MEASURED RESULTS OF ENERGY CONSERVATION RETROFITS IN NON-RESIDENTIALBUILDINGS: AN UPDATE OF THE BECA-CR DATA BASE*

Betsy L. Gardiner, Mary Ann Piette, and Jeffrey P. HarrisLawrence Berkeley Laboratory

ABSTRACT

Energy consumption data have been compiled for over 300 commercial build­ings that have been retrofitted with energy conservation measures@ This database has been updated and expanded since the 1982 Santa Cruz Summer Study; were-contacted the original contributors of data, updated energy usage andretrofit information, and removed data points with poor quality data& Newdata sources include schools and hospitals receiving Federal grants, Califor­nia public buildings, projects undertaken by architecture and engineeringfirms, and 100 buildings retrofitted under the U.S@ Postal Service Phase Iproject@

The distribution of energy savings is examined for the data set as a who~e

and for subsets by building typee For the 942

percent of bUildi~gs that savedsite energy, median savings are 30@8 kBtu/ft -year (350 MJ/m -year)@ Themedian percent reduction is 24@6 percent@ Cost-effectiveness indicators areevaluated for tho~e buildin2s with retrofit cost data@ The median retrofitcost is $@40/ft ($4e30/m) in 1983 dollarse The most common retrofit meas­ures involve HVAC operations and maintenance, and lighting@ In many casesenergy management in non-residential buildings is a continuing process withoutclear npreu and retrofit periods@ For buildings with a series ofretrofits and operating ,changes we explore simple time-trend analyses as analternative to a pre/post model@ We discuss problems of correcting energy

data for changes in weather, occupancy, process loads, and othergaps in the data base are identified, along with sug­

with them~

The work described in this report was funded by the Assistant Secretary forConservation and Renewable Energy, Office of Building Energy Research andDevelopment~ Building Systems Division of the DeS@ Department of Energy,under Contract No@ DE-AC03-76SF00098@

GARDINER ET AL e

MEASURED RESULTS OF ENERGY CONSERVATION RETROFITS IN NON-RESIDENTIALBUILDINGS: AN UPDATE OF THE BECA-CR DATA BASE

Betsy L@ Gardiner, Mary Ann Piette, and J'effrey P@ Harris1;,awrence Berk.eley LabQ.ratory

INTRODUCTION

Commercial buildings* use about one-eighth of the energy consumed in theU$S@ (DOE, 1981). According to the Department of Energy, UeS. commercial sec­tor energy use is expected to increase slightly faster than energy use by theeconomy as a whole (op@ cit.). This is due largely to a projected floorspaceincrease of 2@5 percent per year; annual growth in housing units, for com­parison, is about 1@5 percent. Despite this projected growth, about two­thirds of the commercial floorspace anticipated for the year 2000 is alreadyin place, and thus a prime target for energy efficiency improvements.

For large office buildings, the Building Owners and Managers Associationestimates that annual energy costs now represent nearly $1950 per square foot,or about 37 percent of all operating costs (median value for large officebuildings in the 1982 BOMA survey; BOMA, 1983)@ Energy costs, despite slower

rate increases recently than during the 1970's, remain a potentiallycontrollable expensee Reducing such costs is still among the top concerns ofcommercial building owners and managers@ Moreover, electricity demand forcommercial building air conditioning and lighting represents a large propor­tion of total system peak load for many utilities, and a major cause of expen­sive additions to generating capacity. For all these reasons, improvingenergy efficiency and reducing peak demand in existing commercial buildingsare objectives shared by policy makers, utility planners, and building ownersand operators.

Despite widespread interest, most estimates of energy management savingsand paybacks are based on engineering calculations, computer simulations, or"professional judgment@" A compilation of actual, measured data on commercialretrofit and cost-effectiveness is important as an empirical benchmarkfor these estimatese Measured data also provide a source of improved credi­bility, feedback on the accuracy of savings predictions, and a means of iden­

new issues that deserve more concentrated data collection andanalysis~

This paper presents the results of such a compilation (BECA-CR), one of aseries of data bases developed and maintained at Lawrence Berkeley Laboratoryas part of the "BECA" (Buildings Energy-Use Compilation and Analysis) project@We and analyze results of conservation projects in 311 commercialbuildings (or centrally-metered building complexes), almost all in the U.Se

'* We use the term "commercial" and "non-residential" interchangeably in thispaper to refer to all buildings, government- and privately-owned, used forpurposes other than residences or industrial activities@

GARDINER ET AL~

This study builds upon and updates earlier published reports (Ross and Whalen,1983; Wall and Flaherty, 1984)@

METHODOLOGY AND DATA SOURCES

Methodology

At a minimum, each building in the data base must include data on: build­ing size and type, metered energy usage before and after retrofit(s), andretrofit descriptions and implementation dates. In addition, we attempt toobtain more detailed information on building physical features, as well as anymajor changes in process loads, operating schedules and practices, or otherfactors that may have affected energy usee

