Deliverable D7.3 Final Evaluation report · Document Title Final Evaluation report Version 1 Status Resubmission Work Package WP7 Deliverable Type R1 Contractual Date of delivery

Deliverable D7.3

Final Evaluation report Work Package 7

Responsible Unit:KTH Authors: UNITN, FBK, KIT

FP7-SMARTCITIES-2013|ICT-2013.6.4|GA608774Deliverable7.3Page2/100

Version:Finalversion;VersionDate:2017.01.31

DocumenttechnicaldetailsDocumentNumber 7.3

DocumentTitle FinalEvaluationreport

Version 1

Status Resubmission

WorkPackage WP7

DeliverableType R1

ContractualDateofdelivery 2017.01.31

ActualDateofDelivery 2017.01.31

ResponsibleUnit KTH

Contributors UNITN,FBK,KIT

KeywordsList Testsites,CIVIS,ICT,Energy

DisseminationLevel PU2

1DeliverableType:P=Prototype,R=Report,S=Specification,T=Tool,O=Other2DisseminationLevel:PU=Public,RE=RestrictedtoagroupspecifiedbytheConsortium,PP=Restrictedtootherprogramparticipants(includingtheCommissionservices),CO=Confidential,onlyformembersoftheConsortium(includingtheCommissionservices).



DocumentchangelogVersion Date Status Author(Unit) Description

0.1 2016.06.02 Outline KTHwithotherpartners

Outlineofthedeliverable

0.2 2016.07.31 Draft KTHwithotherpartners

TableofContentsandlistofcontributors

0.3 2016.09.03 Draft UNITN Chapter2socialaspects

0.3 2016.09.16 Draft FBK Chapter2energyparts

0.4 2016.09.20 Draft KTH Chapter3

1.0 2016.09.29 Draft KTHwithotherpartners

Draftforinternalreview

1.1 2016.09.30 Draft ICL Internalreview1

1.2 2016.10.04 Draft IST Internalreview2

2 2016.10.11 Draft KTH Draftforqualitycheck.

2.1 2016.10.25 Draft UNITN Qualitycheckreview

2.2 2016.10.26 Draft KIT Inputonconclusionchapter

Final 2016.10.28 Final KTH Finalforsubmission

2017.01.18 Review EC Reviewresultsreceived

3.1 2017.01.24 Draft KTH,UNITN,FBK Revisionsplanningandtaskassignment



3.2 2017.01.27 Draft FBK Revisionsreceivedregardingcomments2,7-11

3.3 2017.01.27 Draft UNITN Revisionsreceivedregardingcomments4&5.

3.4 2017.01.30 Finalforinternalreview

KTH Integrationofcommentsandfinaldraftforqualitycheck

Final 2017.01.31 Final KTH FinalforSubmission



CIVISConsortiumCIVIS (Grant Agreement contract No. 608774) is a Collaborative Project within the 7thFramework Programme, theme FP7-SMARTCITIES-2013, ICT-2013.6.4. As defined in theConsortiumAgreement,membersoftheConsortiumare:

No. Beneficiaries

1

UNIVERSITADEGLISTUDIDITRENTO,establishedinVIACALEPINA14,38122TRENTO-ITALY,representedbyMr.PaoloCOLLINI,Rector,orhisauthorisedrepresentative,thebeneficiaryactingascoordinatoroftheconsortium(the"coordinator").

2AALTO-KORKEAKOULUSAATIOestablishedinOTAKAARI1,00076AALTO-FINLAND,representedbyMrIlkkaNIEMELÄ,DeputyPresidentand/orTuijaPULKKINEN,VicePresident,ortheirauthorisedrepresentative.

3FONDAZIONECENTROSTUDIENELestablishedinVIALEREGINAMARGHERITA137,00198ROMA-ITALY,representedbyMrFrancescoSTARACE,President,orhisauthorisedrepresentative.

4

IMPERIALCOLLEGEOFSCIENCE,TECHNOLOGYANDMEDICINEestablishedinExhibitionRoad,SouthKensingtonCampus,SW72AZLONDON-UNITEDKINGDOM,representedbyMsCaroleMEADS,SeniorNegotiator,EuropeanPolicyand/orMrJamesLLOYD,ContractsAdministrator(Europe),ortheirauthorisedrepresentative.

5INSTITUTOSUPERIORTECNICOestablishedinAvenidaRoviscoPais1,1049-001LISBOA-PORTUGAL,representedbyMrArlindoOLIVEIRA,President,orhisauthorisedrepresentative.

6

KarlsruherInstitutfuerTechnologieestablishedinKaiserstrasse12,76131Karlsruhe-GERMANY,representedbyMrBernhardDASSELAAR,HeadofCostandFundManagementand/orMrWolfFICHTNER,HeadofIIP,ortheirauthorisedrepresentative.

7

KUNGLIGATEKNISKAHOEGSKOLANestablishedinBRINELLVAGEN8,10044STOCKHOLM-SWEDEN,representedbyMrPeterGUDMUNDSON,Presidentand/orMrKennethBILLQVIST,HeadofResearchOffice,ortheirauthorisedrepresentative.



8SANTERREPLYSPAestablishedinVIAROBERTKOCH1/4,20152MILANO-ITALY,representedbyMrLuigiCICCHESE,Partner,orhisauthorisedrepresentative.

9

NEDERLANDSEORGANISATIEVOORTOEGEPASTNATUURWETENSCHAPPELIJKONDERZOEK-TNOestablishedinSchoemakerstraat97,2600JADELFT-THENETHERLANDS,representedbyDrs.RenéHOOIVELD,DirectorofSustainableEnergy,orhisauthorisedrepresentative.

10TECHNISCHEUNIVERSITEITDELFTestablishedinStevinweg1,2628CNDELFT-THENETHERLANDS,representedbyMrJeroenVANDENHOVEN,Deanand/orMrHansDEBRUIJN,Vice-Dean,ortheirauthorisedrepresentative.

11

CREATE-NET(CENTERFORRESEARCHANDTELECOMMUNICATIONEXPERIMENTATIONFORNETWORKEDCOMMUNITIES)establishedinVIAALLACASCATA56/D,38123TRENTO-ITALY,representedbyMrImrichCHLAMTAC,President,orhisauthorisedrepresentative.

12FONDAZIONEBRUNOKESSLERestablishedinVIASANTACROCE77,38122TRENTO-ITALY,representedbyMrAndreaSIMONI,GeneralSecretaryand/orhisauthorisedrepresentative.



TableofContent

TableofContent.......................................................................................................................7

ListofFigures.........................................................................................................................13

ListofTables...........................................................................................................................13

ExecutiveSummary................................................................................................................14

1 Introduction....................................................................................................................151.1 WorkPackage7andDeliverableObjectives....................................................................151.2 TargetAudience...................................................................................................................151.3 ReportOverviewandstructure..........................................................................................161.4 SummaryofUpdates............................................................................................................16

2 ItalianTestsiteevaluation.................................................................................................202.1 Energyevaluation:datacollectionandmethodology..............................................................242.2 AnalysisoftheToUsignalinterventionforcommunitiesofenergyprosumers........................25

2.2.1ToUsignals:introduction...............................................................................................................252.2.2ToUsignals:methods.....................................................................................................................262.2.3DSOelectricalbalances..................................................................................................................272.2.4ToUsignals:timedistributionoflowsignals.................................................................................322.2.5Analysisofthewithdrawalprofiles...............................................................................................342.2.6Socialacceptanceofinterventionsandparticipants’behaviours.................................................42

2.3ResultsofelectricaldataanalysisinItaliantestsite.......................................................................502.3.1CEIS................................................................................................................................................50

2.4Analysisofthethermaldemand....................................................................................................592.4.1OutdoortemperaturesinCEISareaandinCEDISarea.................................................................602.4.2IndoortemperaturesinCEISareaandinCEDISarea....................................................................622.4.3EvaluationofoverheatinginCEISareaandinCEDISarea.............................................................632.4.4SpaceheatingdemandinCEISareaandinCEDISarea..................................................................64

