Criteria for Evaluating an Energy-conserving Design

8

Criteria for Evaluating an Energy-conserving Design

8.1 V A R I A T I O N OF CRITERIA

The stochastic, random, sporadic and measurement processes in energy systems can cause wide variations in recorded data and in estimates. If we graph data or estimates of two variables there is a scatter of individual values (Fig. 8.1). The data are described first as a central tendency for the higher density of the scatter, then as a variation for the scatter from the central trend. Traditional statistical formulations for t h i s 39'6v'68 a r e generally not in a convenient form for interpreting and applying energy-related data. Rather than group data according to the dependent variable we mainly group according to the independent variable, which is predetermined by the design conditions or control operation. Groups are established for the independent variable along the x axis in equal intervals (Fig. 8.2). The statistics for each group are now discussed separately.

A group is divided into equal classes along the y axis in order to find its frequency distribution. Figure 8.3 shows their progression from a histogram, polygon or relative frequency to a continuous frequency distribution. This graphical step is an essential process because it determines the type of statistics that can be meaningful. For instance, with solar radiation data two-peak bimodal distributions often occur from the changes in cloud cover. Humidity ratios for outside air can be similar, and air temperature distributions are often skewed for a particular time interval.

Central tendencies are considered in terms of an arithmetic mean. Figure 8.4 shows how this is derived as a first moment of area. Put simply, the area of the frequency diagram balances about the mean. A mean is quile satisfactory for normal-like, bell-shaped curves and averaged data such as in

187

188 Design integration .['or minimal energy and cost

energy consumption. But with skewed and bimodal distributions a mode is more appropriate since it relates to the sizing of equipment for each limiting condition (Fig. 8.5). Where there is little data on the shape of the distribution, a median is very useful as a halfway value between the maximum and minimum (Fig. 8.6).

Variation from the group mean is difficult to visualize. With most energy data from buildings the scatter is broad within a range of values between YM and Ym (Fig. 8.3), about a mean assumed to be at the median. A deviation is the extent a value is away from the mean. A maximum deviation, dM, is the half-range derived from two data points. A mean deviation, d, for a random distribution is about 0-3-0"5 of the half-range. A variance, s a, in Fig. 8.7 is a mean second moment of area or 'average inertial effect' about the group mean. A standard deviation, s, is a square root of the variance or a root mean square of the deviations. For a random distribution the standard deviation is about 0.6-1.0 of the half-range and is the basis for estimating excursions, +e , in variation and trend analysis.

Probability is the likelihood of an event occurring between certain limits. Graphically, it can be represented by the area in the frequency diagram between the limits (Fig. 8.8). It is used to determine the confidence of predictions and the certainty of trends.

Normal distributions are well described and widely applied in statistical analyses for variation, sampling, error estimation and decision theory. 39'67 When analyzing energy data the first step is to t ransform typical distributions into normal-like distributions (Fig. 8.9). Bimodal distributions proport ion to their areas. Skew distributions are often normalized by exponential functions. The normal-like distribution (fly) is then transformed into a standard form (F, z) in Fig. 8.10 by the usual Gaussian function. Areas under the transformed curve provide the confidence levels, p, for the confidence limits, zp, with a standard deviation of unity.

Excursions, _+e, are defined as the standard deviations for the normal distribution of the design data from its mean (Fig. 8.11). Mathematical texts call it error estimation, but in physics it is considered as a naturally random excursion in a parameter. An appropriate standard deviation can be estimated in three ways. If the normal curve is found from, say, over 30 data points (N > 30), s is determined directly without probability. If N < 30 the finite sample has a standard deviation o f s e, which requires an adjustment to a chosen level confidence through the confidence limit Zp and the number in the sample. Four points are a minimum for fixing an assumed normal curve; a 90% confidence level is common which provides a 0"82s e excursion. If only the two range limits are known the standard deviation equals the half-range, s =dM, ZM = 1 andp = 68%. This is the maximum standard deviation, but it is lowered for a higher certainty for the limits by dividing by the probability

Criteria for evaluating energy-conserving design 189

limit, z~. Thus the excursion could be considered as simply 0.61d M, with 90% certainty if no other data are available.