The simplest analysis compares annual energy use by fuel type during pre­retrofit and post-retrofit periods@ Energy use intensity (annual kBtu pertotal square foot' of floorspace) is calculated for each fuel type, thentotaled in terms of both site energy and resource energy (i@ee, electricity at3,413 Btu/kWh and 11,500 Btu/kWh, respectivelY)e For buildings with more thantwelve months of energy data available in either the pre- or post-retrofitperiod, we average the multi-year data. Where data allow, we also look attrends over several post-retrofit years, as an indicator of energy savingspersistence~ Finally, where data are available by month (or billing period),we examine them to identify possible effects of weather, building usage, orother factors that vary seasonally@

The upre/postU retrofit analysis allows a straightforward economic com­parison: changes in energy use can be compared with dollars invested in con­servation@ However, in many commercial buildings the actual sequence ofenergy management activities does not fit readily into the pre/post framework@Both retrofit investments and changes in operating practices may continue--andoverlap one another--for· several years. Lacking a well-defined quantitativemethod for such continuous energy management efforts, for now we usesimple graphics to examine related time-series data, looking for consistent

Most of the with continuing conservation efforts can alsobe included in the pre/post analysisG This requires that we judg-

define the pre- and post-retrofit periods as those which bracket theof most intensive conservation activitYe

Retrofit cost data are available for a subsample of 179 buildings (58 per­cent)@ After these values to constant (1983) dollars using the U~S~

GNP deflator, we calculate two cost-effectiveness indicators: simple paybacktimes and cost per unit of (site or resource) energy saved (Meier, 1983)@Other economic indices can also be derived from the data (Goldman, 1983)$ Weuse payback time rather than the discounted payback or net presentvalue because: (1) simple payback is a familiar index to many building own­ers~ (2) projected rates of energy price increase are similar to the range ofdiscount rates in common use (thus the two factors tend to offset each other),and (3) since most payback periods are short, the refinement of usingdiscounted would have little impact@

GARDINER ET AL@

To calculate simple payback periods we use national-average energy pricesfor commercial customers, by fuel type (EIA, 1982 and 1984)e An alternativewould have been to calculate paybacks using local energy prices--either theaverage price for the utility area or region or a building-specific averageunit energy cost@ However, we know of no consistent data source on localenergy prices for the commercial sector~ Moreover, few buildings had billingdata sufficiently detailed to calculate unit energy costs accurately (i.e@,accounting for rate changes and customer shifts within or among complex ratestructures) 0 Finally, the short payback periods again suggest that refiningthe unit energy price estimates would make little difference in the overallresults@

In calculating the cost per unit of saved energy, we chose a real discountrate (ieee, above inflation) of 7 percent* and an average retrofit lifetime of10 years, representing the typical amortization of a commercial buildingretrofit@ These assumptions imply a capital recovery rate of 0@14/year@ Anumber of reasonable alternative assumptions could be used, but they would notchange the relative ranking of project cost-effectiveness@ One refinementwould change relative rankings: the use of lifetimes specific to each type ofretrofite However, there are almost no empirical data on actual conservationmeasure lifetimes, as might be expected given the general absence, to date, ofmulti-year tracking of retrofit results@

Most sources for the data in the initial Ross and Whalen compilation werere-contacted in order to verify and update information on energy use, buildingfeatures and ion, and retrofitsG Of the 223 buildings in the originalcompilation, 163 have remained in the data base@ Buildings were deleted forreasons of data quality, such as missing energy consumption data, or ambiguousretrofit or dates@ In a few cases, anticipated retrofit projectswere never implementede A separate working paper contains the detailed BECA­CR data tables, as well as a narrative summary of each data point and an

of reasons for each deletion (Gardiner et al@, 1984)@

new sources of data include schools and thatreceived federal under the Institutional Conservationoffices retrofitted under the U@S@ Postal Service Phase 1 Energy Management

, California state and local government , and retrofit entriesin the ASHRAE of Heating, and Air-

) awards

* This discount rate is based on for energy managementects in Federal buildings (Ruegg, 1980)* It is higher than the long-term

discount rate," about 2-3 percent real, that arguably might be used tocalculate the value of saved energy to society as a whole@ Conversely, the

discount for commercial sector investments in conservation ison the order of 20-50 , based on typical payback periodsQ

GARDINER ET AL ~

Confidence Levels

All buildings are assigned a data confidence level (A, B, or C) for eachof three data categories: building characteristics, retrofit data, and energydatao Data Table A, in the BECA-CR working paper, shows confidence levels forindividual buildings; the notes accompanying that Table define the rating cri­teria.

