Applying computer-based simulation to energy auditing-A case study

Applying computer-based simulation to energy auditing-A case study

/locate/enbuild

Applyingcomputer-basedsimulationto

energyauditing:Acasestudy

YiminZhu*

DepartmentofConstructionManagement,CollegeofEngineeringandComputing,EngineeringCentre,FloridaInternationalUniversity,Miami,EC2956,10555W.FlaglerStreet,Miami,FL33174,USA

Received15March2005;receivedinrevisedform20July2005;accepted29July2005

Abstract

Throughacasestudy,thisresearchexploresanapproach,whichusescomputersimulationtechnology,toevaluatedifferentenergyconservationalternativesandtoassistfacilitymanagerstoselectreliableandfeasiblesolutions.ThesubjectfacilityislocatedintheSoutheastregionoftheUnitedStates.OneofthemajorchallengesandoperationgoalsoftheGeneralServicesAdministration,whomanagesthefacility,isforthatfacilitytoachievetheEnergyStardesignation.However,duetothecomplexityofthefacility,therequirementsfrombuildingoccupants,aswellasotherdif culties, ndingapathforoptimizingtheoperationofthefacilityinordertoachievetheEnergyStardesignationisnotalwayseasy.ThisprojectuseseQuest,asimulationsoftwaretool,tocreatea‘‘virtualenvironment’’,inwhichtheoperationsoftheHVAC(heatingventilationair-conditioning)systemandthelightingofthefacilityarestudied.Subsequently,recommendationsinitiallymadebyexpertsthroughtraditionalenergyauditapproachesareevaluatedinthe‘‘virtualenvironment’’inordertodeterminethebestsolutiontoachievethegoalofthefacilitymanagers.Thispaperdiscussesmajoraspectsoftheproject,includingthechallenges,thevaluesandthelimitationsofapplyingcomputersimulationtechniquesinsuchafacilitywithcomplicatedstructural,occupancyandoperationfeatures.#2005ElsevierB.V.Allrightsreserved.

Keywords:Energyef ciency;Computer-basedsimulation;Energyaudit

1.Background

Energyconsumptionofbuildingsisaresearchtopicthatretainsalotofresearchattention[e.g.,1–5],sincemanystudiessuggestthatenergyconsumptionisoneofthemajortypesofcostthroughoutthelifecycleofabuilding.Inaddition,duetotherisingcostofenergy,lookingforef cientwaysofbuildingoperationsuchasloadmanagement[6]orrenewableenergy[7]becomesmoreandmoreimportantforfacilitymanagers,whooftenrequireatoolthatcanassistthemfordecision-makingregardingvariousalternativesofaretro ttingprojectorthealterationofanexistingfacility.

Facilitymanagers,nowadays,facemanytechnicalchal-lenges,includingidentifyingproblematicareasinafacility,isolatingdifferenttypesofproblems,prioritizingtheimpactofthoseproblems,developingsolutionsandimplementingselectedsolutions,aswellaspsychologicalchallenges,i.e.,toacceptrisksassociatedwiththeselectedsolution.Oncean

*Tel.:+13053483517;fax:+13053486255.E-mailaddress:zhuy@ u.edu.

0378-7788/$–seefrontmatter#2005ElsevierB.V.Allrightsreserved.doi:10.1016/j.enbuild.2005.07.007

energysavingplanisdecidedandexecuted,theprocessisdif culttoreverse.Inaddition,manyenergy-auditingstudiesareoftenconstrainedbybudgetandtime,yetexpectationsfromtheresultsofthosestudiesareusuallyhigh.Allthosefactorsputafacilitymanagerinaveryriskypositionatthetimeofmakingdecisionsinordertoensurethat,theselectedenergyconservationplanwilldeliverwhateveritpromises.

Ingeneral,energyauditinghasbeenaneffectivetoolthatcanassistfacilitymanagerstodeveloptheirenergysavingplansandtoachievetheirenergysavinggoals[e.g.,4,8–12].However,manyexistingenergyauditingapproachesmayoverlooktheintricaterelationshipsbetweendifferentfactorsthatwillaffecttheenergyconsumptionofalargefacility[e.g.,10,13],andthecross-effectthattwoormoredifferentsolutionsmayresultin.Therefore,amoreeffectivevalidationtoolisneededto ne-tunetheresultsfromanenergyauditingprocess.