Combining the excursions of various parameters is important for resolving the overall accuracy of measurements and the variation in mathematical models. Figure 8.11 shows that if the model is the algebraic sum of the parameters then the combined excursion is the root square of the excursions. A fractional excursion, _+ ke, is a ratio of the excursion to the mean value and is a measure of accuracy in physics. If the model is a product then the combined excursion is the root of the squares of the fractional excursions. For any model, the combined excursion is the root of the squares of the excursions times their partial derivatives. Thus the excursions of each parameter can be traced through the measurement accuracy and the power- energy-cost-pr ior i ty models in a straightforward manner. 25

A comparison of two means is important for deciding whether two designs or monitoring tests are essentially the same. Are the results of one scenario really better than another? Figure 8.12 shows a simple method for determining whether a difference between the means of two scenarios are significantly the same. 25 A scenario will peak at the mean, Ya,- )b,r' with 100% certainty or 0% uncertainty. An expected value away from this mean adds to the uncertainty about the scenarie achieving its purpose. Thus with 90% certainty or 10% uncertainty we could expect a lower value in scenario 'a' by 0.25 for the normalized distribution, and a similar higher value in scenario 'b'. This spreads the means, Ayah. As long as the means are within this range the scenarios are the same, with a probable 90% certainty. Now, this is related back to the variable through the excursions _+e and fractional excursions -k-k e in Fig. 8.12. For example, it is quite common to find 20°/,) fractional excusions in power data; consequently means separated by 0-25 (0"2 + 0-2)= 10% would not be sufficiently different, and the changes in a mean of less than 10% could not be measured with sufficient certainty. Another case is in comparing benefit for resource ratios having 50% fractional excursions. The fractional sameness is 0-25 (0"5+0.5j= 25%, which suggests that a ratio would have to exceed 1"25 to be significantly more useful, or lower than 0-75 to be detrimental.

Regression is a process of reducing data to its basic variations. The means of the groups are plotted in Fig. 8.13. Maxima and minima values are noted for the range. An envelope, A~a b, is created for the same mean for 90% certainty 0"15 × 2 x d M from the median; that is, the middle-third of the range. A curve is sketched through the means and within the mid-third envelope. This is studied in terms of the expected relationships, and modeled as a mathematical function chosen to represent the curve. This is a very important step. Subtle changes and expected inflections should be modeled rather than simply reducing them to a linear regression. The regression

190 Design integration for minimal energy and cost

function parameters are found by inserting coordinate data from the sketched curve, only since the sketching was part of the regression process. For inflections and limits the gradients may be inserted into a differential of the regression function. Parameters are found from the simultaneous equations. A coefficient of correlation, r, is useful for finding the fraction of the variation in y that is accountable for by the variation in x. Analysts tend to place too much emphasis on the correlation rather than the variations from the trend itself. A curve within the mid-third range ensures sufficient correlation. For design and feasibility analysis it is more important to know the excursions and fractional excursions about the mean trend. These are calculated and graphed separately in Fig. 8.14. Group limits are included because these represent the boundaries for the greatest possible excursions. Comparing various trends now becomes a simple process since the trends would be the same if the difference in the group means was less than a quarter of the sum of their excursions. Greater separations than the sameness criterion could suggest separate influences for the trends. Fractional excursions are only useful for resolving products, since the origin for the mean ~ can be moved. For example, an outside air temperature origin can be an inside thermostat setting for the transfer of power. Measuring instruments are usually calibrated for a zero origin. However, a sound power level has an origin at a hearing threshold. Fractional excursions have no meaning at the mean when )7=0. In this case the excursion limits are substituted in an equation to find the new excursion limits.

Variations in the values of the parameters have a tremendous impact in the approach to energy-conserving design. For instance, consider the sum of 50 parameters of 10% accuracy in a life cycle cost. The overall accuracy could amount to 70%, making a typical payback of 7 _+ 5 years. This is hard for a scientist to adjust to, because lessening the precision of a prediction is contrary to the definitive nature of his discipline. It is analogous to applying the uncertainty principle in physics. For a traditional designer, variation suggests a lack of decision so that anything can be justified. It is like the saying 'statistics can prove or disprove anything'. For a designer it is essential to think of everything in integration as a goal-directed trend. With so many factors influencing the management and design process, each decision and action should complement the overall effect. This is why a reasoned preconception, or simply experience, is important in reducing the reiterations of design. Some would argue that this preconception inhibits innovation. A variety of solutions can come directly from the variations themselves. This is why the vagaries of climate and the diversities in people's activities set an exciting trend. In fact, it is this expression that can become the esthetic. Even the term minimal suggests a trend, in contrast to 'minimum' which is deterministic.

Figs

8.1

8.

14.