Fewer than one.....fourth of the buildings have nAu or HB" levels' in all threedata groups; none of the buildings have an nAu in all three categories. Futureupdates of the data base will analyze separately a subsample of buildings withhigher-quality datas

Changes from Previous BECA-CR Compilations

Beyond the additions, deletions, and revisions noted above, we are makinga special effort to obtain monthly and multi-year energy billing records touse in time-trend analyses, and to collect data on winter and summer peakelectrical demand. We currently have pre- and post-retrofit peak demand datafor about 20 buildings@ For many buildings we have obtained additional yearsof data for both pre- and post-retrofit periods@ Finally, the multiplier usedto convert site electricity to resource energy is now 11~500 Btu/kWh ratherthan the 10,234 Btu/kWh used previouslyB This revised factor accounts fortypical utility system transmission and distribution losses, in addition topowerplant efficiency. For all these reasons, the values now shown in thedata tables and plots may not match those reported previously for the samebuildings (new or revised entries are noted in the data tables)@

Building Characteristics

Buildings in the BECA-CR data base~ although not deliberately chosen torepresent the U@S~ commercial stock, are quite diverse in terms of occupancy

, size~ and location@ Tables I and II summarize building characteristicsof the BECA-CR sample and the total stock as of 1979 (the most recent pub­lished data)~ Details are presented in Data Table A of the working paper@

Schools, offices, and post office buildings are all heavily represented@Of 311 buildings in the data base 134 are schools; two-thirds of these areelementary schools@ School retrofit data may be more readily available as aconsequence of numerous audit programs and the Federal Institutional Conserva­tion grants$ Retail stores and hotels/motels are still poorly represented inthe data base, even though significant energy management efforts have occurredin these subsectors$ Adding more examples of these and other privately-owned

will close collaboration with industry associations andindividual firms$

Table II shows that the data base significantly overrepresents largebuildings, compared with the total stock. This is probably due to two fac .....tors: (1) retrofits are more likely to be installed in larger buildings, and(2) large-scale buildings, public or private, are more likely to have a pro­fessional facility manager or other individual to track energy performance andrecord data suitable for BECA~

GARDINER ET AL 0

Table 10 Distribution of buildings by type.

BECA-CR DATA BASE u.s .. COMMERCIAL STOCK (1979 NBECS)

Building Type Percent by Percent by Total, of Buildings Floor Area

Schools 43.1 22413Elementary 28.6 7.3Secondary 10.0 6.3Colleges 4.5 8",7

Offices 15~4 13.5Large 11.3 13.3Small 4.2 002

Hospitals 1.9 2.2

Retail 0.6 0&01

Hotels 1.6 1.9

Other 38.9 61.9Post Offices 29.9 36.1Correctional 1.6 6.0Assembly 006 001Restaurants & Grocery ·OeJO 0.0All other 611>8 19.7

Table II~ Distribution of buildings by size.

Percent by, of Buildings

4.0

17.9

Percent by TotalFloor Ares.

1203

BECA-CR DATA BASE U.S. COMMERCIAL STOCK (1979 NBECS)

Floor Area Percent by Percent by Total Percent by Percent by Total(1000 sqefte) # of Buildings Floor Area , of Buildings Floor Area

> 100 63,,7 93 .. 1 1 .. 6 33 .. 2

> 50 < 100 1900 5.1 2.5 15.1> 25 :i 50 1006 1.5 502 15 .. 0> 10 ~ 25 308 002 13 .. 8 1609> 5 < 10 2.3 0.1 18.6 10.5> 1 ~ 5 0 .. 6 4L~9 8.6

~ 1 0 0 16.4 0.7

Table III. Retrofits implemented&*

CATEGORY OF RETROFIT NUMBER OF PERCENT OFBUILDINGS BUILDINGS

Operations and Maintenance 198 64

HVAC System 137 44Cooling 60 19Ventilation 88 28Control Systems 117 38

Lighting 120 39

Shell Envelope 47 15Insulation 29 9CaUlk/Weatherstrip 26 8

Windows and Doors 37 12

Water Heating 30 10

Other 49 16Heat Recovery 3 Oe9Load Management 9 2Gt9

* Totals may not add since, in many buildings, morethan one measure was installede

GARDINER ET AL @

All areas of the continental United States are represented in the database (46 states have at least one occurrence) but the sample is weightedheavily toward Eastern states@ About 10 percent of the BECA-CR buildings areall-electric, compared with 19 percent of all UeS@ commercial buildings (and25 percent of all offices)@

The averag~ pre-retrofit site energy intensity for BECA-CR ,buildings is149~4 kBtu/ft -year@ Hospitals had the highest average energy intensity(396@3 kBtu); retail buildings the lowest (64~5 kBtu)@ This ranking is gen­erally consistent with results of the 1979 Non-Residential Buildings EnergyConsumption Survey (NBECS): hospitals were in the high range of average energyintensities (262 kBtu) while retail buildings were among the lowest (82 kBtu;EIA 1983)@

Types of Retrofits

Retrofit measures included changes in the HVAC (heating/ventilation/air­conditioning) system, building envelope, lighting system, windows and doors,and domestic water heating equipmente Many of the buildings had severalretrofit measures implemented@ Table III summarizes the implementation fre­quencies for each or category of measures@ Notes to Data Table A in theworking paper describe our scheme for classifying measures@

HVAC and maintenance measures were the most common (64of the ), but this general category encompasses a

number of measures, from simple actions like changing ther-mostat setbacks to diagnosis and adjustment of boilers,ers, fans, and distribution ducts@ Lighting measures were popular (39 per~

cent); included delamping, with more effi-cient bulbs and addition of controls@ Economizer

and other modifications were also common (20 per-cent)@ This is not since most commercial signi-ficant amounts of , even in mild climates~