Computer-basedsimulationisacceptedbymanystudiesasatoolforevaluatingbuildingenergy[e.g.,14,15].Therearemanydifferenttypesofcomputer-basedsimulationtoolsthatareavailableforperformingwhole-buildingsimulation,e.g.,theapplicationofDOE2[10,16]andanexpertsystemfor

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422Y.Zhu/EnergyandBuildings38(2006)421–428

supportingenergyauditing[17].eQuest,,is‘‘asophisticated,yeteasytouse,freewarebuildingenergyuseanalysistoolwhichprovidesprofessional-levelresultswithanaffordablelevelofeffort’’().ThisisthereasonthatthisstudychoosestouseeQuestovermanyothersimulationtoolssuchasDOE2()andEnergyPlus(http://www.eere.energy.gov/buildings/energyplus/).

Anotherissuerelatedtoanenergyauditisbenchmarking.TheEnergyStarProgram,developedandmaintainedbytheEnvironmentalProtectionAgencyintheUnitedStates,providesanexcellentsourceforbenchmarkingbuildingenergyconsumption.TheEnergyStarProgramisavoluntarylabelingprogramoftheUnitedStatesEnvironmentalProtectionAgency(EPA)andtheUnitedStatesDepartmentofEnergythatidenti esenergyef cientproducts,includingbuildings.Quali edproductsexceedminimumfederalstandardsforenergyconsumptionbyacertainamount,orwherenofederalstandardsexist,havecertainenergysavingfeatures.SuchproductsmaydisplaytheEnergyStarlabel.TheEnergyStarlabelisawardedtobuildingsthatperforminthetop25%inthecountry(ascoreof75orbetteroutof100).

Inaddition,theEnvironmentalProtectionAgencyprovidesanonlinetool,theportfoliomanager,forenergyevaluationofanexistingfacilitywithrespecttotheEnergyStardesignation(http://www.energystar.gov/).Thesoftwaretoolallowsausertomanageseveralfacilitiesatthesametime.Toevaluateeachfacility,auserneedstoinputfacilitydata(e.g.,thenameandtheaddressofafacilityandcontactinformationofafacilitymanager),facilityspaceinformation(e.g.,thetypesofspaces,gross oorarea,occupants,thenumberofcomputersandoperationhours)andenergymeters(e.g.,thetypesofenergy,thetypesofspacesthatareassociatedwiththeenergydata,timeperiodoftheenergydata,theenergydataandtheassociatedcost).Oncesuchinformationisinputtothesoftware,thesoftwaretoolwillcalculateascoreforthefacility.Therefore,thisstudywillrelyontheonlinetoolprovidedbytheEnvironmentalProtectionAgencyforevaluatingenergyperformanceofanexistingfacility.

Inthefollowing,thepaperwilldiscussacaseusinganoff-shelfsoftwaretool,eQuest,asacomplementarytooltovalidaterecommendationsfromaconventionalauditingprocess.Detailsofthemodelingprocess,aswellastheresultsofusingthesimulationtechnology,arealsodiscussed.2.Anintroductiontothecase

Thefacilityconsistsofahigh-risetower(of25stories),abridgecrossingtheForsythStreetthatconnectsthehigh-risetoa12-storymid-risetower,themid-risetowerandthe1924building(thehistoricRich’sdepartmentstore)directlyconnectedtothemid-rise.Thetotalareaforthesestructuresismorethan1.4millionsquarefeet(about130,000m2)(seeTable1).Inaddition,thereisa10-storyparkinggarageattachedtothetowerbuilding;fourstoriesofwhicharelocatedundergroundandtherestareabovegradeandblendedinwithadjacentof cespace.

