
0.92
1.03
1.30
1.33
0.62
0.74
1.19
0.80
0.75
0.95
0.37
1.05
0.85
0.85
0.74
0.65
0.91
0.59
0.77
0.67
12
12
1
1
12
1
1
1
1
7
1
1
12
1
12
12
TOTAL
493.0
655.1
710.2
487.0
645.9
565.0
532.7
593.0
640.0
526.7
574.1
607.8
544.2
405.1
631.3
617.3
1849.7
1804.5
2254.0
1663.4
2122.3
1941.5
1804.8
1942.3
2046.0
2005.5
1763.9
1740.9
2194.5
1361.9
1626.0
1871.5
PEAK KW/YR
AS EOUIVALNT
KWH
TOTAL
EDUIVA
KWH
EGUIVA!
KWH
4
6
3
4
6
4
6
3
2
2
6
2
4
2
3
6
9
8
0
3
9
a
3
I
8
3
9
S
8
9
8
7
10
10
8
8
10
7
10
10
7
7
9
7
7
10
7
2
6
6
2
2
4
6
6
3
2
2
3
4
2
6
2
15
8
3
8
8
15
U
8
8
8
8
17
8
15
6
18
629.2 691.5
755.9
525.6
662.7
688.3
558.4
719.3
694.8
509.4
598.9
619.3
575.5
-479.7
653.4
633.0
1970.9
1860.4
2478.7
1630.3
1979.5
2150.0
1789.4
2151.7
2193.4
1972.1
1741.9
1737.0
2104.7
1341.0
1631.1
1879.8
190.
ANUAL
PEAK MO DY HR
KW
SUMMER
PEAK
MO DY HR
KW
PEAK KW/YR
AS EQUIVALNT
KWH
TOTAL
EQUIVA
KWH
1.25
1.41
1.74
1.12
1.38
1.58
1.16
1.53
1.60
0.86
1.26
1.42
0.95
1.06
1.32
1.33
0.73
0.80
1.19
0.78
0.90
0.99
0.36
1.07
0.93
0.86
0.72
0.64
0.90
0.55
0.92
0.66
565.8
681.8
776.7
537.9
659.6
667.6
559.6
713.2
700.6
506.6
604.4
627.1
549.9
475.0
668.7
636.8
1645.7
1838.4
2566.5
1490.2
1824.2
1987.1
1574.7
2094.0
2221.3
1668.6
1640.4
1706.T
1728.5
1116.1
1582.5
1778.5
SUMMER
PEAK
MO DY HR
KW
PEAK KW/YR
AS EOUIVALNT
KWH
TOTAL
EQUIVA
KWH
0.34
1.15
1.07
1.16
1.03
1.20
1.12
0.89
1.11
1.09
0.79
1.29
0.75
0.90
0.99
690.1
712.6
571.5
719.8
676.0
626.2
650.4
660.9
638.9
641.3
630.1
665.5
448.9
670.5
657.5
1799.3
2297.6
1637.9
1959.8
1943.7
1794.8
1947.1
2064.3
2042.2
1754.4
1697.4
2183.4
1257.7
1609.2
183.8
12
1
1
1
1
1
1
1
1
6
1
1
12
1
12
12
3
2
3
4
6
4
6
3
2
2
6
2
4
2
3
6
ANUAL
PEAK MO DY
KW
1.37
1.63
1.07
1.36
1.53
1.20
1.43
1.46
1.11
1.25
1.31
1.29
0.91
1.23
1.33
9
8
8
3
a
0
3
6
8
8
a
8
6
8
6
8
7
10
10
7
10
10
7
10
10
6
7
8
7
9
10
8
2 8
6 6
6 6
2 9
3 9
4 8
6 9
6 8
2 8
2 8
2 8
4 17
4 3
2 17
3 8
5 17
270.
AZIMUTH
CITY
8
9
9
8
6
PEAK KW/YR
AS EQUIVALNT
KWH
90.