RESULTS

IV summarizes energy results by building type (Data Table Apaper contains data for individual buildings)@

site energy savings per square foot is shown inand fuel use for both the pre- and post­

(94 percent) reduced their total siteIn of resource energy, 241 of 267 (90 percent) achieved a net

the buildings that saved energy~ average percent(site) and 24@2 percent (resource)@ For individual

* Unless otherwise indicated, average values are always (i@e0, allare , rather than weighted by floorspace or energy

Us€@

GARDINER ET AI. "

Table IV iii Summary of energy savings. from retrofits, for commercial buildingswhich reduced energy usee

<--------- SITE ENERGY SAVINGS ------> <------ RESOURCE ENERGY SAVINGS ------------>

<Percent Savings > < Energy Savings > < Percent Savings > < Energy SaVings >( kBtu/ft 2_yrlil ) ( kBtu/ft 2-yr.)

Building Type N average median average median N average median average median

SchoolsElementary 82 27410 27.7 33.0 30.4 78 25.0 24.6 38&4 35&0Secondary 28 27.,4 2405 34.5 37.7 28 25.9 2406 5104 4766Colleges 13 4104 44(15 166416 100417 12 371110 40.0 228.4 14404

OfficesLarge 34 24.4 2L.4 43.4 28,,5 22 1902 1309 8208 43400Small 13 2805 20,,8 5206 32<06 12 2507 18.4 96.8 41.0

Hospitals 6 2607 2604 113.8 93&4 6 19,d 1603 130.2 101.9

Retail 2 12 .. 3 12413 8,.0 8.0 2 17410 17.0 2L~3 2103

Hotels 20.3 1404 51417 4203 5 1605 12.1 76403 60@9

OtherPost Offices 92 25&0 2400 3102 2800 60 2109 2L.5 77 .. 4 67&4Assembly 2 52.2 52&2 18806 188.6 1 47,,5 47.5 348,,9 348,,9Correctional 1 600 6.0 8e5 8 .. 5 1 L~8 le8 3eO 3/ll0Other 14 27 .. 9 23e6 7208 2306 14 27.6 2204 107.5 4208

TOTAL 292 26$7 2406 45e3 30918 241 24412 22.7 74 .. 1 47.1

* All averages are unweighted ll ieee, each building"s savings areweighted equally regardless of floorspa~e or energy usage41

Figure 19 Site energy saVings (frequency d1stribution)~ For those buildingsthat saved ~1te energy the average change in energy 1n~ensity was45~3 kBtu/ft -yr and the median change was 30~8 kBtu/ft -yr@ Theaverage percent reduction was 26~7t the median percent change24~6* Nineteen of the buildings used more energy after retrofitthan before~ either due to "fa11edu measures or to factors otherthan the retrofits~

GARDINER ET AL §

buildings, the difference between resource and site energy savings can be sub­stantial, but the shape of the overall distribution in Figure 1 is similarwhen plotted in resource energy units9

As a group, colleges achieved larger-than-average savings (both percentand absolute), but this was primarily due to very large reported savings forseveral of the Ohio State University buildings (which also had higher thanaverage pre-retrofit energy intensities)& Other building types (those withmore than a handful of data points) all had percentage reductions similar tothe average for the entire sample&

Figure 2 shows a scatterplot of percent site energy savings vS 9 pre­retrofit energy intensity9 One might expect more energy-intensive buildingsto achieve larger proportional savings, but there is no clear correlation$Both large and small users achieve a wide range of percentage savings-­clustered between 10 and 40 percent~ Looking separately at each building typedoes not noticeably reduce the scatter$

Retrofits with Increased Energy Use

For some buildings in the data base energy consumption actually increasedin the period~ Total site energy use increased for 19 build-

; resource energy totals were higher in 26 casese Energy increases rangedfrom less than one percent to about 40 percent9 There were no significantdifferences by building type in the fraction of buildin~s with increasedpost-retrofit usage$

In many cases, we do not know the exact reasons for increased energy con­sumption@ Possible explanations include the improper initial choice of meas­ures, poor quality products or installation, and in building occu-pancy, or weather conditions9 Without more detailed data, it maybe wrong assume that every building with increased post-retrofit usage

a trofit converselyj that the retrofit alone wasfor the total energy use reduction in usuccessful" buildings0

In some cases,on-site

individual building records or consult withreasons for net energy increases@ For

, in one case energy consumption increased 19 percent@ We found outthat the control had been installed improperly at first, but the prob­lem has since been corrected and a net decrease in consumption is now antici-

We will continue the building@

In Conditions

Weather@ An earlier report on the BECA-CR data base (Ross and Whalen,198 , points out that at there is no widely-acceptedmethod for weather-normalizing commercial building energy performance $ The

is even more difficult when only whole-building consumption is avail­able, rather than submetered heating and cooling$ Weather-normalization tech­

developed for single-family residences (Fels et a1$' 1982) may beto some small commercial buildings9 In general, though, commercial

GARDINER ET ALe

100 200 300 400 600

PrewRetrofit Energy Intensity (Site kBTU/ft2~yr)

100

90

80

........-.......c.: 10CDe~ eomCDCoS;

60co(f)

>C)