Table1

BuildingphysicalattributesandoperationdataSpacenameSpacetypeStartdateFloorspace(m2)Operatinghours/weekDatacenterComputer7/26/19991040.79168datacenterFoodserviceMercantile7/26/19992917.3440andservicesOf ceOf ce

7/26/1999

134241.1884

Total

138199.31

AninitialstudyontheenergyperformanceofthefacilityindicatesthatthefacilitymaynotbeveryfarfromachievingthedesignationoftheEnergyStar.Theinitialstudy,basedonthemonthlyelectricityconsumptiondatafromAugust2000toJuly2001,showedthatthebuildinghadascoreof62forEnergyStarrating,whichwaslowerthantherequiredscore,75,forEnergyStardesignation(seeTable2).Theanalysisalsoimpliesthattheenergyconsumptionrateofthisbuildingmaybeabovethenationalaveragerate,whichis50accordingtotheportfoliomanager.Inaddition,theenergyconsumptionforatypicalof ceintheUSAisUS$1.5persquarefoot(US$16.15persquaremeter)peryear[18].Forthisbuilding,theenergycostpersquarefootisUS$0.98(fromJuly1999toJune2000)(orUS$10.55persquaremeter)andUS$1.15(fromJuly2000toJune2001)(orUS$12.38persquaremeter),whichfurthersupportstheobservationthatthecurrentstatusofenergyconsumptionisbetterthanthenationalaverage.OthercomparisonsusingUSof cecostindexes[18]alsorevealsimilarresults.

Beforeconductingthecomputerizedsimulationoftheenergyperformanceofthefacility,anALERT(assessmentofloadandenergyreductiontechniques)wasassembledtoperformanassessmentofthefacility,whichresultedinseveralrecommendations.TheexpertsintheALERT(assessmentofloadandenergyreductiontechniques)teamperformedvariousstudiesbyworkingthroughthefacility,interviewingfacilitymanagers,collectingandstudyingas-builtinformation,study-ingthebuildingcontrolsystemandanalyzingthedataandtheinformationfordevelopingrecommendations.

Amongtherecommendations,threeareasaretargetedforimprovements,i.e.,heatingenergyreduction,theHVAC(heatingventilationair-conditioning)fanruntimereductionandsavingsfromlighting.Sincetheimplementationofthoserecommendationshasdifferentcostimplicationsaswell,thefacilitymanagerswouldliketoseecosteffectivesolutions,aswellastohaveasecondopinionontherecommendation.

Table2

Resultsoftheinitialenergyef ciencyassessment

ThisbuildingNationalaverage

YearendingYourtarget

25July2001

Score

627550Energyuse(kWh/m2)248.98212.42291.84Energycost($/year)

1704037

1457501

1927760

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423

Tomeettheneedsoffacilitymanagers,thisprojectintendedtoexplorethoserecommendationsbyutilizingthecomputersimulationtool,eQuest,andtheEnergyStarevaluationtool,theportfoliomanager.Majoractivitiesoftheexecutionplanfortheprojectinclude:

1.ModelingbyusingeQuest.

2.Validatingthemodelwithactualelectricitydata.

3.Evaluatingeachrecommendation,i.e.,recommendation1,heatingenergyreduction;recommendation2,HVACfanruntimereduction;recommendation3,lightingenergyreduction,ingtheelectricitydatageneratedfromeachrecommenda-tion,aswellastheircombinations,fromstep3todeterminetheEnergyStarscorebyusingtheportfoliomanager.5.Makingthe nalrecommendation.

3.Methodology

Inthefollowing,thepaperwilldiscussthemethodologyappliedinthisstudy,includingdatacollection,modelingandmodelassessment.3.1.Datacollection

Dataacquisitionisprimarilyconcernedwithcollectingdatarelevanttotheenergyperformanceofthefacilitytoultimatelysimulatetheactualenergybehaviorofthefacility.Thedatasubstantiallycoversfundamentalbuildingcharacteristicssuchasgeometricalcon guration,internalloads,buildingshell,energysystemsincludingthewater-sideandtheair-sideoftheHVAC(heatingventilationair-conditioning)systemsandoperations.

Thebulkofcollecteddataisgatheredbasedontheas-builtblueprints(e.g.,architectural,electrical,HVAC(heatingventilationair-conditioning),lighting,etc.)andthespeci ca-tionsofthefacility,whileinterviewingwithfacilitymanage-mentpersonnelaugments,validatesandensuresthatdataandinformationareup-to-dateandconformingwiththecurrentbuildingconditions.Thebuildingautomationsystem,MetasysfromJohnsonControls,isanothersubstantialdata-sourceforbuildingoperationdata.Awealthofdatasuchasoperatinghours,andtemperatureandpressuresetpointsarereferencedfromtheMetasys.

ThefollowingarethemajortypesofthebuildingandtheHVAC(heatingventilationair-conditioning)systemdatathatarecollectedforassessingbuildingenergyperformance(fordetailspleasereferthemodelitself):

GeometricalCon gurationandbuildingfootprint. Buildingshellandconstructionmaterials.