3 EvaluationofactionsinSwedishTestsite..........................................................................673.1 SummaryofactionscarriedoutinSwedishTestsite...............................................................673.2 Datacollectionandanalysis....................................................................................................683.3HammarbySjöstadHousingAssociationsIntervention..................................................................70

3.3.1CIVISapputilization.......................................................................................................................713.3.2EnergyAnalysis..............................................................................................................................73

3.4 HouseholdEnergyVisualizationandTipsAppinHammarbySjöstad.......................................803.5 Smappee.................................................................................................................................86

3.5.1InterviewwithSmappeeusers......................................................................................................88



3.6 MAXHeatingControlSystem..................................................................................................903.6.1Maxsurveyresults.........................................................................................................................95

4 CONCLUSION.....................................................................................................................98



List of Figures Figure1LocationoftheCIVISItalianpilotsites............................................................................................20Figure2InstallationofCIVISsmartmeteringintheItalianpilotsites(1);CurrentCostsmartmetering(2);YouPowerApp(3)..........................................................................................................................22Figure3YouPowerusersengagementinItalyandinSweden(datafromtheYouPowerapp).Inpurpleyoucanseehow“Trentinoprosumptionrequest”(ToUsignal)isbyfarthemostengagingfeatureinCIVISproject(ItalianlaunchofYouPowerwas11March2016).................23Figure4ComparisonbetweenhourlyinjectionofCEISplants(sx)andhourlyconsumptionofCEISmembers(dx).....................................................................................................................................................28Figure5CEISel.grid:powerpurchasedfromNationalGrid(hourly,2013,sx)andpowersoldtoNationalGrid(hourly,2013,dx)......................................................................................................................29Figure6ComparisonbetweenhourlyinjectionofCEDISplants(sx)andhourlyconsumptionofCEDISmembers(dx).............................................................................................................................................30Figure7CEDISel.grid:powerpurchasedfromNationalGrid(hourly,2013,sx)andpowersoldtoNationalGrid(hourly,2013,dx)............................................................................................................31Figure8CEIS:timedistributionoflowsignals(2016,%oflowsignalsintheconsideredtimeslot)....................................................................................................................................................................................32Figure9CEDIS:timedistributionoflowsignals(2016,%oflowsignalsintheconsideredtimeslot)………………………………………………………………………………………………………………………………….33Figure10AveragewithdrawalprofileofCEISparticipantsinCIVISproject(2016,%ofthedailyconsumptionfromgrid)................................................................................................................................34Figure11Individualpercentageofwithdrawalshifting,ingreenYouPowerusersforthetotal(TOT)trialperiod(Youpowerusersingreen,nonusersinblue).........................................................36Figure12Individualpercentageofwithdrawalin“lowsignal”,ingreenYouPowerusersforthetotal(TOT)trailperiod(Youpowerusersingreen,non-usersinblue)......................................37Figure13AveragewithdrawalprofileofCEDISparticipantsinCIVISproject(2016,%ofthedailyconsumptionfromgrid)................................................................................................................................39Figure14Individualpercentageofwithdrawalshiftingfortotal(TOT)trialperiod,ingreenYouPowerusers,nonusersinblue......................................................................................................................40Figure15Individualpercentageofwithdrawalin“lowsignal”,forthetotal(TOT)trialperiod(Youpowerusersingreen,non-usersinblue)..............................................................................................41Figure16DifficultiestofollowToUsignals,inascalefrom1(notdifficultatall)to5(verydifficult)...........................................................................................................................................................................44Figure17Distribution(%)ofperceptionofamusementfollowingToUsignal...............................45Figure18OpinionsaboutEnergyTipsfeature...............................................................................................46Figure19Opinionsaboutdatadisplayfeature.............................................................................................47Figure 20 Family participation to consumption shifting..................................................................................48



Figure21Resultsofthequestion“Haveyoutakenmeasurestoreduceelectricityconsumption?”..............................................................................................................................................................49Figure22PVproductionofCEISparticipantsinCIVISproject...............................................................51Figure23PVinjectionintogridofCEISparticipantsinCIVISproject.................................................52Figure24PVself-consumption(%)ofCEISparticipantsinCIVISproject.........................................52Figure25ElectricalconsumptionfromgridofCEISparticipantsinCIVISproject........................53Figure26TotalelectricalconsumptionfromgridofCEISparticipantsinCIVISproject.............54Figure27PVproductionofCEDISparticipantsinCIVISproject............................................................55Figure28PVinjectionintogridofCEDISparticipantsinCIVISproject..............................................56Figure29PVself-consumption(%)ofCEDISparticipantsinCIVISproject......................................56Figure30ElectricalconsumptionfromgridofCEDISparticipantsinCIVISproject.....................57Figure31TotalelectricalconsumptionfromgridofCEDISparticipantsinCIVISproject..........58Figure32Resultsofthequestion“Haveyoutakenmeasurestoreducespaceheatingconsumption?”..............................................................................................................................................................59Figure33HourlyvaluesofToutdoorinCEISarea.WeatherstationT0414-SanLorenzoinBanale(Pergoletti)......................................................................................................................................................60Figure34HourlyvaluesofToutdoorinCEDISarea.WeatherstationT0393-Storo..................61Figure35Monthlyaveragetemperaturesforeachinvolvedfamily(CEISandCEDIS)................62Figure36Percentagehoursinoverheatingforeachinvolvedfamily(CEISandCEDIS)duringCIVISperiod(01/07/2015–30/06/2016).....................................................................................................64Figure37SpaceheatingdemandevaluationinCEISandCEDIS(standardvsrealTind)duringCIVISperiod(01/07/2015–30/06/2016).....................................................................................................65Figure38SummaryofactionscarriedoutinSwedishTestsite.............................................................67Figure39ScreenshotoftheCIVISappinHammarbySjöstadpopulatedbytheactivehousingassociations.Thecolorsoftheassociationisbasedonascaleoftheirenergyconsumption....72Figure40YouPowerusagedatafortwoparameters;the“cooperativeactionsexpanded"and“cooperativeviewed”(Nov2015-Aug2016)................................................................................................73Figure41Normalizedannualheating&hotwaterconsumptiondataforCIVISusers(KWh/m2-year)............................................................................................................................................................75Figure42AnnualelectricityconsumptiondataforCIVISuserassociations(2012-2015)inKWh/m2-year...............................................................................................................................................................76Figure43Monthlynormalizedheating(MWh)andelectricity(MWh)dataforhousingassociationsÄlven,Grynnan,HolmenandSjöstaden1for2014-2016...............................................78Figure44Monthlynormalizedheating(MWh)andelectricity(MWh)dataforhousingassociationsSeglatsen,SicklaKanal,HammarbyKanalandHammarbyEkbackefor2014-2016..............................................................................................................................................................................................79Figure45AppusagedataforhouseholdpartofYouPowerapp............................................................81Figure46Min,MaxandMedianelectricityconsumptionin137apartmentsinBRFSeglatsen



groupedbysizeofapartments(KWh)fromJune15-August16...........................................................82Figure47Min,MaxandMediandomestichotwaterconsumptionin137apartmentsinBRFSeglatsengroupedbysizeofapartments(m3)fromJune15-August16.........................................83Figure48Electricityconsumptionprofiles(KWh)forYouPowerusersinBRFSeglatsenJune2015-August2016withredverticallineshowingthetimeofdeployment....................................84Figure49Electricityconsumptionprofiles(KWh)forYouPowerusersinBRFGrynnanJan2015-Aug2016withredverticallineshowingthetimeofdeployment..........................................85Figure50Smappeeusers'consumptiondatainFårdala(KWh)............................................................86Figure51Smappeeusers’consumptiondatainHammarbySjöstad(KWh)…………………………86Figure52No.ofappliancesdetected,labelledandnoofplugsinstalled............................................88Figure53TypicalinstallationconfigurationforMaxheatingcontrolsysteminFårdala............90Figure54PercentagechangeinconsumptioncomparedtobaselineforMaxusersinFårdala..............................................................................................................................................................................................93Figure55Average,minandmaxtemperatureprofilesforindoortemperatures(DegreeC)forMaxusersinFårdala..................................................................................................................................................94Figure56OverallimpressionoftheMaxusers(1)verybadto(5)verygood.................................95Figure57Levelofdifficultyofusefrom(1)verydifficultto(5)verysimple...................................96Figure58Frequencyofinteractionwiththesystemfrom(1)neverto(5)veryoften................96Figure59Modeofinteractionwiththesystem..............................................................................................96Figure60Satisfactionlevelofusers....................................................................................................................97Figure61Percentageofusersthatloweredthetemperatureislessfrequentlyusedrooms...97Figure62Percentageofusersthatusedtheschedulingfunction..........................................................97