Stat

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20

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%

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ain

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± [~k Z

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8.1

1.

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on (

erro

r) (

inte

rval

) es

tim

atio

n,

+e.

& ~b

2"

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ns

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Ya

> Yb

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5% T

ail

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e 1.

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%

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inty

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ab .

....

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val

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dMb

with

10%

un

certa

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SAME

NESS

OF M

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enar

ios

a,b

are

the

sam

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90%

cer

tain

ty w

hen

...

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~

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a + Z

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]

0.25

[ e

a +

e b ]

-- 0.

15 [

dMa

+ dM

b ]

FRA

CTI

ON

AL

SAM

ENES

S O

F M

EANS

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~. A

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= 0.

25 [

kea.

Y a+k

eb(y

a-k

eab.

ya) ]

kea b

~

0.25

I k

ea+k

eb ]

--

0.15

[ dM

a+ dM

b ] /

Ya

Fig. 8.

12. C

ompa

rison

of tre

nds, a

, b.

2 2

REG

RESS

ION

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GROU

P

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IND

IVID

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n d =

n

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roup

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r =

l-

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a fr

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ria

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n

in

y th

at

is

acco

unte

d fo

r by

th

e va

ria

tio

n

in

x .

Fig.

8.1

3.

Gro

up

mea

n re

gres

sion

.

c~

2"

2"

oo

ME

AN

TR

EN

D

Y

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m

Y

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CY

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±k

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Criteria ./or evaluating energy-conserving design 199

Accuracy or fractional excursion depends on the nature and method of measuring the parameters. Physical data for materials may be precise under laboratory conditions but manufacture, construction and aging can readily introduce variations of 10% or more. Modeling the relationship in design is often within a 10% accuracy, but the modeling for the variations in climate, costs and performance may be greater than 20%. Demands can vary over 100%, which is common in the domestic use of hot water and electricity. These realities stress that only trends are being observed.

Where should money go for research in energy-conserving design'? The author suggests that the benefit for resource ratio is looked at as a guide. The outcome of any research venture must anticipate an increase in the ratio. A point that has not been stressed is that research should also look for significant ways to decrease the variations. Frequently, the fractional excursion exceeds the percentage gain in benefit, which makes the trend uncertain. The least effective direction is to improve the accuracy of acceptable modeling in design and laboratory testing, which is a point that scientists may resist. Methods of controling climatic variations through appropriate siting, orientation and sunshading are well understood, but designers need to express them in their projects. Research here is in the designer's education in the studio. Developing ways to control the wide fluctuations in user demand is another fruitful direction. Electric utilities are interested in scheduling activities, programming use, daylighting and thermal storage. Policy makers could well be concerned with stabilizing the fluctuations in energy pricing and financing opportunities.

Example 8 Variation in pre- and post-1970s office estimates

The strategy for estimating the excursions is to work from the demand power

equipment loads, utility supply, utility energy use, annual and capital

costs, life cycle costs to priorities. In this examp[e only a few

representative cases for scenario b are taken :in order to illustrate the

process. Within each of the originating equations the excursions (±) and

fractional excursions (x) are inserted and combined by the root-square

method in Fig 8.11. Also a fractional excursion for the modeling of the

equations is applied to allow for their empirical derivation and

regression.

People - Sensible heat - perimeter

PA : (I~'I>)(70~15)(1"3~'2)(x'15) = 9['152+'212+'152+'152] ½ = ~ = ~ - i0


Luminaire heat 1 1 , i 1 1 PA = 214(x. O5) t (x. 1 ) ~ ( x . 1 ). ~ x . 2) . -~ ( x . 05)-VS(x. 05)77(x . 15) 1.1 (×. 04) ,..

. . . . j(x.2)(x.1) 2 i = 1'7[ '052+'12+'12+'22+'052+.052+.152+.04 +.22+.12] 2 = 1.7(x .38) = (_1.7+.64)

Daylight~ -. 25(x. 4)/Sin(75,5+o 5) EANMBum = 128000(x.15) e (x.1)

Sin(75.5 +-.5) = .97(x.007 .9~ Cos75.5) = .97(x.13)

exp -.26[,42+.1321½ = -.26(x,42)

e -'26(x'42) 77(Xo42 .26 e-.26) . = . ~ .26 = 77(x.028) Grad

_(.26+.1) _~.36+ 1 .852

= , 000[, 2+0282+ ix18> , o + oo) I : t

= 1 99000(x.18).97(x.13).29(x.2).003(x.05 I02)(x.i) + Lbl

1 99000(x .18) .97(x .13) .24(x .2) .021(x .05 7½)(x.i)