Internalloadsincludingoccupancy/un-occupancyloadsofemployeesduringdaytimeandafter-hours,of ceequipment,lightingsystemsandheatingandcoolingloads.

Operatingschedulesincludingoccupancyandafter-hourschedules.

Fig.1.Geometricrepresentationofthefacility(south-east

view).

HVAC(heatingventilationair-conditioning)systemequip-mentandoperation,includingthewater-sideandtheair-sidesystems.3.2.Modeling

Themodeliscreatedfromthebuildingcharacteristicsacquiredfromourbuildingsurveyandtheasbuiltdocumenta-tions,speci cationsanddrawings.

3.2.1.Geometricmodeling

InordertocreateabuildingmodelfortheeQuestsimulation,ageometricmodelofthebuildingiscreatedandthenthecharacteristicsofeachmodeledspace(seeFigs.1and2)arespeci edaccordingly.ThelayoutofthegeometricmodelortheconnectivityofthethermalzonesisbasedonthearchitecturalandtheHVAC(heatingventilationair-conditioning)drawings.Afterwards,theHVAC(heatingventilationair-conditioning)systemofthebuildingismodeled,followedbytheAHUs(airhandlingunits),thecontrollingunitsinthisproject.

Thegeometrymodelofthefacilityis rstcreatedbasedontheworldcoordinatesofthefacilityandthenthemodelisrotated388clockwiseaccordingtotheazimuthangleofthe

Fig.2.Geometricrepresentationofthefacility(south-westview).

Applying computer-based simulation to energy auditing-A case study

424Y.Zhu/EnergyandBuildings38(2006)421–428

Fig.3.Thermalzonedesign.

actualfacility.Theinteriorwallsinthemodelareclassi edintotwotypes:solidwallandairwall.Theinteriorpartitioninginthemodel,whichformsthespaceboundariesofthermalzonesofthemodel,ismodeledbytwocriteria:thethermalzonesaccordingtotheHVAC(heatingventilationair-conditioningsystem)drawingsandthethermalcharacteristicsofthephysicalpartitionsofthe oorsaboveorbelow,fortheconsistencyinspecifyingtheadjacentspaceorthespace‘‘nextto’’orontheothersideofthewall.Forexample(seeFig.3),the oorsofspaceBandCcanbespeci edasinteriorwallsthatarenexttospaceA,insteadofspecifyingtheentire ooraboveAasaninteriorwallnexttospaceBorC,becausethe oorsofspaceBandCmayhavedifferentthermalcharacteristics.Althoughthiswillleadtomorethermalzonesinthemodelthanthosespeci edinthedrawings,itwillimprovetheaccuracyofthesimulationresults.Ontheotherhand,withspaceD(seeFig.3)actingasaplenumspaceabovespaceA,thejobcanbedonemoreeasily,becausenomatterhowbusythepartitionsofthespacesaboveorbeloware,theplenumspacecanbesharedasthe‘‘nextto’’typeofspacefortheinteriorwallspeci cationandcanactasatransitiontothenext oor.

TheplenumspacesabovetheceilingaremodeledtobethereturnairspacesfortheAHUs(airhandlingunits).Likeotherthermalzones,theplenumlayouthastobeconsistentwiththeadjacentspacesontheothersideoftheceilingor oorintermsofgeometry.Toseparateeachplenumfromoneanother,airwallsareusedaspartitions.Inthehigh-risebuilding,theplenumspacesarepartitionedintomainlythreeparts,theplenumin:thetowerarea,theconnectorareaandthebridgearea.Themid-towerbuildingandtheRichbuildingalsohavetheirownplenumspacestoseparatethereturnair,sincetheydonotsharethesameHVAC(heatingventilationair-conditioning)system.

Tosimplifythemodel,themodelusesmultipliersfortypical oors.However,thecomplexityofthebuilding,especiallythetypesofwallsthatdifferfromone oortoanother,limitstheuseofthemultipliertoonlythetypical oorsofthetowerdespitethefactthatmanyother oorshavethesame,orsimilar, oorlayoutintermsofgeometry.