AZIMUTH
CITY
6
6
3
6
6
4
6
6
6
2
6
6
2
5
6
6
SUMMER
PEAK
MO DY HR
MW
12
1
7
12
1
3
12
12
a
1
12
7
12
3
12
131
6
3
6
6
4
2
6
6
5
6
6
2
5
4
6
HR
8
5
8
3
8
8
3
3
3
3
I
9
3
8
3
7
10
7
3
6
3
7
7
3
7
3
7
5
7
7
2 S
6 3
6 3
2 3
2 3
2 S
5 3
2 6
5 U
2 8
4 3
2 3
6 8
2 3
2 8
ELECTRO-OPTIC-3
0.
AZIMUTH
CITY
ALBUOUEROUE NM
POSTON MA
CARIBOU ME
CHARLESTON SC
COLUMBIA MO
ELY NE
FORT WORTH TX
GREAT FALLS MT
MADISON WI
MIAMI EL
NASHVILLE TN
NEW YORK NY
PHOENIX AZ
SANTA MARIA CA
SEATTLE WA
WASHINGTON DC
HEAT
LOAD
KWH
169.5
360.4
951.6
50.7
364.1
511.4
63.8
591.6
649.6
0.0
171.2
324.2
4.5
33.0
236.5
343.3
COOL
LOAD
KWH
795.3
512.0
329.5
176.5
727.3
514.2
928.3
490.5
476.0
1282.6
750.6
550.5
1244.9
613.1
398.8
623.3
LITE
LOAD
KWH
115.5
207.2
224.7
160.7
172.7
125.0
147.6
160.4
186.7
155.6
195.6
211.5
127.2
141.9
273.7
191.5
TOTAL
LOAD
KWH
1100.3
1087.7
1505.8
1087.8
1264.2
1150.6
1139.6
1232.5
1312.3
1438.2
1117.5
1006.1
1376.6
78.0
908.9
1158.1
ANUAL
PEAK
MO DY HR
KW
SUMMER
PEAK
MO DY HR
KW
1.00
1.37
1.66
0.95
1.35
1.52
1.12
1.48
1.45
1.06
1.24
1.31
1.14
0.82
1.26
1.32
0.76
0.63
1.16
0.95
0.73
0.62
1.02
0.64
0.61
1.06
0.81
0.69
1.14
0.57
0.65
0.67
12
12
1
0
12
1
1
12
12
9
1
12
8
12
3
12
AZIMUTH
CITY
BOSTON
MA
CARIBOU ME
CHARLESTON SC
COLUMBIA NO
ELY NE
FORT WORTH TX
GREAT FALLS MT
MADISON WI
MIAMI EL
NASHVILLE TN
NEW YORK NY
PHOENIX AZ
SANTA MARIA CA
SEATTLE WA
WASHINGTON DC
HEAT
LOAD
KWH
COOL
LOAD
KWH
502.0
1186.7
108.4
465.8
741.5
133.9
778.6
505.4
332.4
399.3
668.0
544.2
953.0
490.9
480.2
1281.9
751.7
543.1
1291.6
613.0
401.0
638.0
845.7
0.0
232.1
409.2
58.6
112.0
314.6
442.1
LITE
LOAD
KWH
205.2
228.9
156.1
171.9
120.9
146.0
171.5
194.6
143.1
191.8
212.7
120.1
126.9
283.2
193.0
TOTAL
LOAD
KWH
1212.6
1748.0
1163.0
1305.8
1406.6
1233.0
1441.0
1520.6
1424.9
1175.6
1165.0
1470.4
851.8
993.9
1273.1
ROSTON MA
CARIBOU ME
CHARLESTON SC
COLUMBIA MO
ELY NE
PORT WORTH TX
GREAT FALLS MT
MADISON WI
MIAMI PL
NASHVILLE TN
NEW YORK NY
PHOENIX AZ
SANTA MARIA CA
SEATTLE WA
WASHINGTON DC
HEAT
LOAD
KWH
COOL
LOAD
KWH
590.4
1338.4
136.3
533.2
655.0
157.6
389.1
989.1
0.2
276.4
483.0
72.0
131.4
371.7
496.8
500.6
323.7
920.8
617.6
508.5
942.1
455.2
482.0
1344.3
762.9
552.9
1245.6
619.7
377.9
626.7
LITE
LOAD
TOTAL
LOAD
KWH
KWH
233.8
256.0