2 _i = 26~6[o182+o132+.22+.052x10+.123½ + 154t. 182+.13 +.22+o052x7+oi~ 2

= 26.6(xo35) + 154(x.34) = (26.6+9.3) + (154+52.4) + -i = (i81 -[9o32+32.&2] 2) = (181+i~3) = 181(x.29)

E~uipment - floor

PA = (6+-'6)+(6+-'6)+(i0+I) = (22 +[o62+.62+!2]½) = (212+1.~) : 22(x.06)

Conduction - window I summer

PA = 1.5(X. 02) ((33+3) _ (25 +. 9) ) (x . 1)~(. 0z#~+. 008)*( . 0063 + . 003)*( . 17"-. 03)+. i . 4°5 +(~ 0063+° 003)+ (. 12+o 01) )

+ 1 = .33(x.02)(8 -[32+.9212)(x.I)/( 34 + 2 2 2 2 2 ~

o - [ .008 +.003 +.03 +.003 +.01 Jz) 7o8 .022+o0332/.342+3.12/82+ 12 ½ = Z.8(Xo41) = (7.8+3.2)

Solar transmission - summer

PA = ' 33(x. 02). 85(x. 05) 1350(x. 15)o 77(x. 028). 2 . 95(x. 13). 85(. 04). 85(. 02) (x. I ) 2 2 2 2 2 2 2 2½ = 40.3[ .02 +.05 +.15 +.028 +.13 +.04 +°04 +.1 ] = 40.3(x.24) = (#0.y9.6)

Chi l l e r - per imeter - summer

Load PA =[(9+3)+(22+1'3)+(6+2)+(40'3+9°6)+(I'7+'7)+(7"8+3'2)+(2"7+'I) + ....

,..+(4.8+I.9)+(6.9+2o6)+(ii.8+2.4)](x.1)

= (I15+11.6)(x.i) = 115(~.14)= (iiJ-16.3)

Electricity PA = 28.8(x.14)(x.2)(x.l) = 28.8(x.26) = (28.8+-~.6)

Electricity PA = (19+5'3)÷(28'8+7'6)+(Ii'8+-2"4)+(22+1.3) = (82.1+~.7) = 82,!(x.12) perimeter

Energy - electricity - perimeter - summer

wp : Ap (x.05)82.1(x.12)5.~ I .22~(x.2)(x.i2)+.o43(x.3)(x.2)+.123(×.2)(x.3)(x 2) I = Ap .45(x. OS)(X.12)(( .224t .052)+(.O43t.016)+(.123t .051)) L03

= Ap .18 103[.052+.122+o192] ½ = Ap.18 i03(x.23) = Ap 103(.18t.04)

Criteria .for evaluatblg energy-conserving design 201

Life cycle costs - electricity - perimeter - summer

c~ : (257tsO+3~(Xol)(x.23)( x.2 ~0~) : (2~7±~i)+(3~t2~)

: (6oG2~9) = Boo(~.~) In life cycle costing we can expect accuracies abcut 40%/~ and payback periods

2 ~ = 1.4 times this of about 60%

Cgmparisons

W i t h f r a c t i o n a l e x c u r s i o n s o f a b o u t 40~ i n s c e n a r i o s t h e c o m p a r a t f v c

l r a c l i o n a l e x c u r s i o n , f o r a s i g n f i i c a n t s e p a r ~ t t o r , of t h e i r m e a n s , ~'i~ ~ . ] 2

b e c o m e s . . .

keb c : [x.25(x.A+x.4)] = (x.20)

8.2 CRITERIA FOR R E G U L A T I O N

A community, for its own preservation and welfare, establishes laws and regulations to enforce those laws. The government of that communi ty reacts to crises depending on those parties representing the public interest. In socialist states a government embodies all the parties involved and dictates control from the resource to the demand. A nationalized industry is a prime example. As long as the resources flow, the public are serviced, and the people are employed there is little incentive for economic improvement. In a free enterprise state people can do what they like, provided that it does not infringe upon the laws of the community. The concept allows for a competitive market to determine the resources, supply, distribution and demand. Profit is invested in capital, which cycles to perpetuate the system. Economics becomes the essence of the process. A capitalist interest represents an investment in goods for their own sake rather than for the need alone. This tends to waste resources and does not encourage planning for the future.