List of Tables Table1NumberofinvolvedfamiliesinItalyandinstalledsmartsensors........................................22Table2Numberofplants(withinstalledpower)propertyofCEISandconnectedtoitsownelectricgrid(2013).....................................................................................................................................................27Table3Numberofplants(withinstalledpower)propertyofCEDISandconnectedtoitsownelectricgrid(2013).....................................................................................................................................................30Table4CEISpercentageofwithdrawalshifting............................................................................................36Table5CEISpercentageofwithdrawalin“lowsignal”..............................................................................38Table6CEDISpercentageofwithdrawalshifting.........................................................................................40Table7CEDISpercentageofwithdrawalin“lowsignal.............................................................................42Table8MonthlyvaluesofToutdoorinCEISarea.WeatherstationT0414-SanLorenzoinBanale(Pergoletti)andPVGIS...............................................................................................................................60



Table9MonthlyvaluesofToutdoorinCEDISarea.WeatherstationT0393–StoroandPVGIS..............................................................................................................................................................................................61Table10Monthly%hoursinoverheatingforeachconsortium(CEISandCEDIS)duringCIVISperiod(01/07/2015–30/06/2016)..................................................................................................................63Table11MonthlySHdemandevaluationinCEISandCEDIS(standardvsrealTind)duringCIVISperiod(01/07/2015–30/06/2016).....................................................................................................66Table12OverviewofevaluationmethodologyforvariousinterventionsintheSweidishtestsite......................................................................................................................................................................................69Table13ListofBRFswheredatacollectionforCIVIStookplacewithCIVISusersmarkedby*..............................................................................................................................................................................................70Table14AsampleofenergyactionsenerterdbytheenergymanagersintheYouPowerapp...............................................................................................................................................................................................71Table15DegreedaysforStockholmfor2013-2016comparedwiththe"NormalYear"degreedays....................................................................................................................................................................................74Table16NormalizedheatingdataforQ1andQ22016alongwithcorrespondingaveragebaselines(KWh)...........................................................................................................................................................92



TermsandAcronymsBRF HousingAssociation(BostadsrättsföreninginSwedish)CEdiS ElectricalConsortiumofStoroCEIS IndustrialElectricalConsortiumofStenicoCPI CategoryPerformanceIndexDOW DescriptionofWorkDSO DistributionSystemOperatorDSS DecisionSupportSystemEE EnergyEfficiencyESP EnergySolidarityProjectHSW HouseholdSanitaryWaterICT InformationandCommunicationTechnologyPV PhotoVoltaicSCPI Sub-categoryPerformanceIndexSEF SpecificEmissionsFactorSH SpaceheatingToU TimeofUseRES RenewableEnergySystemWP WorkPackage



ExecutiveSummary

ThisreportprovidesthefinalevaluationofthetestsitesbasedontheWorkPackage7(WP7)objectives,aslaidoutintheCIVISDescriptionofWork(DoW)notably:

• To measure the reduction of energy consumption and of CO2 emissions through theintroductionoftheCIVISICTplatform.

• Toanalyse thesocialandeconomicdrivers for thesuccess (or failure)of themeasures.Thesewillbedeterminedbymeansofqualitativeanalysis.

ThisdeliverablepresentstheanalysisofimpactfortheinterventionscarriedoutintheItalianandSwedishtestsitesattheendoftheproject.Duringthethirdyearoftheproject,theCIVISICT platform, YouPower, was deployed in the test sites. The sensor deployment wascompletedinthetestsites.IntheSwedishtestsites,themainfocusoftheinterventionswason heating at housing association level in Hammarby Sjöstad and at household level inFårdala. In the Italian sites ToU signal was introduced in order to facilitate demand sidemanagementandprosumerself-consumption.Following the completion of intervention deployment and trial period, the results of themeasures were analysed. Surveys and interviews were conducted in order to gain betterunderstanding of user behaviours and motivation to change. In Hammarby Sjöstad, thehousing association part of the trial achieved good results, with a continuation processalready on going to expand the activities started with CIVIS. In Fårdala, heating controlthroughMAX resulted in positive savings in heatingdemandduring the trial period. In theItalian test sites, therewas an increase in PV self-consumption and an overall reduction inelectricity consumption. The ToU engagement was also more pronounced among theprosumers.Theanalysisofheatingdataalsosuggestspositiveimpact.Overall,theprojectwasabletoachievesuccessfullyenergyreductioninsomeoftheusecaseswhile engagement was lower in the others. Various socio-economic factors contributed tothat.Ingeneralcollectivemeasureswithhighsavingspotentialweremoresuccessful.



1 IntroductionAttheendofthethree-yearsCIVISproject,theDeliverable7.3“EvaluationReport”describesand discusses themain results, based on themeasurements collected in the different PilotSites.Thetestedconceptsandtechnologies,consistingintheinteractionoftheenergywiththeICTandthesocialdimensions,areevaluatedintheirpotentialitiestoinfluencetheenergyusageandthecorrelatedCO2emissions,insocalled“smartcities”.

1.1 WorkPackage7andDeliverableObjectives

ThemainobjectiveofWP7istotesttheeffects,intermsofreducedenergyuseandreducedCO2emissions,ofthetechnologyproposedwithintheCIVISproject,byrunningextensivereal-lifeevaluationtestsonthetwopilotsites.Thefollowingobjectivesareidentified:

• To measure the impact on energy consumption and of CO2 emissions through theintroductionoftheCIVISICTplatformandotherinterventions.TheenergyuseandCO2emissions will be determined from detailed measurements of energy supply(electricity,fuels,districtheating/cooling)and/orenergyuse(electricity,sanitaryhotwater,heating).

• Toanalysethesocialandeconomicdriversforthesuccess(orfailure)ofthemeasures.Thesewillbedeterminedbymeansofqualitativeanalysis.Theexpectedoutcomeofthe measurement is also to suggest explanations for the results, namely, the maindriversfortheenergyandCO2-emissionperformanceofthepilotsites.

Thedeliverable7.3coversthetasks7.3,7.4and7.5uptoM36,dealingwiththefinalresultsfrom themeasurements aswell as an analysis of the tested concepts and technologies formeetingreductiontargetsintermsofenergyconsumptionandCO2emissions.

1.2 TargetAudience

ThisreportaimstoprovideanoverviewofthetestsitestothedifferentCIVISstakeholdersinordertosupporttheproject.Thedisseminationlevelofthisreportispublic.Thereporthelpsintheunderstandingofthesocio-technicalaspectsofthetestsitesandisusefulforstakeholderwithinCIVISaswellasnationalandlocalactorsintheenergycontext.Private



entitieswithinterestinenergyefficiencycanalsofindthereportusefulinunderstandingthesystemsinplaceontestsite.

1.3 ReportOverviewandstructure

Thereporthasbeenstructuredinfollowingway:

Chapter1:providesandintroductiontotheobjectives.

Chapter2:coverstheevaluationofItaliantestsites.TheimpactofToUsignal,visualizationofuserdataandimpactofthermalenergyusearepresented.

Chapter3:providestheimpactofmeasurescarriedoutinSwedishtestsite.Theinterventionwith housing associations, household level visualization, introducing Smappee energymonitorsandMaxheatingcontrolsystemarepresented.

Chapter4:providesasummaryofimpactintestsitesandconcludingremarks.

1.4 SummaryofUpdates

In this revisedversionof thedeliverableasper theobservations in theFinal reviewreportCNECT/H4/PB/lb (2017) 270089 dated 17th January 2017. Below is a summary of thechangesfollowedbyreferencetorelevantchaptersalongwithcommentsontheupdates.