40.....CDJjG)

30......en20

10

00

• Offices

0 Schools

II Post Offices

0 Retail

I). Hospitals

<> Other

•0 0

0 <><>

Nsm: 292

0 637.8

81&.3621.0

844.4

600.4

.. I) 527.0

<> 0 703.3

II<>

6 ~

IIIJ. 637.1

0<>

CD

6. <>

Figure 2~

xeo 806..13076

Percent site energy savings VS~ site energy intensity (kBtu/ft 2­yr)0 There does not appear to be any correlation between thepre-retrofit energy intensity and the percentage savings realized0Both high and low energy users achieved a wide range of percentagesavings 0

Table V" Summary of retrofit costs and cost-effectiveness~

Retrofit Cost: Simple Payback. Cost of Conserved Energy ($!MBtu; eRR 3li 0 .. 11.)~~~~~~~~~--~-~-----~~ ~~~-~~--~~-~-~-----~- ~~-~~~~~--~~-~--~----~---~~-~------~------~-

Building Type (1983 S!sqeft,,) (years) (---- Site ----) (--- Resource ---)N Average Median N Average Media.n N Average Median Avera.ge Median

SchoolsElementary 25 1 .. 09 .,88 21 5103 2,,3 24 11 .. 2 2.. 8 4,,5 2 .. 7Secondary 10 2 .. 73 ,,22 10 1 .. 1 .. 8 9 1.. 7 1.. 3 1..1 ,,8Colleges 10 1 .. 60 1,,12 8 .. 8 .. 6 9 .. 9 .. 8 .. 6 .. 5

Offices22 .. 73 ,,31 19 1.. 8 1.. 3 21 3.,7 2.. 4 1..4 1.. 05 3.. 26 2 .. 68 4 3.. 4 1.. 4 5 13.,2 6 .. 7 2.. 8 1,,2

Hospitals 1 .. 13 1.. 06 2,,9 2 .. 6 3 .. 1 2.. 6 2 .. 2 2 .. 0

Retail .. 02 .. 02 2 .. 2 .. 2 2 .. 7 .. 7 .. 2 .. 2

Hotels .. 41 .. 47 .. 5 .. 5 .. 6 ,,6 04 .. 4

OtherPost Offices 93 .. 42 .. 29 59 1107 $9 92 5~O 1 .. 5 L,4 .. 7Assembly 2 4.. 12 4 .. 12 1 408 .. 8 2 5 .. 1 5,,1 .. 6 .. 6Correctional 0Other 4 .. 59 .. 68 4 ,,9 .. 4 4 1..3 .. 6 .. 8 .. 3

TOTAL 119 .. 75 .,40 134 2402 .. 9 174 5 .. 3 1,,6 1.. 9 .. 9

0-39

GARDINER ET AL 0

buildings respond to weather quite differently than single-family residences,due to their larger internal loads, year-round requirements for cooling, zonalvariations in load (often requiring reheat), and mechanical fresh-air ventila­tion systemse

Commercial building weather response also depends on physical features,operating practices, and occupancy type$ A series of parametric buildingsimulations were prepared for the ASHRAE/DOE "Standard 90" update project,using the DOE-201B computer program (Battelle PNL, 1983)& Comparing five U$S@climate zones, variations in overall building energy intensity were 9 to 35percent (depending on the HVAC type) for small offices and 15 to 20 percentfor large offices. Other building types showed even more climate variation:35 to 77 percent for schools and 73 to 128 percent for warehouses@ Of course,these whole-building numbers tend to understate climate influences, sinceheating and cooling changes often partially offset each other$

For BECA-CR our principle concern is comparing the same building beforeand after retrofit@ Thus, we need to account for the (less extreme) weathervariations within a climate zone rather than variations across climates, butthe normalization problem remains $ Until an appropriate quantitative tech­nique is developed and validated, we can only look for general indicators thatweather changes may have significantly affected building energy use@ An exam-

is offered in the later section on time-trend analysis$

increasesabout the

Occupancy and Loads $ Changes in building occupancy and processloads can also energy consumption$ We try to collect detailed pre- and

information on the number of occupants, occupied (or operating)hours, and process load types and intensities0 Detailed data are currentlyavailable for a few buildings, but can sometimes help to explain

(or conversely, to raisereduced energy use)$

Economic of Retrofits-------

viceable;;;,

Retrofit Cost(58 percent ~

with a mediancosts acrosscost data@

Retrofit cost data are available for 179 of theper square foot of ranged from $0$01 to $8636,

@40 (1983 $)@ Table V shows the variation in retrofitIt is difficult to obtain consistent retrofit

keep complete records of all costs ofa those involving modest outlays or use of

in-house personnel$ Also, retrofit projects are sometimes accompanied byeven though the existing equipment may still be ser­

one should consider only the added cost of energy­features of the new equipment; in practice these numbers are seldom

available~ In some cases, there are changes in the cost of periodic mainte­nance, , and other non-energy operating expenses associated with theretrofit measure, but consistent multi-year records are rare@ A possiblerefinement to BECA-CR would be to include an alternative cost-effectivenesscalculation i'standard factors instead of reported costs@