The 1970s brought worldwide recognition that our resources and environmental pollution were issues for global survival. Nations and communities are now involved in conserving resources and controling pollution. Without a crisis, few communities could gather the combined support to do this voluntarily. In democratic societies a majority vote of its representatives determines the law. There is a perpetual lobbying to represent the various sectors of interest in the community. Worldwide recessions have drained the fiscal resources of countries, which makes it difficult for governments to foster conservation.

In a socialist state the priorities between competing government bureaux play a more important part in the allocation of resources. The benefit for resource ratio could be used to weigh those interests. Benefits could be extended to include those gains in production within a broader context of


energy issues. Resources are generally shared more equitably in these communities, because avoiding waste is an inherent part of their social culture. The emphasis shifts to the benefits in performance.

Free enterprise implies an unregulated situation driven by economic opportunities. Communities are questioning this premise through laws involving environmental and occupational health and safety, non- competitive monopolies, city planning, land preservation, civil rights and now a wasting of resources. How can this be regulated to satisfy both the economic and social goals? A government should not regulate an energy design to the extent that they become the designer themselves, because this would then make them legally responsible for the working and safety of the design. Evaluative parameters for regulatory purposes should be the same as those used in construction by a designer. Parameters such as energy demand and resources should not be limited by regulation because they are determined by the user's activities, for which the designer and regulator have no control in a free enterprise system. It is possible to limit the input, efficiency and output of a distribution, but not all three at once. One aspect must float in order to permit alternative designs. Similarly, it is confusing both to set a performance and to allow a certain design at the same time. Performance of the space, envelope and service demands (Fig. 4.2) should be regulated to ensure that the design complements the activities. This should be specified, first according to human response parameters, and then in terms of the environment and equipment. Regulations should provide acceptable methods of analysis to relate those responses to the power distribution. A minimum allowable working efficiency for each alternative component should be regulated so that alternative arrangements can be selected by the designer. This can be an extension of the appliance labeling laws. Energy efficiencies would be used for intermittent and varying loads. A simple life cycle cost procedure should be provided for a designer to compare his alternatives rather than those of the regulator. Criteria for the cost parameters and the utility resources must float and should not be limited by regulation.

8.3 CRITERIA FOR CONSERVATION

8.3.1 Optimal performance for activities, p{B}opt

The fundamental requirement for any conservation scenario is that the design must provide an environment that will complement the activities. This means that the demand line in Fig. 4.2 must meet an optimal performance to maintain the envelope, space and service conditions.

Criteria .for evaluating energy-conserving design 203

A regulatory authority has no mandate to enforce an optimal condition, but it is responsible for the limits of performance in terms of health and safety. This is why it was so important in Section 8.2 to couch the regulations in performance terms and state how this could be related to the demand power. Any challenge could be resolved through public hearings before enactment rather than afterwards in a court of law.

There is considerable confusion between optimum, minimum and maximum criteria. Voluntary standards have been developed by the American Society of Heating, Refrigeration and Air-conditioning Engineers (ASHRAE), the Illuminating Engineering Society (IES) and many other groups.l 3,5 9.1v.as These are professional guides which originally stressed the optimal operating criteria for design. Federal regulators and building code officials encouraged the establishment of limiting criteria for health and safety. Economic pressures are now doing the same thing, but moving towards the limiting criteria increases the risk of poor performance and increases the hazards with those conditions. It is difficult to comprehend why guides for good design should be compromised when they should be supported on the basis of good, economically justified, performance. Present debates center on what constitutes suitable parameters and criteria for avoiding indoor pollution and poor illumination. The benefit for resource ratio in Section 7.1 illustrates some of the trade-offs in these decisions.

There is a trend to resort to the recommended practices of countries that are used to conserving their resources. Even here one should be cautious because the materials and tasks can be quite different. Building and cleaning materials themselves can be more toxic, and many visual tasks that used to be illuminated are now self-luminous. We are experiencing an explosion of diversity in design, which means that we will have to integrate a broader range of parameters and criteria so that each may complement the intended activities.

8.3.2 Minimal space for power distribution, Aserm

Space for services and power distribution is a necessary encumbrance on the planning. It takes up valuable, productive floor areas. A further 25% of the occupied floor area is necessary for corridors, lobbies, egress, elevators, toilets, telephones, and electrical and riser ducts. Another 10% of the occupied floor area, or 1 floor in 12, is needed for central plant such as air handlers, filters, sprays, refrigeration, cooling towers, fans, boilers, pumps, tanks, hoists, transformers, control panels, etc. Ducts, terminal units, cables, luminaires, sprinklers and so on represent a need for vertical space which imposes on the structural height.