173.1
195.7
160.3
160.9
204.1
217.0
155.9
210.0
233.1
140.7
151.3
310.1
207.0
1324.8
1918.1
1230.2
1346.5
1523.8
1260.6
1543.4
1688.1
1500.5
1249.4
1268.9
1458.2
902.4
1059.7
1330.6
HEAT
LOAD
COOL
LOAD
KWH
KWH
LITE
TOTAL
LOAD
LOAD
KWH
KWH
; i6aF;----------------------------------POSTON MA
CARIBOU ME
CHARLESTON SC
COLUMBIA MO
ELY NE
FORT WORTH TX
GREAT FALLS MT
MADISON WI
MIAMI FL
NASHVILLE TN
NEW YORK NY
PHOENIX AZ
SANTA MARIA CA
SEATTLE WA
WASHINGTON DC
398.8
1019.3
57.0
390.3
525.4
69.4
617.4
722.8
0.0
175.6
343.3
11.0
39.1
253.4
360.0
530.9
361.2
902.3
671.2
594.9
954.8
531.8
515.9
1297.0
760.7
560.5
1308.4
669.3
423.1
653.9
228.4
247.3
171.0
190.7
156.6
159.6
189.9
211.2
160.5
207.6
229.0
142.7
153.0
295.1
203.3
1158.1
1627.7
1130.3
1252.6
1278.9
1183.8
1339.0
1449.9
1457.6
1143.9
1132.3
1462.1
361.4
971.7
1217.2
8
6
8
8
8
8
8
8
8
8
8
8
8
ANUAL
PEAK MO DY HR
KW
1.38
1.71
1.09
1.37
1.55
1.16
1.56
1.56
0.90
1.25
1.36
1.04
1.04
1.30
1.33
12
1
1
12
1
1
1
1
7
1
1
7
1
12
12
1564.6
1746.7
2220.6
1608.3
188.4
1726.3
1688.1
1813.1
1948.5
1991.3
1706.5
1696.4
1896.1
1197.3
1546.6
1774.1
PEAK KW/YR
AS EOUIVALNT
KWH
TOTAL
EQUIVAI
KWH
6
3
4
6
4
6
3
2
2
6
2
6
2
4
6
674.8
760.6
536.9
639.0
658.5
572.0
706.3
693.0
548.2
599.2
621.6
574.8
474.8
652.2
632.4
187.4
;508.6
1700.6
1944.8
2065.1
1804.9
2147.3
2213.5
1973.2
1774.8
1786.6
2045.2
1326.6
1651.1
1905.5
SUMMER
PEAK
MO DY HR
Kw
PEAK KW/YR
AS EGUIVALNT
KWH
TOTAL
EGUIVA:
KWH
0.75
1.19
0.87
0.80
0.97
1.03
1.06
0.92
1.03
0.79
0.66
1.04
0.55
0.92
0.68
681.8
772.1
559.9
655.2
672.0
582.6
716.4
704.2
557.6
609.9
629.8
583.3
481.6
663.1
644.7
2006.7
2690.:
1790.1
2001.6
2195.8
1843.1
2264.8
2392.3
2058.1
1859.1
1998.8
2041.5
1384.0
1722.8
1975.3
SUMMER
PEAK
KW
8
8
3
S
S
8
S
8
8
8
8
I
3
8
8
ANUAL
PEAK MO DY HR
Kw
1.41
1.74
1.11
1.38
1.58
1.17
1.58
1.60
1.03
1.26
1.42
1.04
1.06
1.32
1.33
464.3 659.1
714.8
520.6
624.3
575.7
548.5
580.6
636.1
553.1
589.0
610.3
519.5
409.2
637.7
616.0
7
7
10
8
7
7
7
7
7
9
7
3
8
9
10
8
2
3
6
2
2
5
6
5
3
2
2
4
2
2
6
5
8
18
a
9
8
18
8
18
18
3
8
8
8
17
8
17
0.71
1.18
0.88
0.65
0.96
1.02
1.05
0.87
0.98
0.30
0.66
1.04
0.56
0.77
0.67
MO
DY HR
10 6 8
10 6 8
9 -2 8
3 2 18
10 4 S
7 6 8
10 6 3
10 3 8
7 2 9
7 2 I
9 4 17
7 6 8
9 3 17
10 6 8
7 2 13
190.