Thermalzonesconsistofperimeter,coreandplenumspaces.Whenmodelingthermalzones,theperimeterspaces,stripsofspacearoundthebuilding,aremodeledas15ft(4.6m)wide;exceptfortheonesofthebridge,whicharemodeledas9ft(2.7m)wide.TheHVAC(heatingventilationair-conditioning)drawingsareusedwhenthethermalzonesaredeveloped.Thehigh-riseandthemid-risehavecurtainwallsystemswithmainlytwotypesofglass.Theremainderoftheexteriorwallsystemismasonryconcreteblocksmaskedandconcealed

withdecorativepre-castconcreteboardsontheoutside.TheRichbuilding,withmoretraditionalwindowopenings,isen-closedwithpale-yellowbrickveneerexteriorwalls.

Theroo ngsystemsare8-in.(20cm)concreteroo ngslabsinsulatedwithfelt-bitumenandrigidinsulatingstucco.Waterproo nganddrainagemattingareusedtoenhancetheresistanceagainstthesevereweatherconditions.Theroo ngsystemsare nishedwithpolishedandhonedterrazzomarble.Theinterior oorsare nishedwithtuftedcarpet.

Thefeaturesofthefacilitydiscussedabovearemajorconsiderationswhendevelopingthegeometricmodel.3.2.2.Internalloads

Thetypesofinternalloadsconsideredinthemodelincludehumanoccupants,overheadlighting,tasklighting,plug-loadsanddatacenters.Thedataismostlycollectedviasurveys.Inmanycases,datacollectedisnotdirectlyassociatedwitheachthermalzone;ratherthedataisthetotalforaspeci c oor,oreventheentirebuilding.Insuchcases,thismodelusesanaveragingapproachbasedonthepercentageofaparticularthermalzoneareatothetotal oorarea.

Whende ninginternalloadsforeachthermalzone,eQuestallowsausertospecifymanytypesofinformation,e.g.,geometricinformationaboutthethermalzonesinthemodel,energyconsumptionforequipmentandlightinginthezone.Inaddition,in ltrationmethodsanddaylightingcanalsobespeci edinthemodel.

3.2.3.Waterandair-sidesystems

Thecentralchillerplantconsistsof veTranechillers,four1310tunitsandone500tunit,andislocatedinthebasementofthehigh-rise,withchilledwaterpumpedthroughoutthefacility(bridge,mid-riseand1924building).AnAlfa-Lavalplateheatexchangerallowswater-sideeconomizeroperation,with2000tofcoolingcapacitywhentheoutdoorwet-bulbtemperatureis388F(3.38C)andfullcoolingtower owismaintained.Coolingtowersareontheroof.Theeconomizerisnotutilizedatthetimeofthisstudyandthusisnotmodeledeither.

Intheprimaryloop,thecon gurationofchillersandpumpsareparallelinthatonechillerisservedbyonepumpforthecondensationcycleandanotherpumpfortheevaporationcycle.Thecon gurationsoftheprimarypumpsandsecondarypumpsareserial.Thedatarequiredforsimulatingtheworkingconditionsofchillers,pumpsandcoolingtowersisobtainedfromequipmentspeci cations,designdocumentsandsurveys.

Theair-sideunitsare oor-by- oorvariablespeedairhandlerswithchilledwatercoils.InteriorzonesarecontrolledbyVAV(variableairvolume)boxestomaintaininteriorspaceconditionsatreasonablecomfortlevels(withnoheatingavailable)andexteriorzonecontrolissupplementedwithPIUs(poweredinductionunits)withheatingcoils.Minimaloutdoorairisprovidedandnoair-sideeconomizersareused.Thedataforsimulatingtheoperationofair-sideunitsisobtainedfromequipmentspeci cations,designdocumentsandsurveys.

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Table3

Electricitydataformodelassessment(units:kWhÂ1,000,000)MonthActualSimulated

14.244.20

23.483.46

33.303.32

43.102.72

52.732.75

62.922.80

73.002.98

82.813.12

92.822.58

102.512.60

112.903.14

425

123.853.68

Table4

Paired-samplest-test

PaireddifferencesMean

Standarddeviation

Standarderrormean

95%con denceinter-valofthedifferenceLower

Actualvs.simulated

0.0256

0.19125

0.05521

À0.1459

Upper0.1971

0.463

11

0.652

t

d.f.