0-40

GARDINER ET AL e

60

O-&mIllilllllllllJl~~~~~IIIIilIIIAi6I~~"~~~~~~~~~~

L"\ V"'}, '1....::> :,/A, A,/'J 'J/\()

PAYBACK PERIOD [YEARS]

(f) (/)<.:) 60 e.."Z Z0 0 40 N = 147--' N = 133 -I

::::> =>CD CD

La.... 40 lL.0 0a::: 0:::W Wm m 20~ ~:J 20 :JZ Z

&.12

2.1&oo

Nm 134

V1sun 4. Cost of saved en.f'y Unquency dhcr:ibuUon). That cost of Illlaved(iUUll'SY \lU calculaUd udn, a Capita! Rec:oYQry bu (CJU\) of 0 .. 14C1nuu.t nte 7 percal'lt, amortiut1on 10 yellllu).. The IiI:ltdhnvalue 13 $O.90/Katu, \lieU below the coet of purchased fu~l orehctddty ..

<>

<>

@ Offices

a School.

e Post Officee

o Retail

A Hospitals

<> Other

300

@ II200 I#iI 2.ee

@ I@

&I~

m0

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Om0

100 [). BD 0 !J.

* 0A

II 000 II 41»

8 2.82o Ii IJl! 6.61

II

0

0.25 0.50 0.76 1 1.25 1.60 1.76 2

Retrofit Cost (1983 S/ft2)

:KeG 806...13074

400

i'18ulfo 3. Simp!@ payback 1Ktt'1od (frequency dhtrlbuUon). PayblJcka W'l1Ilr~

c8!cultllllt@d u81nl 1983 national average fuel prius. Roughly one­half of too r~uroUtted building. hlld paybacks of lelai thon oney~UU'; over 80 ~fcent had pa)'back p.erloda under thru yeau.

Figure S{9 Energy savings VS~ retrofit cost (normalized to building floorarea)~ A range of energy ~av1ngB 1s achieved for each level ofinvestmente SaVings do not appear to be positively correlatedwith the level of retrofit 1nvestmentQ Thus, cost-effectivenessis lower

2for most buildin2s with retrofit costs greater than about

$OQ75/ft ~

0-41

GARDINER ET AL@

Simple Payback. Figure 3 shows the distribution of simple paybackperiods, calculated using DoSe average fuel prices for 1983. For about halfthe projects, payback periods were under one year; all but a few had paybacksshorter than three years. This pattern of relatively short paybacks,unchanged from the earlier BECA-CR compilation, implies that few building own­ers are investing in the full range of measures that would be cost-effectiveon a life-cycle basis. Uncertainties about actual savings probably plays arole in limiting investments to short-payback items--as do questions aboutfuture energy prices, limitations on capital and technical resources, andoperational constraintso

Cost of Saved EnergYe The cost per unit of energy saved (1983dollars/MBtu) was computed for both site and resource energy, using theassumptions noted earlier (7 percent real discount rate, la-year average life­time of retrofit measures). Figure 4 shows the resultant distribution ofcosts per unit of resource energy; the distribution for site energy (notshown) has a similar shape.

Figure 5 presents another perspective on the retrofit energy and costdata, comparing resource energy savings with the level of retrofit investment(both normalized for building floor area)$ One might expect to see a patternof steadily increasing energy savings with increased expenditures on retro­fits@ In fact, other influences apparently mask any such pattern, whether oneexamines all buildings together or each building type separately.

Examining Time-Trends

severalfiles,

As discussed above, there are limitations in using annual consumption datafor a "pre/post U analysis of retrofitted commercial buildings@ In many cases,energy management activities and retrofit measures are implemented almost con­tinuously over a period of years~ Moreover, weather, occupancy, processloads, operating schedules, and other factors affecting energy use may change,

the ion of t savings. u Tracking buildings forafter retrofits, and examining monthly energy pro­added into effects of retrofits on build­6a,b,c show examples of simplified graphic analyses

the conventional "pre-post" assessment&

6a shows five years of annual energy consumption data for a 49,000school in Pennsylvania (ID #99 in the Data Tables)$

1977 and 1978, ,000 was spent on installing efficient replacementboilers and adjus the ventilation system to reduce outside air~ To our

no additional conservation measures were implemented after 1978~

t the 1975 data as a pre-retrofit base year, and 1980 - 83 as fourt-retrofi data. All four years show a reduction in site energy

use, 36 percent below 1975. However, there is considerable varia-tion in energy use these post-retrofit years@

A teachers# strike which lasted from October, 1980 to February, 1981 prob­contributed to the reduced oil consumption during 1981@ Heating degree­

days (base 65° F) were higher for the years 1980-82 than for 1975, so mild

GARDINER ET AL3

6000 Yr HDDq COD.,Occ..

5n2 fZZ1 ElEC 75 4594 1252

~ 5000 _Oil 80 4815 1133 510....... 81 5171 1447 510CD

82 5256 1038 466:'2CD 83 491..... 4000gc:0=a 3000E:JMc:0

U 2000>..~CD

as 1000

0

Figure 6a@ Persistence of energy sav1ngs& One year of upre-rfu:rof1tn base....line energy data (1975) and four years of "post-retrofit" data areshown for a 1977-78 boiler replacement and ventilation systemretrofit in a Pennsylvania elementary school& The variation inpost-retrofit consumption raises questions about .attributing allthe decrease in energy consumption to the retrofit8~