1
1
1
1
1
1
1
1
6
1
1
7
1
12
12
AZIMUTH
CITY
3
B
TOTAL
EQUIVAL
KWH
90.
AZIMUTH
CITY
6
6
3
2
6
4
6
6
6
2
6
6
2
5
4
6
PEAK KW/YR
AS EQUIVALNT
KWH
2
3
4
6
4
6
3
2
2
6
2
6
2
3
6
8
8
8
8
8
S
8
S
8
9
8
3
8
8
9
10
10
8
10
10
7
10
10
6
7
3
7
9
10
3
6 U
6 8
2 8
2 8
4 8
6 U
6 a
2 8
2 8
2 8
4 17
6 8
2 17
3 6
5 17
270.
ANUAL
PEAK MO DY HR
KW
SUMMER
PEAK KW/YR
PEAK
MO DY HR
AS EQUIVALNT
KW
KWH
-----------------
TOTAL
EGUIVA:
KWH
~i-----------------
1.37
1.68
0.98
1.36
1.53
1.12
1.48
1.46
0.96
1.25
1.31
1.09
0.57
1.27
1.33
12
1
1
12
1
1
12
12
8
1
12
7
12
3
12
132
6
3
4
6
4
6
6
6
5
6
6
2
5
4
6
3
8
8
8
S
8
S
S
8
1
8
1
U
8
8
0.65
1.15
0.90
0.38
0.35
1.00
0.70
0.81
0.96
0.90
0.68
1.09
0.56
0.63
0.67
5
10
7
8
9
S
7
10
8
7
8
7
9
10
8
5 8
6 8
2 8
2 8
4 8
2 3
5 3
4 8
5 3
2 8
6 17
2 9
2 17
6 8
5 17
664.8
702.7
535.4
654.7
615.6
562.6
593.6
658.8
553.2
590.5
612.8
553.7
418.5
633.6
617.8
1822.9
2330.4
1665.7
1907.4
1894.5
1746.4
1932.6
2108.7
2010.8
1734.4
1745.6
2015.8
1279.8
1605.2
1835.1
ELECTRO-OPTIC-4
AZIMUTH
CITY
BOSTON MA
CARIBOU ME
CHARLESTON SC
COLUMBIA MO
ELY NE
FORT WORTH TX
GREAT FALLS MT
MADISON WI
MIAMI FL
NASHVILLE TN
NEW YORK NY
PHOENIX AZ
SANTA MARIA CA
SEATTLE WA
WASHINGTON DC
HEAT
LOAD
KWH
374.6
949.3
54.6
362.4
526.0
66.0
595.9
661.0
0.0
172.4
327.2
3.6
30.0
239.0
350.9
COOL
LOAD
KWH
470.5
301.3
826.9
680.7
465.9
976.6
446.9
439.8
1215.5
704.3
509.4
1186.8
565.6
364.2
581.9
LITE
LOAD
KWH
212.2
229.3
166.0
174.3
126.2
153.9
165.4
191.7
156.0
199.7
215.6
127.6
143.5
291.1
197.6
TOTAL
LOAD
KU
1057.3
1479.9
1047.5
1217.4
1119.1
1096.5
1208.2
1292.5
1371.5
1076.4
1052.1
1318.0
747.1
94.3
1130.4
0.