Sig.(two-tailed)

3.3.Modelassessment

Themodelwasassessedbasedonone-year(2001)electricitydata,becausethatyeartheoperationwasrelativelystable.Beforeorafterthatyear,therewereoperationchangesmadetotheHVAC(heatingventilationair-conditioning)systemandeQuestdoesnotsupporttheco-existenceofvariousoperationsforsimulation,whichlimitsouruseofactualelectricitydata.

Paired-samplest-testswereappliedtocomparethedatafromsimulationandfromtheactualelectricitybillstodetermineifthereisasigni cantdifference.Astatisticssoftwaretool,SPSSversion11,wasusedtofacilitatetheanalysis.

Table3shows12-melectricitydatacollectedfromtwosources,i.e.,theactualelectricitybills(labeledas‘‘Actual’’)andthesimulationmodel(labeledas‘‘Simulated’’).Fig.4descriptivelydemonstratesthepatternsofthetwodataseries.ThetwopatternsareverysimilarexceptfordataforApril,AugustandSeptember,whichshowsomeirregularities.Inordertoverifythatthereisnosigni cantdifferencebetweenthetwodataseriespairedsampletestswereperformed.TheresultsofthetestsfromtheSPSSsoftwareareshowninTables4–6.Theprobabilityvalue,0.652,labeledas‘‘Sig.(two-tailed)’’inTable4indicatesthatthereisnosigni cantdifferencebetweenthetwodatasetsatthesigni cantlevelof0.05.Meanwhile,thecorrelationanalysisshowsthatthesetwodatasetsaresigni cantlycorrelated(seeTable5).Thestatistics

Table5

Paired-samplest-testcorrelations

N

Actualvs.simulated

12

Correlation0.925

Levelofsigni cance0.05

Table6

Paired-samplest-teststatistics

Mean

ActualSimulated

3.13813.1125

N1212

Standarddeviation0.500870.48769

Standarderrormean0.144590.14078

(seeTable6)alsoshowthatthemeansforthetwodatasetsareverysimilar.Thestatisticsanalysisindicatesthatthemodelhasgeneratedviabledata.4.Optimization

Beforetherecommendedenergyconservationplanswereinputtothemodelforevaluation,observationsweremadeabouttheexistingfacilityoperationandmaintenance.IthasbeennoticedthatthefansofAHUs(airhandlingunits)arelockedintomanualmode,meaningthattheyrunallthetimeregardlessofwhattheMetasystellsthemtodo.Thishasnegativerami cationsastohowmuchfanenergyiswastedespeciallyduringunoccupiedperiods.Also,theMetasysprogrammingdoesnotmapthecontrolofthePIUs(poweredinductionunits)toanunoccupiedsettingforcontrollingheating,whichresultsinthePIUs(poweredinductionunits)supplyingheatingenergyevenwhenthecentralAHU(airhandlingunit)fansareoff.Thismeansthattheseterminalunitsoperateduringafter-hourstomaintainspacetemperaturesat728F(228C)oraboveallthetime.ImplementationofheatingsetbackinvolvesmappingtheunoccupiedperiodcontrolofthePIUs(poweredinductionunits)toMetasys,sothatthespaceheatingtemperaturesetpointis728F(228C)duringoccupiedperiodsand688F(208C)duringunoccupiedperiods

Fig.4.Actualvs.simulatedelectricityusage.

Applying computer-based simulation to energy auditing-A case study

426Y.Zhu/EnergyandBuildings38(2006)421–428

(allothertimes).Thesetwoapproachesdonotcosttoomuchtoimplement.

Anothermoreexpensiveapproach,whichmayresultinmoreenergysavings,istoreducethelightingenergyconsumptioninthefacility.Currentlightingpracticesandschedulesdonotre ectoptimizedusageand,ifmonitoredandadjusted,mayprovidesigni cantenergysavings.Mainoverheadof celightsaresupposedtohaveregularoccupancyschedules,yettherealityindicatesthatlightingschedulesextendafter-hourstoallowcleaningcrewstoperformtheirjobsbutwithahugetimewindow.Thisisessentiallyduetolightingcontrollers,whicharecentralizedoneach oorsothatawhole poundedwiththesepractices,thehigh-risecafeterialightingsetupilluminatesapproximately7W/f2(96W/m2)anddoesnotmakeadvantageoususeofdaylightharvestingoftheperimeterlightingcomingthroughthenorthernandsoutherncafeteriaglasscurtainwalls.Ontheotherhand,athresholdof1.8W/f2(19W/m2)hasbeendocumentedbasedonas-builtlightingdrawingsandcouldprovidesuf cientilluminationforthecafeteriaarea.