There is a move towards dispersing cooling and heating equipment in the


ceiling space and in the core, using fan coil terminals and air handlers for each demand zone. Locating fan coil units over the occupied space is not recommended since most commercial equipment is noisy in the lower frequency ranges and is difficult to access during working hours. However, equipment could be placed over corridors or over services in the core. Outside air should be processed separately for humidity control so that there are no wet coils near the occupied space, which could produce health hazards such as Legionnaire's disease. Dispersing equipment can also make it more difficult to size the ducts and arrange ventilation for a full flow of outside air during mild weather economizer cycles.

Perimeter cooling and heating units are generally part of the building capital and are reflected in the lease cost. Ceiling equipment is often not part of the lease and the lessee has to arrange to have it designed, installed and maintained. Consequently, there has been a rapid growth in packaged integrated ceiling arrangements of panels and units on a T-bar grid. Dual duct distributions are obsolescent, particularly as USA energy codes do not permit the cooling and heating of air at the same time with non-renewable resources. This is paving the way for utility leased packages as a completely serviced 'plug-in' module. These, in turn, could interface with alternative modules with cogeneration, heat pumps, river cooling, solar ponds, district waste heat, fuel cells and geothermal combinations.

Elevators require considerable space and electrical power. Piggyback arrangements 4° with one car over the other are possible by splitting the demand with escalators at the entry level. Flexible work hours, and preprogramming elevators by moving the call control from car to lobby, could spread the demand over time and help to reduce the number of cars.

8.3.3 Minimal demand power, PDm

The demand for power directly relates to the performance of the environment to support the activities. It is a resource in the benefit for resource ratio (Section 7.1), which means that it can be traded with benefits within the limits of health and safety. Table 4.2 lists typical powers of equipment in the occupied space. Management should ensure that they purchase energy-efficient, low-power appliances to do the job effectively. The ventilation and lighting demands were discussed in Section 8.3.1.

Elevator demand power is generally not included in the regulatory codes. However, the very high cost of elevators (Table 4.7) provides sufficient pressure on the designer to minimize the number of cars.

It is not fruitful for a regulator to make the power demands more stringent since it is the use of power over time that determines the energy consumed and cost. Overtime, shift work and flexible time make the use indeterminate.


A simple life cycle cost procedure advocated in Section 8.2 would encourage a designer to discover the merit of conservation in a self-evident way.

8.3.4 Maximal and minimal efficiency for components, KOl M. KwoiM and KWDlm

The single most effective guide for energy conservation is an efficienl distribution of the power from resource to demand. An instantaneous power efficiency through a component is the power factor (Section 3.2.1). This varies according to the simultaneous temperature and voltage differences, Integrating the power over time provides the energy factor for a componen t For steadily working components these are the same, but with storage and functionally dependent temperature differences the energy factor will be less than the peak power factor.

Power factors relate to the sizing and capital costs of the design, whereas energy factors relate to the economics of resources and annual costs. Sizing of equipment depends on the peak loads and a maximal power factor to handle the power distribution. Where the efficiency relates to the demamL as in the envelope transfer, a minimal power factor becomes the criterion.

Regulators should provide allowable limits for the energy factors for each component for specified working ranges. Continuously running boilers, engines, motors, etc. are reasonably straightforward through their power factors by measuring the power out over the power in to the component. Temperature-variable components, such as heat pumps, solar collectors, daylight and storage, should have specifications for seasonal energy factors according to those regional cycles. These efficiencies need to be maximal with minimum limits. Envelopes can be specified as a 'relative energy factor'. Thus, if the envelope efficiency is related to a massless, frictionless surface, or simply a single glass window, the relative energy factor equates to the conductance, t7 (U-factor, etc.). Because it is a demand the efficiency has to be minimal with maximum limits.

There is a trend for energy regulations to over-insulate the envelope. 1 t Section 5.2 showed that seasonal energy and annual cost were dependent on both the outside air temperature, ventilation rate and the envelope conductance. Thus a trade-off product in the benefit for resource ratio for insulation would become:

kBRba = • { DWmO'QAa + kAEnvF'ha ] , _ DWmO.QAb + kAEnvF-h b

lout. air~reaslenvelope 1.2 /1/s Iw/m2. °c .l [~tm/mi n [~tu/h. ft2. °F


As the conductance, h, is decreased with more insulation the benefit is improved, with an increase in capital resources for the extra insulation. With small envelope-to-floor area ratios, as in high-rise offices, or with over- insulated homes, the outside air ventilation governs and the benefit of insulation becomes very marginal.