ANUAL
PEAK
MO DY HR
KW
SUMMER
PEAK
MO DY HR
KW
1.37
1.66
0.97
1.35
1.52
1.15
1.40
1.45
1.02
1.25
1.31
1.10
0.85
1.26
1.32
0.62
1.17
0.91
0.67
0.61
0.99
0.64
0.61
1.02
0.79
0.67
1.10
0.56
0.67
0.66
12
1
12
12
1
1
12
12
9
1
2
9
12
1
12
AZIMUTH
CITY
ALBUQUERQUE NM
BOSTON MA
CARIBOU ME
CHARLESTON SC
COLUMBIA MO
ELY NE
FORT WORTH TX
GREAT FALLS MT
MADISON WI
MIAMI FL
NASHVILLE TN
NEW YORK NY
PHOENIX AZ
SANTA MARIA CA
SEATTLE WA
WASHINGTON DC
HEAT
LOAD
KUH
COOL
LOAD
KUH
343.1
509.3
1190.8
115.6
478.5759.2
141.4
735.7
753.3
464.2
300.5
039.A
617.6
492.2
894.4
446.4
441.8
1211.7
700.9
500.2
1219.0
557.8
362.9
599.6
859.3
0.0
237.9
413.9
62.5
121.2
322.3
452.1
LITE
LOAD
KWH
99.4
207.7
234.7
160.2
175.6
122.5
149.3
175.2
199.2
144.7
195.6
216.4
120.1
128.9
292.1
198.0
TOTAL
LOAD
KU
ANUAL
PEAK
KW
1195.9
1191.2
1726.0
1115.9
1271.6
1372.9
1185.1
1407.4
1500.3
1356.4
1134.3
1130.5
1401.7
807.9
977.3
1239.8
1.24
1.38
1.71
1.10
1.38
1.55
1.17
1.55
1.57
0.95
1.25
1.37
1.01
1.07
1.31
1.35
AZIMUTH
CITY
ALBUQUERQUE NM
BOSTON MA
CARIBOU ME
CHARLESTON SC
COLUMBIA MO
ELY NE
FORT WORTH TX
GREAT FALLS MT
MADISON WI
MIAMI FL
NASHVILLE TN
NEW YORK NY
PHOENIX AZ
SANTA MARIA CA
SEATTLE WA
WASHINGTON DC
HEAT
LOAD
KWH
COOL
LOAD
KU
409.9
603.0
1350.5
141.8
545.6
377.6
164.0
904.6
1002.0
0.5
294.2
492.9
75.7
140.4
379.4
504.8
697.1
455.5
239.3
349.9
567.4
451.7
374.4
409.0
438.4
1258.0
703.7
506.2
1163.6
555.1
337.0
575.9
LITE
LOAD
KUM
150.1
237.6
262.9
173.5
200.2
163.6
163.8
208.2
223.2
157.2
214.2
240.5
140.7
155.9
315.6
213.7
TOTAL
LOAD
KWH
1256.1
1296.1
1901.7
1165.2
1313.1
1493.0
1202.2
1521.8
1663.6
1415.6
1202.1
1239.6
1379.9
351.4
1032.0
1294.4
6
3
6
6
4
6
6
6
2
6
4
2
5
6
6
8
8
3
5
S
S
3
S
3
9
3
3
6
9
S
PEAK KW/YR
AS EGUIVALNT
KWH
TOTAL
EQUIVAI
662.5
726.2
512.1
626.6
589.4
544.5
590.1
639.5
539.4
585.2
612.4
510.0
414.3
643.0
619.1
1719.9
2206.1
1559.6
1944.1
1706.4
1641.0
1798.4
1931.0
1910.0
1661.6
1664.6
1825.0
1161.4
1527.3
1749.6
SUMMER
PEAK
MO DY HR
KW
PEAK KW/YR
AS EQUIVALNT
KWH
TOTAL
EGUIVAI
KWH
0.71
0.73
1.19
0.85
0.67
0.99
0.99
1.09
0.90
0.95
0.76
0.65
1.01
0.59
0.81
0.67
594.6
677.5
767.8
542.2
646.6
668.0
570.7
715.3
703.0
534.1
599.1
626.7
573.3
484.9
659.4
641.2
1790.4
1858.7
2493.8
1658.0
1918.2
2040.9
1755.8
2122.6
2203.4
1990.E
1733.4
1757.2
1975.0
1292.9
1636.6
181.0
7
10
a
7
7
7
7
7
9
7
9
9
9
5
8
3'18
6 8
2 a
2 9
5 is
6 8
5 18
3 19
2 3
2 8
6 17
2 9
2 17
6 9
5 17
KWH
90.