Multiplerecommendationsareconsideredtooptimizelightingpracticesatthefacility.Havinglightsonmorethan12h/dayisnoteffectiveenergymanagement,sostringentoccupancyschedulesaretobeenforcedtocontrolthefacilitylightingsystems.Forafter-hourof cedemandsand/orjanitorialpurposes,itisidealtodecentralizelightingcontrollers(localization)orinstalloccupancy-sensinglightcontrolssimilartotheEnvironmentalProtectionAgencylightingretro ttingprojecttosuitoccupancyloadsintheworkplaceandtrimonenergyconsumption.Thiscanbeaccomplishedthroughmeansofdetectinghumanpresenceandsignaltoturnlightsonby oorzonesforaspeci edperiod.Decentenergysavingscanbeobservedifnormaloccupancyscheduleshavebeenadaptedtocontrollightingonthebridgeareaaswell.Furthermore,daylightharvestingalongwithas-designedlightingoperationshastobeconsideredwhenimprovingcafeterialighting.Althoughitisdif cultforeQuesttosimulatetheschedule,itispossibleto ndouttheresultsofreducinglightinginthecafeteriaareabyreducingthenumberofwattspersquarefootage.

Meanwhile,uponreviewingtheEnvironmentalProtectionAgency’soverheadlightingmeteredbillfor30October2002,apowerdensity gureof0.88W/f2(9.47W/m2)hasbeenmeasuredafterthecompletionoftheEnvironmentalProtectionAgency’slightingretro ttingproject.Of ceoverheadlightingloadof1.2W/f2(12.92W/m2)hasbeensubstitutedfor

Fig.5.Electricityconsumptionbydifferentscenarios.

EnvironmentalProtectionAgency’scalibrated gureinallof cezones.

Inaddition,normaloccupancyschedule(6:00a.m.to6:00p.m.withautomaticshutdownforthenight)takesplaceatthebridgeareatoregulatelightinginsteadofthe24h/day,7days/weekcurrentoperationalmode.ThesefeaturesarethenintroducedtotheeQuestmodelforevaluation.Fig.5andTable7showtheresultsoftheevaluation.

Table7includesfourdataseriesbymonth.The rstistheseriesofactualdatacollectedfromelectricitybillsofthefacility.Thesecond,thirdandfourthseriesincludedatageneratedfromthesimulationmodelafteroptimizationstepswereintroducedtothemodelrespectively,i.e.,heatingsetpoints,thefanoperationandlightingenergyreduction.Resettingheatingsetpointswas rstintroducedtothesystem,whichresultedina4%energyreduction(seeTable7)comparedtothetotalenergyconsumptionofthe‘‘Actual’’dataseries.Thenoptimizingfanoperationwasaddedtothemodel,whichresultedin17%ofenergyreductioncumulativelycom-paredtotheactualtotalenergyconsumption.Ontopofthesetwostrategies,lightingenergyreductionwasintroducedtothemodel.Therewasatotalenergysavingof22%observedfromthesimulation.5.Energyevaluation

ThreedataseriesinTable7,i.e.,theHeating,theHeating+FanandtheHeating+Fan+Lighting,werethenusedasthreesituationsofenergyconsumptionandwereinputintheportfoliomanagerseparatelyfortheevaluation.Table8belowshowstheresults.Themodelshowsthatwhenimplementingvariousenergy-savingscenariosthefacilitycanachieveEnergyStarlabelstatusof75orabove.Uponinspection,

Table7

Meteredandsimulatedelectricityusage(units:kWhÂ1,000,000)Month

ActualHeating

Heating+fan

Heating+fan+lighting

14.243.973.303.20

23.483.222.682.59

33.303.122.722.58

43.102.702.412.27

52.732.752.422.26

62.922.802.452.30

73.002.982.602.43

82.813.122.772.58

92.822.582.222.07

102.512.602.322.16

112.902.942.522.39

123.853.402.712.62

Total37.6636.1831.1229.45

%Saved4.0017.0022.00

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Y.Zhu/EnergyandBuildings38(2006)421–428