A seasonal energy factor for the whole building efficiency can be assessed by taking the demand over the utility supply energy. This tends to unity. In summer the high efficiency of compression refrigeration is offset by the extra cooling loads from the occupancy, lighting and envelope gains. In winter those spatial gains tend to compensate for a poorer heating efficiency.

8.3.5 Minimal peak utility power, Pum

Peaks in utility supply determine the capacity of the utility plant and their capital investment. A constant load of about 0.8 of the full capacity would be desirable. Electrical power generation is the most affected, since the transmission has no storage and the system relies on reserve peak power generators and load shedding over a connecting grid.

The demand for fuel peaks in winter when the climatic resources are at their lowest. Hydroelectric storage in reservoirs and biomass stockpiling are possible alternatives. Refined fuel can only be stored for about three months, and the balance of refined products is in set proportions. The effect is to seasonally lower gasoline prices in order to produce heating oil at a higher price. Cogeneration could help to reduce those variations. Coal can be stored but labor and freezing weather can govern its mining, transportation and handling. Hydro and geothermal energy fluctuate with water availability. In the USA this is mainly in the spring thaw, and in equatorial regions during the monsoons. Agricultural waste has a finite life in that it digests in time. Well gas can be quite consistent.

8.3.6 Minimal utility energy and resources, W v v m

Governments are generally concerned with minimizing the depletable or non-renewable resources of the utilities. A utility seasonal energy factor of the demand over the resource energy can be used to assess this efficiency. Very often, this is about unity because the electricity generation is only about 0"3 efficient (Table 6. le) during the peak refrigeration period. Without the service and process demands this has been called a resource utilization factor, RUF.

Energy codes 13.~ s.~6.66 usually restrict the utility resources to an 'energy budget' by setting a maximum allowable annual utility resource energy


density for the conditioned space demands. Values depend on climate and use but offices are in the range 0-7--1-8 GJ/ym 2 (60-160 103 Btu/y ft2). The term 'energy budget' should not be used since it can be confused with a cost budget. In Section 8.2 it was suggested that this regulatory approach should be avoided. If the resources are not allowed to float in a free enterprise system the economic alternatives are inhibited.

The following list gives an idea of the utility supply energy breakdown in a high-rise office building in the U S A : 29

Air distribution fans 20-30% Lighting + heat removal 3 0 ~ 0 % People heat + sweat 20% Outside air ventilation 10-20% Envelope 10-15% Elevators 5 10% Pumping 0.4 Water heating 0.1

This distribution of utility energy suggests that attention should be drawn to the fans and lighting. Variable speed and pitch fans, larger ducts, shorter runs, plenum ventilation by the wind pressure, or even opening windows in cleaner cities could be solutions. Lighting almost double-counts the demand because its heat has to be removed. Return air of wind ventilation through the plenum may be an alternative. Sunshading the envelope in hot climates could have a number of advantages. For instance, sunshading could avoid high radiant glass temperatures that would require cooler air, avoid the direct solar gains, and assist the distribution of daylight to reduce the electric lighting demand.

8.3.7 Minimal capital cost, Ccm

Each conservation scenario involving construction has an associated capital cost. The size of equipment and materials relates to the peak powers that those components have to transfer (Section 6.2). The owner is concerned with minimizing the capital and looks for the benefits that may accrue through performance and in avoiding future costs. Costs for a conventional design are readily justified, but alternative scenarios need to be argued in terms of account costs over a life cycle. The resource probabilities of the benefit for resource ratio provide a method for setting the priorities.

Energy-related components include practically all of the building, except perhaps the structure, furniture, partitions and surfaces. The professional responsibility for this design is reflected in the capital cost for the


construction trades. In high-rise offices in the USA one could expect the following breakdown in construction costs:

Mechanical 40-50% Electrical 10-15% Structural 20-25% Architectural 1 0-15 % Plumbing 5%

In these circumstances the responsibility for design integration is dominated by the engineering disciplines and not by the traditional architectural services. The management process (Section 1.2) is likely to take over the responsibility for coordinating the integration process of design. Architects, engineers and applied scientists would then be managed as independent consultants or brought together in a joint venture for a specific project.