Ser.No.

Reviewers’comment Relevantsection

Page Status/Comments

1. Itisverydifficulttoassessthequantitativeimpactofthesocialaspects(positive/neutral/negative)andrelatedICTonthee.g.energyusage.Itwasnotonlyprobleminshorttermofobservation,butalsoinwrongmethodology,makesunabletocollectandcomparereliablehistoricaldata,makestheusersengagementrelativelylowandmakesdifficult

4 100 Addressedintheconclusionchapter



tocomparetheimpactfromengagedandnon-engagedusersanddwellings.Thefinal,criticalremarksaboutthequantitativeinfluenceofCIzVISshouldbeincludedintheD.7.3.

2. ThepartpresentingtheToUresultsisnotproperlypresented.TheFiguresarenotdescribed(axis,meaningofpresentedvaluesandparameters).Eachsubsectionendswiththe„CEDISpercentageofwithdrawal...”summary,butitisunabletoassesstheresult.TheD7.3shouldpresenttheresultsof„reduction/savings/consumption”measurements.TheinfluenceofCIzVISshouldbedistinguished.ThepresentationofToUpartdoesn’tgivethebasetodrawtheconclusions.

2.2,2.3 Addressed.AxestotheToUFigureshavebeenadded.TheToUpart(chapter2.2)presentsquantitativeresultsaboutelectricalconsumptionshiftingofCIVISparticipants.CIVISparticipantsaredividedinCEISandCEDISusers,YouPowerusersandnon-users,PVownersandnon-owners.OnlytheYouPoweruserswereexposedtothesignals(greenandred)producedbypredictionofthelocalenergysystembalance(basedonpredictionoflocalproductionandpredictionoflocalconsumption).Chapter2.3describesquantitativeresultsofelectricaldataanalysisinItaliantestsites(resultsofreduction/savings/consumptionmeasurements).

3. TheanalysisofmeasurementweremarkedinD7.3aspreliminary(page15).Isitexpectedtoobtainthenon-preliminarymeasurementsinfutureorthefinalevaluationcanbebasedonpreliminaryresultsonly?

1.1 15 Addressed.

4. InItalynotallfamilieswereequippedwiththesensors.Whatwastheinfluenceandroleoffamilieswithoutsensors?

2 22-23 Addressed.DuetotechnicallimitationssomefamiliesparticipatinginCIVISprojectwerenotequippedwithsensors(e.g.lackofinternetconnection,characteristicofthebuildingsthatpreventthetransmissionofdata).ThesefamiliesrepresentonlyasmallnumberbothinCEIS(18/68)andinCEDIS(4/33).DespitethelackofsensorsthesefamilieshaveactivelyparticipatedintheCIVISproject,theyhavebeenengagedinpubliceventsorganizedbytheproject,



andthroughparticipationinquestionnaires.ForthesefamiliestheevaluationofCIVISimpactisonlybasedontheanalysisoftheelectricityconsumption&production(andnotontheanalysisoftheToUsignalandontheanalysisoftheheatdemand).

5. WhythenumberofengagedfamiliesthathavethesensorsinstalledissignificantlygreaterthatnumberofYouPowerappusers?Shouldn’titbeacommitmentincaseofCIzVISbeneficiary(ife.g.familiesgetthesensorsforfree?).

2 22-23 Addressed.InItalyseveralCIVISfamilieswerecomposedbyelderlypeoplethatwerenotusedtointeractwithICTsandsoftwareapplicationslikeYouPower.ThisiswhyseveralfamiliesthatwerepartofCIVISprojectandhavesmartmeterswerenotable/interestedinusingYouPower.However,thesefamilieshavebeenaffectedbyCIVISprojectusinghomedisplaysandthroughparticipationinCIVISsocialmeetings.

6. Page20->(Error!Referencesourcenotfound.)onpreliminaryresultsonly?

2 23 Addressed.

7. Thedescriptionof“Figure3YouPowerusersengagementforItalianusers”(Page20)isnotsufficient.Whatarethefollowingplots(itisnotvisible)Itislackofcomment(especiallyontheindividualincreaseinApril).Howistheresultassessed?

2 23 Addressed.ThedescriptionofFigure3isimproved (adding also axis). It is nowexplain the increase in March/April(based on launch of YouPower app inItaly).Theseresultsshowhow“Trentinoprosumptionrequest”(ToUsignal)isbyfarthemostengagingfeature.

8. Theplotsindeliv.arenotclear.TheXandYaxisshouldalwaysbespecified.Nevertheless,itisunknownwhatisonYaxisonFig.10.WhatisTOTonFig.14and15?Total?OnFig.50thesubsequentplotsarenotdescribed.

2.2.5;3.5

34-39;83-85

Addressed. Axes to the Figure 10 andFigure13havebeenadded.InFigure11,12, 14, 15TOT is the total abbreviationand has been added to the description.Fig 50 and on have been described intextandcaptions.

9. HowtheToUrelatedmeasurementswerecollected?WasitabletodistinguishtheCIV1Suserformnoninhabitantsthatwerenotinvolvedintheproject?

The evaluation of ToU signal in Italy isbasedontimedistributionoflowsignals(inCEISandinCEDIS)availablethroughYouPower app and on withdrawalprofiles of CEIS and CEDIS participantsinCIVISproject available throughCIVIS



smartmeters.ToUevaluationcompares,only between participants in CIVIS,userswhohaveusedYouPowerappandthosethatdidnot.Forprivacyreasonsitwas not possible to use the data ofinhabitantsnotinvolvedintheproject.

10. IftheToUsignalswereavailablethroughYouPowerappsinceMarch2016,whytheFigure3onpage20presentstheperiodsinceOctober?

2 23 Figure 3 includes the use of YouPowerapp both in Sweden and in Italy. InSweden the YouPower app wasintroduce in November (in October wehaveonlysometestof theappbyCIVISdevelopers)

11. Whatthe“withdrawalprofile”means?Itwasusedbutnotdefinedinthedeliv.

2.2.5 34 Withdrawal profile refers toconsumption from electrical grid. Thedefinitionhasnowbeenadded.



2 Italian Test site evaluation InItalyastatisticallysignificantnumberofusers(foratotalof101families)wereinvolvedinCIVISproject.TheyhavetestedtheCIVISenergyICTinfrastructureandservicesformorethanoneyear(fromMay2015).The involved families are part of two different communities of energy prosumers, namelyCEIS3andCEdiS4,locatedinthenorthofItaly(ProvinceofTrento,Figure1).

Figure1LocationoftheCIVISItalianpilotsites

3CEISistheelectricalDSOactiveintheareaofSanLorenzoDorsino4CEdiSistheelectricalDSOactiveintheareaofStoro



CIVIS interventions can be summarized in the use of ICT (smart metering, softwareapplications)toincreaseenergyawarenessandstimulateanimprovementofpositiveenergyandenvironmentalbehaviours(consumeless,consumebetter).InItalyaspecialattentionhasbeenpaidtooptimizingtheuseoflocalrenewableenergysources(RES).CIVIS actions comply with the indications of Article 9 and Article 10 of the EU EnergyEfficiency Directive (2012/27/EU). In the Article 9 (Metering)Member States shall ensurethat,“insofarasitistechnicallypossible,financiallyreasonableandproportionateinrelationto the potential energy savings, final customers for electricity, natural gas, district heating,district cooling and domestic hot water are provided with competitively priced individualmeters that accurately reflect the final customer’s actual energy consumption and thatprovide information on actual time of use”. In the Article 10 (Billing information)MemberStatesshallensurethat“finalcustomershavethepossibilityofeasyaccesstocomplementaryinformation on historical consumption allowing detailed self-checks. Complementaryinformationonhistoricalconsumptionshallinclude:(a)cumulativedataforatleastthethreeprevious years or the period since the start of the supply contract if this is shorter; (b)detaileddataaccordingtothetimeofuseforanyday,week,monthandyear”.Testingthesmartmeteringtechnologiesinarealenvironment,withasignificantnumberofusersandfora longenoughtimeperiod,CIVISprojectcanprovideusefulevaluationsaboutcorrelatedsocialacceptabilityandpotentialenergysavings.TheinstallationsofCIVISsensors(Figure2)beganinMay2015andendedinNovember2015,introducingsmartmeteringofelectrical consumption,PVproduction,outdoor temperature,indoor temperature.TheYouPowersoftwareapplications(active in Italy from11/03/2016,Figure3) includedata visualization in real time, data comparisonwithhistorical data, tips,time of use signals (elaborated from 13/01/2016 and introduced in YouPower from11/03/2016).