200000

'3...,~ 160000

CD"*""!!i

100000

EMCS inltaUation (S86Id; zone cooling ,etrofit C3n9. S27ldWill insulltion (7/19. 58.Gld

Ughting modificAtions.water helting using steam condensate

Outside air to kitchen venta (S16td

CSSJ CHILLeD WATERm STEAMf2J fLEe

1Years

Figure 6b~ Multiple retrofits. This 485,000 square-foot Kentucky hospitalwas retrofitted with a number of measures over the last fiveyear8. Both steam and chilled water consumption decrea8ed~

IlIlIilliu although overlapping retrofit periods make it difficult to

separate effects of individual measures@ In addition to the pro-. jects DeteCt about $50,000 was spent on a number of smaller retro­

fit measures during the same period~

D-43

GARDINER ET AL &

b. Electricity

I•I

8am

Chiilleid water

o

600

1000

14000

~

::J 12000....

CD 10000+milen~

c 80000G+:i~

E:J 60000c:0

>4000

C)a..CDc: 2000w

02000

U)

>co

1500

o

Figure 6c~ Monthly consumption profiles@ Three years of monthly energy con­sumption and weather data are shown for the same hospitaldescribed in Figure 6b~ Although the building is large~ with sub­stantial internal loads~ there are clear seasonal variations inchilled water and steam consumption0 Despite higher coolingdegree-days (base 6So F)t chilled water usage was lower followingcooling system retrofits in early 1979~

GARDINER ET AL @

weather was not a factore However, some of the variation during the "post"period could have been influenced by the weather; HDD's were higher in 1982than in 1980, as was oil use (1981 is complicated by the teachers' strike;weather data are not yet available for 1983).

No occupancy data are available for the pre-retrofit period, but classroomoccupancy varied less than ten percent during the four post-retrofit years.*The school is not air-conditioned, so the gradual increase in electricity usemay be due to additional equipment, longer hours, or less careful operatingpractices.

The above factors suggest reasons for some of the variance, except for thejump in 1982 energy usee Oil savings appear to be persisting, but there isenough variation in the .annual data that it would be useful to examine addi­tional pre-retrofit years and to review monthly trends during the years shown(neither was available to us)@

A more detailed but also more complicated example is shown in Figures 6band 6co The data are from a large (485,000 square-foot) hospital in Kentucky(ID #249)@ Numerous retrofits were implemented during the 1978-1982 periodeThe timing of several of the most significant measures is noted on Figure 6b@Figure 6c shows monthly energy consumption by fuel type, along with heatingand cooling degree days (base 65° F) for three years@

The largest single project was the 1979-80 installation of computerizedcontrols for the HVAC system@ Steam usage dropped in 1981, although the totalreduction was less than projectede Chilled water use declined from 1979 to1980, and again in 1981, possibly in response to the HVAC control system andthe changes in cooling system zoning (the latter was also completed in time tocontribute to the even larger drop in chilled water use between 1978 and1979)@ Annual electricity use remained essentially constant throughout theperiod, even though $40,000 was spent on lighting retrofits. Hospitals oftenadd new equipment, which might explain why no electricity savings are

The lighting measures may have contributed to reduced chilled wateruse, as may other measures such as reduced ventilation rates@

at the monthly fuel type we see a very clear seasonalresponse for both heating and energy, despite the fact that this is arelatively large building with substantial internal loads@ Chilled waterusage the summer and drops to almost zero in the winter; steamconsumption is significant higher in the wintere Of the three energy types,chilled water consumption dropped the most during these three yearse The1978-79 reduction may have been due to milder summer weather, as indicated inFigure 6c, but between 1979 and 1980 cooling degree-days increased, so thecontinued decline in chilled water use may be the result of HVAC system zoningmodifications completed in March, 1979 (pumps, pipes, and cooling coils weremodified to meet requirements for lower-temperature air in Surgery withoutover-cooling the rest of the building)@

* Occupancy was lowest in 1982, which had the highest consumption of the fourpost-retrofit years~ In a school, lower occupancy may increase heating energyuse due to reduced occupant gains--assuming the same daily schedule and no de­crease in the number of classrooms used~

GARDINER ET ALe

Additional data on peak electricity demand, occupancy, and equipmentchanges would improve the evaluation of energy management in facilities suchas this, where a series of efforts extend over several years.