8.3.8 Minimal annual energy cost, Cyu m

The annual energy costs mainly consist of the monthly utility bills. Maintenance and plant operation represents a small portion, perhaps 1-5% of the utilities. With dispersed terminal units, maintenance could be a trade- off between higher labor costs and lower parts costs. A conservation scenario is justified in terms of a lower utility bill.

People and corporations in the USA can generally afford to pay utilities to about 3% of their take-home pay or profit. If the disproportionate escalations raise this to 6-7% managers will take heed to lower it, first by curtailing the demand then by modifying the distribution. Building leases that include utilities are being phased out in favor of submetered utilities where each tenant pays for what they use. In this way a tenant may also monitor their own energy management to ensure a minimal utility cost.

8.3.9 Minimal finance cost, CyFm

As a general principle, high-interest loans to finance the capital should be avoided. For a scenario to pay back in a reasonable time, interest on a loan must be less than the utility escalation rate. By the very nature of banking even first-mortgage interests cannot meet this criterion. Adding property taxes and realtor fees makes financing even more tenuous.

A government may create a form of subsidy for conservation construction through tax credits and deductions. This shifts the finance burden to all the taxpayers. Although this encourages the development of an associated industry it does not promote an economically viable market. It favors people

Criteria .for evaluating energy-conserving design 209

with higher taxable incomes rather than those who really need the lower utility cost.

Utilities are providing packaged services where they have installed the appropriate equipment and materials, and finance the capital with low- interest loans to be paid back as a charge on their utility bill. This is possible because the loan becomes a business expense with all the corporate tax advantages. Leasing would be a further step in reducing finance costs (Section 6.4).

8.3.10 Minimal life cycle cost, CvLm

In long-term planning an owner and economist may assess their liabilities over a period that they might consider as a life cycle. Government agencies in the USA have thought of 40 years as appropriate, but with present-day escalations and uncertain discounting even a decade can be tenuous. The measure is used as a resource in the benefit for resource ratio as a way for setting priorities. An economist would find a life cycle cost useful as part of a broader business or industrial strategy. The point is that the escalations in energy are greater than the monetary inflation, which means that a business overhead rises in cost at a disproportionate rate which tends to infringe on the profits.

8.3.11 Minimal payback period, TLa_bm

A payback period is a comparative measure between the life cycle costs of two scenarios, 'b' compared with ~a'. Frequently, the base case 'a' is a business-as-usual scenario using an existing or conventional solution. A payback period is the time for the two life cycle costs to equate (Section 3.2.10). Extra capital is played against savings in annual costs.

In design a favourable simple payback period is less than three years. which is roughly the period of a short-term unsecured loan. Payback should be less than half the period of a longer-term secured loan to recover the principal and pay the interest. Periods beyond ten years are hard to jus t i6 because of the changes in ownership and uncertain escalations. It must be less than a replacement period, for that starts a new cycle. Account costs shorten the payback while discounting extends it.

8.3.12 Maximal benefit for resource ratio, kBRba M

A benefit for resource ratio can set the priorities of scenarios by comparing one against the other. A comparison with a conventional case or base-case scenario must exceed unity to have more benefits for the resources expended.


Ratios over 1.1 would tend to be more significant in view of the variations outlined in Section 8.1. Time-zero costs compare the capital as a first priority. Decade costs compare the life cycle costs over ten years to weigh the benefits of reducing the utility bill. All of the parties are interested in finding the scenarios with the highest ratio so that they can be instigated as soon as possible.

Values less than unity can only be justified for contingencies such as emergencies, embargoes, strikes and equipment failure. Again, the higher the value, the higher the priority. In this situation there can be an immediate trade-off in performance knowing the risks involved in approaching the limits of health and safety.

8.3.13 Minimal budget, CTt m

A minimal budget first establishes the least capital costs for the best benefits for the least resources. Time-zero priorities do this. Next, the lower annual cost opportunities are established from the decade priorities. Not all scenarios are independent, and so the order has to be qualified according to the design constraints. For instance, insulation may be installed when the roof is repaired, access or downtime may only be possible during certain periods, there may be shipping delays, or waste heat recovery may be pre- empted by reducing the demand.

A target annual budget may be invested at the rate of the anticipated savings or the inflation rate times the annual utility cost. Thus profit from a preceding year becomes the seed capital for the following year.

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Criteria for Evaluating an Energy-conserving Design