Figure2InstallationofCIVISsmartmeteringintheItalianpilotsites(1);CurrentCostsmart

metering(2);YouPowerApp(3)

TheItaliansocialparticipationinCIVISischaracterizedbyatotalof101families,ofwhich68in the CEIS area and 33 in the CEDIS area.Not all the involved families are equippedwithsmartmeters(Table1),duetotechnicallimitationssomefamiliesparticipatingintheprojectwere not equipped with sensors (e.g. lack of internet connection, characteristic of thebuildingsthatpreventthetransmissionofdata).In CEIS, 50 sensors for total electricity consumption (from grid + from PV, if present), 20sensors for PV electricity production and 50 sensors for building indoor temperature areinstalled.InCEDIS,29sensorsfortotalelectricityconsumption,9forPVelectricityproductionand 29 for building indoor temperature are installed. In addition, 2 outdoor temperaturesensorsarelocatedintheCEISareaandother2intheCEDISarea.

Table1NumberofinvolvedfamiliesinItalyandinstalledsmartsensors CEIS CEDISInvolvedfamilies 68 33ofwhich:Equippedwithtotalelectricalconsumptionsensors

50 29

EquippedwithPVelectricalproductionsensors

20 9

Equippedwithbuildingindoortemperaturesensors

50 29

1 2

3



InItalythenumberofYouPower5registrations,attimeofwritingofthisdeliverable,sincetheItalianlaunchofthe11March2016,hasreachedthe32units,ofwhich22inCEIS(32%oftheinvolved families) and10 inCEDIS (30%of the involved families).Not all theparticipantswere able or interested in using YouPower also due to the digital divide affecting severalfamilies,whicharecomposedbyelderlypeoplethatdonothaveenoughtechnologicalskills.Number of actions users have taken per action type show how “Trentino prosumptionrequest” (ToU signals) is by far themost engaging feature, with an usage peak in April ofabout5000login/month(Figure3).

Figure3YouPowerusersengagementinItalyandinSweden(datafromtheYouPowerapp).Inpurpleyoucanseehow“Trentinoprosumptionrequest”(ToUsignal)isbyfarthemostengaging

featureinCIVISproject(ItalianlaunchofYouPowerwas11March2016)

5YouPoweristheCIVISICTPlatform,implementedinthetestsites.MoreinfoaboutthefunctionalitycanbefoundinCIVISDeliverable3.3



2.1 Energy evaluation: data collection and methodology In order to test the CIVIS impact, a lot of data have been collected by local CIVIS partnersinvestigating, describing and quantifying the behaviour of the involved families andcommunitiesintheconsumptionandproductionofenergyandintheinteractionwiththeICTtoolsintroducedbyCIVISproject.Thedatacollectionregardstwotimeperiods:

1) Baselinedata:dataconcerningtheperiodbeforetheCIVISintervention.ThesedataarecollectedfromlocalelectricalDSO,CIVISsensorsandCIVISBaselineQuestionnaire;

2) CIVIS data: data concerning the period after the CIVIS intervention. These data arecollectedfromlocalelectricalDSO,CIVISsensorsandCIVISFinalQuestionnaire.

Thecomparisonbetweenthe twotimeperiods isessential inorder to identifyandquantifytheCIVISimpact.ThetypeofparametersconsideredinthisEvaluationReportinclude:

• IndividualPVproductionandusage:electricityproduction,electricityinjectedintogrid,electricityself-consumption;

• Electricalenergydemand:electricitydemandfromgrid,totalelectricitydemand;• Timeofuse(ToU)signals:timedistributionofhighandlowsignals;• Thermalenergydemand:Toutdoor,Tindoor,spaceheatingdemand.

Theanalysisofall theseparametersallowsacompleteoverviewof theenergybehaviouroftheinvolvedfamiliesandcommunitiesconsideringboththeelectricityandheatdemands.Theevaluationmethodologydescribedinthefollowingchapterissubdividedinthreeparts:

1) AnalysisoftheToUsignalinterventionforcommunitiesofenergyprosumers;2) Analysisoftheelectricityconsumption&production;3) Analysisoftheheatdemand.



2.2 Analysis of the ToU signal intervention for communities of energy prosumers

2.2.1 ToU signals: introduction

Aspart of theEuropeanFP7CIVISproject the introduction of a novel dynamic time-of-use(ToU)signalinanAlpinevalleyinthenorthofItalywasdevelopedandtested.TheaimofthisICT service is the management of the electricity demand side, generating a new form offlexibilityforthelocalloadbalancing.

InCIVISproject, the involvedparticipantswereequippedwithapredictivetoolenablinganoptimizationof thedemandprofiles, improving the fitwith the local renewableproduction.Several positive effects were expected, since it is a win-win situation for DSO, users, andCommunity.ThepositiveimpactsfortheDSOare(1)increasetheelectricityproducedfromlocal own energy plants and consumed bymembers, (2) reduce the necessity of importingenergyfromthenationalgrid.Fortheusersthedecreaseoftheenergytariffcostisthemainimpact.Finally, fortheCommunitythe(1)increaseoftheintegrationofthelocalrenewablesources(inparticularsolar)withthe localdemand,(2)reductionofCO2emissionfootprint,(3) improvement of the local independency from the national grid, represent the mostimportantachievements.

Key features of the dynamic time-of-use signal are the predictions of the local electricitydemandandofthelocalrenewableproduction(HydroandPV).Predictionoflocalelectricitydemand is based on a statistical analysis of hourly historical data received fromDSO (DSOmembers)whilepredictionof localelectricityproduction isbasedon localweather forecast(solarradiationandrainfall)andhourlyhistoricalproductiondatareceivedfromDSO.

Usersenergybehavioursareidentifiedthroughdetailed(3hours’granularity)DSOmeteringbeforeandaftertheintroductionofthenewToUsignal.

In Italy, theexisting tariff schemestilldoesnotrewardvirtuousbehaviourofuserssuchas



prioritisingself-consumption,loweringconsumptionduringpeakhoursetc.So,notonlytherearenoappropriateICTtoolscapableofpromotingthisloadbalancingbenefitsbutalso,fromtheeconomicpointofview,thisisnotencouraged.

In the CIVIS project it is currently proposed a simple signal, electrical consumption isencouraged in “green hours” (“low intervals”) and discouraged in “red hours” (“highintervals”). A competition, promoted by local DSO and local CIVIS partners, supported theconsumptioningreenhoursfinancingsocialinitiativesinthetwocommunities.Theideaistostudy the social acceptability and quantify the potentialities and benefits for the electricitybalance,asthebasisfordesignarealincentiverate(ToUtariff),incollaborationwiththeDSO.

2.2.2 ToU signals: methods

Themodel calculates every day, for a time-horizon of 48 hours and for time intervals of 3hours, a forecast of the electrical energy produced by DSO hydroelectric plants, by DSOphotovoltaicplantsandconsumedbytheDSOmembersofeachconsortium.

Therefore, the ToU signal reflects the total energy balance for each timeslot. If the energybalance is positive (consortium overproduction), the time-interval is labelled as “low”,otherwise(consortiumunderproduction)itislabelledas“high”.Ifduringonedaythereislessthan 3 “low intervals” this minimum value is reached considering as “low” the less overproductivetimeslot.

Concerningthehydroelectricproduction,eachconsortiumregularlyestimatesthequantityofhydroelectricenergythatwillbeproduced.CEISproducesthisforecastevery2weekswhileCEDISonlyonceayear.In“CIVISToUsignal”aredirectlyusedthesedata(sendbyDSOtotheCIVISserver).CEISdataare,ofcourse,morereliablethanCEDISdata.