CONCLUSION: AREAS OF FUTURE EMPHASIS

Data presented above provide further evidence of trends in energy savingsand cost-effectiveness of commercial building retrofits, but no radical shiftsin the findings reported earlier (Ross and Whalen, 1982). We continue toobserve modest levels of retrofit investment--typically less than one-half theannual cost of purchased energy--and correspondingly short paybacks--in halfthe cases less than one year and almost always shorter than three years9 Onthe one hand, this means that conservation investments are very cost-effectivefor most of the buildings in our sample@ On the other, it suggests that inmany buildings only a fraction of the full cost-effective potential for energysavings is attemptede Even after retrofit, many buildings in the sampleremain well above the stock-wide average energy intensity for that buildingtypee

We still find considerable scatter in the data for both energy performanceand cost-effectivenesse This scatter is difficult to account for with themodest level of detail available for most of the buildings~ More detaileddata on end-uses of energy~ changes in building operation, weather-response,and other factors are needed to better understand why some buildings save morethan expected and others lesse However, detailed, instrumented monitoring ofcommercial building retrofits will continue to be the exception rather thanthe rule@ New, low-cost alternatives to continuous on-site monitoring need tobe developed@ One example is the creative use of in-place energy managementsystems for monitoring and reporting selected aspects of building performance@

For future data compilation efforts improved data quality will be moreimportant than simply increasing the number of data points@ Still~ there aresubstantive gaps to be filled, including results from energy management inretail stores, hotels/motels, and smaller buildings in general@ Also impor-tant is the continued of buildings over a multi-year period, to seewhat occur and what continuing costs are incurred@

The BECA data compilation project is a continuing effort; we solicitreaders# comments, suggestions, and leads to additional sources of data.

ACKNOWLEDGEMENTS

The authors acknowledge the assistance of the many people whothe actual building data for this study, and those who provided us

with leads to new data sourcese We also acknowledge Howard Ross, Sue Whalen,and John Flaherty who began the data collection in 1981 and produced the ini­tial analysis@ Special thanks to Nick Armstrong, John Flambard, ValerieKelly, and Virginia Magnus for their help with graphics development and dataprocessing9 Last, we owe a great deal to Jeana Traynor for her help in word

and productionG

0....46

GARDINER ET ALe

REFERENCES

Battelle Pacific Northwest Laboratory (PNL), Recommendations for Energy Con­servation Standards and Guidelines for New Commercial Buildings, Volume III:Description of the Testing Process, Report # DOE/NBB-0051/6, October 1983.

W.M. Bowen et al., Climate Selection and Development of Climate Indicators,Battelle Pacific Northwest Laboratory, Report # PNL-4435, UC-95d, September1982.

Building Owners and Managers Association (BOMA) , 1983 Experience ExchangeReport, Washington, D@C., 1983.

Energy Information Administration (EIA), U.S. Department of Energy, MonthlyEnergy Review, December 1983 [i], Report #DOE/EIA-0035(83/12(4]), publishedMarch 1984@

Energy Information Administration (EIA) , U@S. Department of Energy, Non­residential Buildings Energy Consumption ?urvey (NBECS): 1979 Consumption andExpenditures, Part 2: Steam, Fuel Oil, LPG, and All Fuels, Report # DOE/EIA­0318(79)/2~ December 1983.

Energy Information Administration (EIA), U@S. Department of Energy, StateEnergy Price System, Volume 1: Overview and Technical Documentation, Report #DOE!NBB-0029, November 1982.

M. Fels, et al~,

Tables, Princeton U.,PU/CEES-131, June 1982@

ModularCenter

Retrofit .!xperiment: Summar~ ScorekeepingEnergy and Environmental Studies, Report #

B. Gardiner, M.A@ Piette, and Je Harris, Technical Documentation for theBECA-CR Data Base ~ Retrofitted Commercial Buildings; Data Tables,-nefini=tions, and Summarr Descriptionse BED Working Paper # BED-WP-84-02, BuildingsEnergy Data Group, Building 90-H, Lawrence Berkeley Laboratory, Berkeley, Cal­ifornia, July 1984@

Technical Performance and Cost-Effectiveness of Conservation-- ---- -------___~ U.E... Residential Buildings: Analysis of the BECA-l! Data, LBL Report #LBL-17088, October 19839

A. Meier, The Cost of Conserved Energy as an Investment Statistic~ in HarvardBusiness Review, 61--(1), pp$ 36-7, January-February 1983@

H$ Ross and S$ Whalen, Building Energy Use Compilation and Analysis (BECA)Conservation Progress in Retrofitted Commercial Buildings, published

___~~ and Buildings, (5), 1983, 171-196@

R@T@ Ruegg, Life-Cycle Costing Manual for the Federal Energy Management Pro­grams, NBS Handbook 135, prepared by the Building Economics and RegulatoryTechnical Division, Center for Building Technology, National Bureau of Stan­dards, Washington D@C., December 1980@

0-41

GARDINER ET ALa

U@Sc Department of Energy (DOE), Office of Policy, Planning and Analysis,Energy Projections to the Year 2000, Report # DOE/PE-0029, July 1981.

L@W@ Wall and J@ Flaherty, A Summary Review of Building Energy Use Compilationand Analysis (BECA) Part C: Conservation Progress in Retrofitted CommercialBuildings, in J@ Harris and Ce Blumstein (eds.), What Works? DocumentingEnergy Conservation in Buildings, based on proceedings of the 1982 SummerStudy on Energy-Efficient Buildings, American Council for an Energy-EfficientEconomy (ACEEE), 1984@ This paper summarizes the previous work of Ross andWhalene