MO
12
1
1
1
1
1
1
12
1
S
1
1
7
1
12
1
DY HR
4
2
3
4
6
4
6
2
2
2
6
2
6
2
3
5
9
8
9
3
9
9
U
S
3
3
3
U
S
1
3
8
7 2
10 6
10 ~6
8 2
10 3
10 4
7 6
10 6
10 3
3 2
7 2
8 4
7 6
9 2
10 3
3 5
9
9
a
9
3
9
6
3
8
8
8
17
3
17
8
17
130.
ANUAL
PEAK MO DY HR
KU
SUMMER
MO DY HR
PEAK
KW
PEAK KW/YR
AS EOUIVALNT
KWH
TOTAL
EGUIVAI
KWH
1.23
1.42
1.74
1.12
1.39
1.58
1.18
1.59
1.61
0.93
1.26
1.43
1.01
1.09
1.32
1.37
0.74
0.77
1.20
0.84
0.84
1.00
0.99
1.09
0.96
0.99
0.76
0.67
1.01
0.55
0.95
0.69
597.4
695.7
783.7
561.2
662.0
682.3
590.4
725.3
713.7
541.6
609.6
636.2
580.9
490.3
668.7
654.9
1953.4
1991.9
2685.4
1726.5
1975.2
2175.2
1782.6
2247.0
2377.3
1957.2
1911.0
1975.7
1960.8
1341.7
1700.6
1949.2
AZIMUTH
1
1
1
1
1
1
1
12
1
6
1
1
7
1
12
1
2
2
3
4
6
4
6
2
2
2
6
2
6
2
3
5
3
3
5
8
3
8
3
3
3
3
3
9
a
3
S
3
7
10
10
3
10
10
7
10
10
6
7
3
7
9
10
10
2 9
6 0
6 9
2 3
2 3
4 3
6 3
6 9
2 U
2 8
2 3
6 17
6 8
2 17
3 3
2 8
270.
HEAT
COOL
LITE
TOTAL
ANUAL
SUMMER
LOAD
LOAD
LOAD
LOAD
PEAK MO DY HR
PEAK
KU
KWH
KU
KU
KU
KU
----------------------------------------BOSTON MA
407.5
435.8
232.5 1125.8
1.37 12 6 8
0.63
CARIBOU ME
1027.3
326.1
252.6 1606.0
1.63
1 3 3
1.16
CHARLESTON SC
59.3
845.8
173.5 1073.2
1.01
1 4 9
0.33
COLUMBIA MO
394.5
620.9
193.5 1209.0
1.36 12 6 3
0.85
ELY NE
533.8
542.0
159.9 1235.7
1.53
1 4 3
0.77
FORT WORTH TX
73.3
99.2
163.0 1134.4
1.15
1 6 3
0.99
GREAT FALLS MT
630.1
491.9
194.0 1316.1
1.43 12 6 1
0.73
MADISON WI
734.2
471.3
216.6 1422.6
1.46 12 6 8
0.65
MIAMI FL
0.0 1225.6
160.5 1336.1
0.94
3 5 3
0.94
NASHVILLE TN
162.6
707.1
211.3 1101.4
1.25
1 6 1
0.37
NEW YORK NY
350.0
519.3
234.2 1104.0
1.32
2 4 S
0.67
PHOENIX AZ
3.2 1241.8
142.7 1392.7
1.07
7 2 8
1.07
SANTA MARIA CA
40.2
611.4
155.5
307.1
0.91
12 5 1
0.71
SEATTLE WA
259.2
382.5
302.3
944.0
1.27
3 4 3
0.65
WASHINGTON DC
363.2
602.1
209.2 1174.5
1.32 12 6 3
0.67
CITY
133
PEAK KW/YR
TOTAL
AS EOUIVALNT
EQUIVA.
KWH
KWH
-------------------------------
MO DY HR
7
10
7
8
9
3
9
10
9
7
3
7
5
10
8
3 13
6 S
2 3
2 1
2 1
2 1
5 3
5 I
5 a
2 S
6 17
2 3
3 3
6 3
5 17
663.2
712.4
531.0
647.9
597.2
560.2
603.9
649.3
533.7
592.4
611.9
542.5
432.8
638.9
618.2
1799.0
2319.3
1609.2
1956.9
1332.9
1694.6
1924.9
2071.9
1924.8
1693.8
1715.9
1935.2
1239.9
1582.9
1792.7
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136
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