Electricity consumption by DSO members can be predicted, with good accuracy, usinghistorical data to identify an aggregated average profile for each of the two consortium.Moreover,foreachmonthandforeachweekday,anaverageprofilehasbeenidentifiedusinghistoricaldatareferringtotheyear2013.

AdetailedpredictivemodelfortheDSOPVproductionhasbeendesigned,basedonthesolar radiation forecasts produced by the meteorological model provided by the National



Oceanic and Atmospheric Administration (http://www.noaa.gov/ ,http://nomads.ncep.noaa.gov/),whichisopenlyaccessible.Fromtheradiationweobtaintheamountofenergyproduced,usinga linearmodelpreviouslyfittedto localhistoricaldataofsolar radiation (data from Meteotrentino, http://www.meteotrentino.it/ ) and local PVproduction(datafromDSOplants).Thelinearmodelhasbeenidentifiedusingdatathatcoverthewhole2013.

Themodelqueries theNOAA's server andas soonasdata for thenextdayare available, itproducestheforecast.Thedataaredownloadedeverydayat4AM.

DespiteToUsignalshavestarted tobeprocessed from13/01/2016, theirviewingbyCIVISusershavebeenpossible,inYouPower,onlyfrom11/03/2016.

2.2.3 DSO electrical balances

2.2.3.1 CEIS

CEISproduceselectricityusingonlyrenewablesources,ithastheownershipof1hydropowerplant(4MW)and5PVplants(1MW)connectedtoitsownelectricgrid(Table2).

Table2Numberofplants(withinstalledpower)propertyofCEISandconnectedtoitsownelectricgrid(2013)

Renewableenergysource

Numberofplants

InstalledPower(kW)

PV 5 1,045Hydropower 1 4,000Total 5 5,045

Thelocalelectricitydistributiongridofmediumvoltage(MV)andlowvoltage(LV)isownedby CEIS. Two MV interconnection points with the national grid ensure the continuous,bidirectional, exchange of electricity between CEIS local grid and national grid. CEIS sellsexcess production to and buy lacking electricity from the regional company called TrentaS.p.A.While the electrical production of CEIS is 100% from renewable sources, electricitypurchasedfromthenationalgridpresentafractionof29.5%(year2013).CEISestimatesfor



theyear2013acost for the localelectricalgenerationonaverageequal to56€/MWh,buyelectricityfromTrentaS.p.Acostsonaverage66€/MWh.

AsCIVISproject stakeholder, CEIShasprovidedhourlydataof injection into the gridof itsownplantsaswellashourlydataofconsumptionfromgridofitsownmembers(year2013,Figure4).

Figure4ComparisonbetweenhourlyinjectionofCEISplants(sx)andhourlyconsumptionof

CEISmembers(dx).

While electricity consumption shows small variations atmonthly level, electricity injectionshows considerable fluctuations. Production from hydro largely dominates the overallproduction in CEIS and is dependent on direct rainfall and snowmelt (reaching a pick inspringandinautumn).MovingtoPV,itsproductionisdependentonthesolarradiation,withthehighestvaluesinsummer.

Theanalysisofgridbalancesneedsatleastanhourlydetail.Injectionprofilesarenotabletoobtainasuitablefittingwithconsumptionprofiles,thelattercharacterizedbyamorningpeakand an evening peak. Hydro injection is almost not regulated due to the absence of a realstoragebasin.Regulationactivitycouldn’tbeperformedalsoforPV(nostorage).

InFigure5 theelectricityexchangeswith thenationalgrid (importandexportwithTrentaS.p.A.)arequantifiedandanalysed.During thereferenceyear2013CEIS imported3.4GWh(peakofimport2.4MW)andexported5.2GWh(peakofexport3.1MW).



Figure5CEISel.grid:powerpurchasedfromNationalGrid(hourly,2013,sx)andpowersoldto

NationalGrid(hourly,2013,dx)

Thesedatadescribeanenergysystemcharacterizedbyahigh fractionofrenewableenergyproduction.Thisenergyisunpredictableandnotprogrammable, there isaclearproblemofenergybalancing.Indeed,couldinterleaveperiodsofhighproductionwithexcessenergyandperiodsoflowornoproductionwithdeficitenergy.Thesehighintermittentpowerflowsputstressandimbalancesintheelectricgridofdistributionandtransmission,makingdifficulttoensureacontinuoussupplywithhighqualityfortheconnectedusers.

In order to improve the match between production and demand, several storageinterventions are possible: (1) improve the managing of the existing small hydro storagereservoirorenlargingit,(2) introducepumpinghydro,(3)introduceotherformsofstoragelikebatteriesorhydrogen.

There is also another, far cheaper, possible intervention: work on the demand side andpromotetheloadshifting.ThisisthegoaloftheToUsignalproposedinCIVISproject.

2.2.3.3 CEDIS

CEDIS produces electricity using only renewable sources, it has the ownership of 3Hydropower plant (4.7MW) and 2 PV plants (0.8MW) connected to its own electric grid(Table3).



Table3Numberofplants(withinstalledpower)propertyofCEDISandconnectedtoitsownelectricgrid(2013)

Renewableenergysource

Numberofplants

InstalledPower(kW)

PV 2 826Hydropower 3 4,679Total 5 5,505

Thelocalelectricdistributiongridofmediumvoltage(MV)andlowvoltage(LV)isownedbyCEDIS. One MV interconnection point with the national grid ensure the continuous,bidirectional,exchangeofelectricitybetweenCEDIS localgridandnationalgrid.CEDISsellsexcessproductionandbuylackingelectricitywiththeregionalcompanycalledTrentaS.p.A.While the electrical production of CEDIS is 100% from renewable sources, electricitypurchasedfromthenationalgridpresentafractionof29.5%(year2013).CEDISestimatedfortheyear2013acost for the localelectricalgenerationonaverageequal to30€/MWh,buyelectricityfromTrentaS.p.Acostsonaverage66€/MWh.

AsCIVISprojectstakeholder,CEDIShasprovidedhourlydataofinjectionintothegridofitsownplantsaswellashourlydataofconsumptionfromgridofitsownmembers(year2013,Figure6).

Figure6ComparisonbetweenhourlyinjectionofCEDISplants(sx)andhourlyconsumptionof

CEDISmembers(dx).

The consumption and production outlooks are very similar to those of CEIS (similarcustomersandsimilarproduction technologies).Whileelectricityconsumptionshowssmall



variationsatmonthly level,electricity injectionshowsconsiderable fluctuations.Productionfrom hydro largely dominates the overall production in CEDIS and is dependent on directrainfall and snowmelt (usually reaching a pick in spring and in autumn).Moving to PV, itsproductionisdependentonthesolarradiation,withthehighestvaluesinsummer.

Theanalysisofgridbalancesneedsatleastanhourlydetail.Injectionprofilesarenotabletoobtainasuitablefittingwithconsumptionprofiles,thelattercharacterizedbyamorningpeakand an evening peak. Hydro injection is almost not regulated due to the absence of a realstoragebasin.Regulationactivitycouldn’tbeperformedalsoforPV.

In Figure 7 the electricty exchangeswith the national grid (import and exportwithTrentaS.p.A.)arequantifiedandanalyzed.Duringthereferenceyear2013CEDISimported2.2GWh(peakofimport2.2MW)andexported7.4GWh(peakofexport4.0MW).

Figure7CEDISel.grid:powerpurchasedfromNationalGrid(hourly,2013,sx)andpowersoldto

NationalGrid(hourly,2013,dx)

Same considerations of CEIS can be done also for CEDIS’s energy system characterization(high fraction of renewable energy production, production unpredictable and notprogrammable,clearproblemofenergybalancing)

This iswhyalso inCEDIS theToUsignalrepresentsan interestingsolution,workingon thedemandsideandpromotingthe loadshifting.This isthegoaloftheToUsignalproposedinCIVISproject.