427

Table8

EnergyStarevaluationresultsSolutionFloorspace(m2)Actualenergy

Scoreintensity(kWh/m2)Heating

138199.31262.2566Heating+fan138199.31245.2377Heating+fan+138199.31

213.39

80

lighting

usingonlythelow-costsolutions,resettingheatingsetpointsorfanoperation,canreducetheoverallenergyconsumptionsigni cantly,butmaynotguaranteeanEnergyStarratingforthefacilityconsideringvariationsinthesimulatedresults.Whenapplyingacombinationofallthreestrategies,considerablesavingscanbeattained,whichoffersahighpossibilityofleadingtotheEnergyStardesignation(seeTable8)6.Conclusion

Thestudyhasindicatedthatcomputer-basedsimulationisavaluabletechniquetoassistfacilitymanagersindeterminingenergyconservationsolutions.Thisproject,,hasanalyzedtheoperationofanexistingfacilityinordertoformulatemethodsforachievingtheEnergyStartdesignation.Basedonexpertobservationsandqualitativeanalysis,threestrategiesareformulated.Thisprojectistoquantifytheircumulativeresultstodeterminewhethertheyaresuf cientfortheenergysavinggoal.Accordingtothestudy,resettingheatingsetpointsalonewillnotleadtosuf cientenergysavingstoachievethedesignation.Thecombinationofresettingheatingsetpointsandcontrollingthefanoperationofairhandlingunitswillresultinsuf cientenergysavings,whichmaybeenoughforgettingthedesignation.However,acombinationofthethreestrategieswillmostlikelybesuf cientenoughforachievingtheEnergyStardesignation.

Inaddition,throughthisstudy,someobservationsregardingtheuseofthesimulationtoolhavebeenmade.Althoughcomputer-basedsimulationoffersavaluabletooltoenergystudiesliketheoneperformedinthisproject,theprocessofcreatingthesimulationmodelisverytimeconsumingandresourcedemanding.Especially,foracomplexfacilitysuchasthefacility,correctlyde ningthermalzonesbecomesamajorchallenge,becausethermalzoneswillsigni cantlyaffectthesimulationresults.Ontheotherhandoverde ningthermalzoneswillcomplicatethework.Anotherchallengeisacquiringdata,whichisthebaseforbuildingaviablemodel.Thesuccessofasimulationprojectisoftenatthemercyoftheavailabilityofdata,suchasas-builtbuildingdata,systemspeci cations,operationschedulesandsoon.Thisrequirementmayputsomefacilityoffthelimitforsimulation,astheremightbetremendousdif cultyingettingproperdata.Otherwise,theaccuracyofthemodelwillbecompromised.Inaddition,therearestilllimitationsinthetools,whichprohibitthemodelfromre ectingthereality.Forexample,thereisonlyonetypeof

operationschedulethatcanbeusedinonesimulationcalculation.However,inrealty,duringthetimeperiodthatamodelcovers,theremightbeseveraldifferentoperationschedulesofthesametype.InexistingsimulationtoolssuchaseQuest,thiscannotbemodeled.Alltheselimitationsoftheexistingtoolswilleventuallycontributetothedisparitybetweentheresultsfromtheactualelectricitybillsandthemodels.

Nevertheless,thesimulationoffersareusableandeffectivetoolforenergyef ciencystudies.Forexample,thecross-effectoftwoenergysavingplanssuchaslightingenergyreductionandHVACfanoperationschedulecanbecalculatedbythesimulationmodel,whileamanual-basedauditmayoverlooksucheffect.

Thestudyhasalsoobservedthatexistingsimulationtoolsareingenerallackofcapabilitiestointegratewithothersoftwaretoolssuchascostestimation.Itwouldbemorehelpfultofacilitymanagers,ifasimulationtoolcanalsogenerateacostestimatewithrespecttoaspeci cenergyconservationsolution,becauseeventuallycostsavingsareoneofthemostconvincingparametersthatfacilitymanagerswillconsiderinordertomakeadecisionofselectinganenergyconservationsolution.Acknowledgements

TheauthorwouldliketoexpressthankstotheGeneralServicesAdministration eldof ceforprovidingas-builtinformation,aswellasparticipationinvarioussurveys.TheauthoralsowouldliketothankGeneralServicesAdministra-tionforproviding nancialsupportforthisproject.References

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