2.2.4 ToU signals: time distribution of low signals

Asdescribedbefore,iftheelectricalenergybalanceispositive(consortiumoverproduction),thecorrespondingtime-intervalislabelledas“low”,otherwise(consortiumunderproduction)itislabelledas“high”.If.inonedaytherearelessthan3“lowintervals”theminimumvalueisreached,consideringaslowthelessoverproductivetimeslot.

Therefore, both in CEIS that in CEDIS, time distribution of “low signals” reflects the excessproduction.

InCEIS(Figure8),“lowsignals”intervalsareafewduringthewinterperiod(fromJanuarytoMarch), mainly allocated during the night 00:00 – 06:00 and during the midday (12:00 –15:00).InAprilthe“lowsignals”reachamaximumavailability(about50%),inthismonthitis verified an abundant overproduction fromHydro (mainly) and PV (secondly) resources.The most favourable periods are during the night 00:00 – 06:00 and during themidday/afternoon (12:00 – 18:00). In the following two months (May and June) the “lowsignal” availability remains frequent and allocated mainly during the midday/afternoon(12:00 – 18:00) and the night 03:00 – 06:00. In May and June gradually increases theinfluenceofPVproductionintheCEISenergybalances.

Figure8CEIS:timedistributionoflowsignals(2016,%oflowsignalsintheconsideredtime

slot)

%oflowsignals



MovingtoCEDIS(Figure9),“lowsignals”intervalsareafewduringthewinterperiod(fromJanuarytoFebruary),mainlyallocatedduringthenight00:00–06:00andduringthemidday(12:00–15:00).InMarchthe“lowsignals”availabilityincreases(over40%),inthismonthitis reached an abundant overproduction fromHydro (mainly) and PV (secondly) resources.The most favourable periods are during the night 00:00 – 06:00 and during themidday/afternoon (12:00 – 18:00). In the following threemonths (fromApril to June) the“low signal” availability remains frequent, reaching the peak in June. In April the mostfavourableallocationsareduringthemidday/afternoon(12:00–18:00)andthenight00:00–06:00;inMayandJuneduringthemidday(9:00–18:00).Inthelasttwoconsideredmonths(May and June) gradually increases the influence of PV production in the CEDIS energybalances(overproductionconcentratedduringthemidday).

Both inCEISand inCEDIS, considering thedemandprofilesof theirmembersand the timedistributionof the “low signals”, a demand shifting is requiredmoving theuse of electricalappliancesfrommorningandeveningtonightandmidday.

Figure9CEDIS:timedistributionoflowsignals(2016,%oflowsignalsintheconsideredtime

slot)

%oflowsignals



2.2.5 Analysis of the withdrawal profiles

The analysis of thewithdrawal profiles (electricity consumption from the grid) in the twoCIVISItaliancommunities(CEISandCEDIS)isdividedinananalysisofthe%ofwithdrawalshiftingandinananalysisofthe%ofwithdrawalin“lowsignal”.

However, at the time of writing this report, the lack of individual historical withdrawalprofilespreventsthecomparisonofeachuserwithhimself, ina“before”and“during”CIVISprojectforthesameperiodoftheyear.

2.2.5.1 CEIS

In Figure 10 it is represented the averagewithdrawal profile of CEIS participants in CIVISproject. This profile has a monthly variability due to seasonal lighting effects. As a wholemaintains a characteristic primary peak in the evening (around 18:00 – 20:00) and asecondarypeakinthemorning(around7:00–9:00).

Figure10AveragewithdrawalprofileofCEISparticipantsinCIVISproject(2016,%ofthedaily

consumptionfromgrid)

Adetailedanalysishasconsideredthepercentageofwithdrawalshiftingandthepercentageofwithdrawalin“lowsignal”,bothonanindividualandonaconsortiumscale.Indeed,itisnot

%ofdailyconsum

ptionfrom

grid



sufficienttoshifttheconsumptionbutthisshiftingshouldbedirectedto“lowintervals”.

Starting with the percentage of withdrawal shifting this is calculated comparing thepre-YouPower period (13/01/2016 – 10/03/2016) and the YouPower period(12/03/2016–24/06/2016).Forthepre-YouPowerperioditiscalculatedtheaveragedailyenergyprofile,inkWhandwith3-hourtimeintervals.IntheYouPowerperiodeachtimeslot(3h)iscomparedwiththeequivalenttimeslotintheaveragedailyenergyprofileofthepre-YouPowerperiod.Foreachmonththe%ofwithdrawalshifting(w.s.)iscalculatedas:

%𝑜𝑓𝑤. 𝑠. = 100

𝑚𝑜𝑛𝑡ℎ𝑙𝑦𝑔𝑟𝑖𝑑𝑒𝑙𝑐𝑜𝑛𝑠∗ (𝑔𝑟𝑖𝑑𝑒𝑙𝑐𝑜𝑛𝑠𝑡𝑖𝑚𝑒𝑠𝑙𝑜𝑡𝑌𝑃 − 𝑔𝑟𝑖𝑑𝑒𝑙𝑐𝑜𝑛𝑠𝑡𝑖𝑚𝑒𝑠𝑙𝑜𝑡𝑝𝑟𝑒𝑌𝑃)

IndividualresultsareshowninFigure11.CIVISparticipantsaredividedinuserswithoutPVanduserswithPV, ingreenusersregistered inYouPower. During theYouPowerperiod,atconsortiumscale(Table4),YouPowerusersdonotshowsignificanthighershiftingcomparedtotheotherusers.



Figure11Individualpercentageofwithdrawalshifting,ingreenYouPowerusersforthetotal

(TOT)trialperiod(Youpowerusersingreen,nonusersinblue)

Table4CEISpercentageofwithdrawalshifting

Moving to thepercentage of withdrawal in “low signal” (percentage of w. in ls), this is

USERID

USERID

%ofwithdrawalshifting %ofwithdrawalshifting



calculatedforeachmonth,intheYouPowerperiod(12/03/2016–24/06/2016),as:

%𝑜𝑓𝑤. 𝑖𝑛𝑙𝑠 = 100

𝑚𝑜𝑛𝑡ℎ𝑙𝑦𝑔𝑟𝑖𝑑𝑒𝑙𝑐𝑜𝑛𝑠 ∗ 𝑔𝑟𝑖𝑑𝑒𝑙𝑐𝑜𝑛𝑠𝑖𝑛𝑙𝑠

IndividualresultsareshowninFigure12CIVISparticipantsaredividedinuserswithoutPVanduserswithPV,ingreenusersregisteredinYouPower.DuringtheYouPowerperiod,atconsortium scale (Table 5), YouPower users show similar performance (- 1.7%)comparedtotheotherusersinthe“withoutPV”category,slightlybetter(+5%)inthe“withPV”category.

Figure12Individualpercentageofwithdrawalin“lowsignal”,ingreenYouPowerusersforthe

total(TOT)trailperiod(Youpowerusersingreen,non-usersinblue)

%ofwithdrawalin“lowsignal”

USERID

USERID




Table5CEISpercentageofwithdrawalin“lowsignal”

In summary with CEIS YouPower users do not show significant higher shiftingcompared to the other users. YouPower users show similar performance (- 1.7%)comparedtotheotherusersinthe“withoutPV”category,slightlybetter(+5%)inthe“withPV”category.

2.2.5.1 CEDIS

InFigure13 it is represented theaveragewithdrawalprofileofCEDISparticipants inCIVISproject. This profile has a monthly variability due to seasonal lighting effects. As a wholemaintains an evident peak in the evening (around 18:00 – 20:00) and a minimumconsumptioninthenightzone(22:00–5:00).ComparedtoCEISitisnotevidentasecondarypeakinthemorning,thisreflectthedifferenttypesofinvolvedCIVISusers,probablyduetodifferencesintheworklife.



Figure13AveragewithdrawalprofileofCEDISparticipantsinCIVISproject(2016,%ofthe

dailyconsumptionfromgrid)

As forCEISalso forCEDISadetailedanalysishas considered thepercentageofwithdrawalshifting and the percentage of withdrawal in “low signal”, both on an individual and on aconsortiumscale.Indeed,itisnotsufficienttoshifttheconsumptionbutthisshiftingshouldbedirectedto“lowintervals”.

Startingwiththepercentageofwithdrawalshifting, individualresultsareshowninFigure14 CIVIS participants are divided in users without PV and users with PV, in green usersregistered in YouPower. During the YouPower period, at consortium scale (Table 6),YouPowerusersdonotshowsignificanthighershiftingcomparedtotheotherusers.

%ofdailyconsum

ptionfrom

grid



Figure14Individualpercentageofwithdrawalshiftingfortotal(TOT)trialperiod,ingreen

YouPowerusers,nonusersinblue.

Table6CEDISpercentageofwithdrawalshifting

Movingtothepercentageofwithdrawalin“lowsignal”,individualresultsareshowninFigure

USERID

%ofwithdrawalshifting

USERID

%ofwithdrawalshifting



15. CIVIS participants are divided in users without PV and users with PV, in green usersregistered in YouPower. During the YouPower period, at consortium scale (Table 7),YouPower users show the same performance compared to the other users in the“withoutPV”category,slightlyworse(-8%)inthe“withPV”category.

Figure15Individualpercentageofwithdrawalin“lowsignal”,forthetotal(TOT)trialperiod

(Youpowerusersingreen,non-usersinblue)


USERID


USERID



Table7CEDISpercentageofwithdrawalin“lowsignal

In summary for CEDIS YouPower users do not show significant higher shiftingcomparedtotheotherusers.YouPowerusersshowthesameperformancecomparedtothe other users in the “without PV” category, slightlyworse (- 8%) in the “with PV”category

2.2.6Social acceptance of interventions and participants’ behaviours

TheYouPowerplatform (described inCIVISD.3.3) hasbeendeployed,while also aparallelprocess in support to households’ engagement started: the participatory energy budgetprocess.ThedescriptionoftheparticipatoryenergybudgetingprocesscanbefoundinCIVISD5.3,withadetailedanalysisoftheresults.

In this paragraph, we will discuss user’s attitudes and social acceptance connected to theinterventions carried out by CIVIS. We combine the data coming from the baselinequestionnaireandthetwoquestionnairesadministeredoneinMayandthefinaloneinJuly,andtheevaluationcomingfromtwofocusgroupsheldinJuly2016inCEISandCEdiSarea.



2.2.6.1 External motivations From the very beginning participants expressed concerns and attention to youngergenerationsandtheenvironment.Inthebaselinequestionnaire(seeCIVISD7.2)participantsdividedmostlyintwobetweentheonethatwanttodosomethingmorefortheenvironmentandtheonesatisfiedwiththeirenvironmentalbehaviours.Thisattitudecameoutalsoduringthe focus groups, where from one side participants described the investments and theirattitudetowardenvironment.Quotingaparticipant:“IusedPVpanelsfor20yearnow,Iwasoneofthefirst[…]Weareconvincedaboutthat,otherpeopleneedtounderstandit[…]BeforeIwasuneducatedaboutthosetopics,butnowIammoreawarebecauseIammoreawareoftheplanet,ofmyterritory…”.

This kind of attitude toward the environment and the energy is common with otherparticipantsof theproject, and thepro-environmentalmotivation is themainone forusingtheYouPowerappforrespondentsofthefirstquestionnaire(foradetailedanalysisseeCIVISD5.3).

2.2.6.2 ToU signals: social acceptance

Whether from the technical point of view the ToU signal intervention is interesting, itspotentialbenefitscanbeachievedonlyifitismanifestedasocialacceptability.

Theanalysisof theToUsignal social acceptance isbasedon thedata collected in theCIVISFinalQuestionnaire,performedintheItalianPilotSitesduringJuly2016.

TheCIVISFinalQuestionnairehasbeencompletedby55families,37inCEISareaand18inCEDISarea.Ofthese,areregisteredinYouPower18CEISfamilies(49%)and7CEDISfamilies(39%).

FortheYouPowerusers,afirstinvestigationconsiderstheusefulnessoftheToUsignals.Inascalefrom1(stronglydisagree)to5(totallyagree),ItalianfamiliesonaveragepartiallyagreethattheToUsignalisusefulforplanningactivitiesinvolvingtheenergyuse(CEIS3.2,CEDIS3.6)andforreducingelectricalconsumption(CEIS3.0,CEDIS3.1).However, difficulties to follow ToU signals are not negligible (Figure 16) the stronger arework life, family life and fixed habits. From this point of view, the low family engagementexpressedbyrespondentsitisanaddeddifficultytoshiftconsumptionwithoutchangingdaily



routinesorwithoutthehelpofdomotics,automationorstorage.Thelackoftechnologiesandthe difficulties to have a cooperationwith other familymembers has been pointed out byparticipantsasdifficulties:“atanindividuallevelwouldbeasolution,insteadof…atthefamilylevelwealreadyhaveenoughproblems,amoretechnologicalmanagement.Forexamplesomesmartstorage[…]”.

Figure16DifficultiestofollowToUsignals,inascalefrom1(notdifficultatall)to5(very

difficult)

A significant number of families declare to have shifted their electrical consumptionsfollowingToUsignals,inCEIS63%amongYouPowerusers,inCEDIS71%.

Shifted consumptions include washing machine, dishwasher, dryer and vacuum cleaner.These electrical appliances are consistent with the activities with higher shifting potentialidentifiedinCIVISd2.1b(washing,drying,dishwasherandwaterheating,representingabout22%ofthetotalelectricityconsumedinthedomesticsector).The usage of other appliances is perceived as non-shiftable,“it’s only the washing machine that can be [shift]… the fridge, the lights [not]… like the 90% of consumption” a user said during a focus group.

The presence of PV panels is a variable that create new motivation for shifting or for changing consumption behaviours and for increase cooperation within family members: participants with PV panels already pay attention about when use energy, quoting a user from a focus group: “[…]



sometimes with my wife we talk about it, and we try to exchange some opinion, mostly when there is the thing of the energy we produce, how to use it and not use together dishwasher and washing machine to not withdraw energy from the grid”.

Figure17Distribution(%)ofperceptionofamusementfollowingToUsignal

As shown in Figure 17, around 50% of respondents felt amusement trying to follow the ToU signal, but during July focus group during the discussion about the ToU and the platform participant expressed the willingness to have some kind of push notification instead of having to control the app continuously. They felt that their daily lives routine could be put under discussion, while with a push notification to be set when they are at home could be easy to adapt.

2.2.6.3 Energy Tips and Historical Data The main feature of YouPower for the Trentino test sites is Energy Weather, but theapplicationhasalsoothertwofeatures:EnergyTips,whichiscommonwiththeSwedishpartandthedatavisualizationpart.



Askedabout theEnergyTips sectionof theplatformrespondents to theMayquestionnaireexpressedageneralconsensusamongtheusefulnessofthisfeature,whilewhenaskedabouthowtheselecttheactionstotaketheyansweredthattheyselectthemfortheirimpact(Figure18).Thisisalsowhatemergedfromthefocusgroups,whereparticipantsexpressedageneralinterest for the tips and curiosity about environmental and energy savings behaviourunknownforthem.Quotingtwoparticipantsfromthetwofocusgroups:“onethingthatIdidnotdoandthatIwillhandtodo,it’stodefrostthingsinthefridge”,“therearesomesmalltipsliketonotwashdisheswithrunningwater[…]smallthingsbutifonedidnotknowaboutit.”

Figure18OpinionsaboutEnergyTipsfeature

A general usefulness and a help to increase energy awareness came also from the datavisualizationfeature,whereuserscanchecktheirconsumptionand/orproductionreal-timeor look at historical data Figure 19. Users tried to monitor their consumption in order tounderstand if savingsarepossibleandhow: “formehasbeenapositive things, if onenoticewhatheconsumes,hecanmakesomecalculations, liketodayIconsumedthatand lastweekIconsumedlessbecausemaybeIdidsomecalculationstoseeifIcouldsave”.



Figure19Opinionsaboutdatadisplayfeature

2.2.6.4 Gender and Energy The need of flexibility in order to follow the ToU signal motivated one third of therespondents’familymemberstotakecareofchoresusuallycarriedoutbysomeoneelse(seeFigure 20).Dishwasherandwashingmachinearethetwoappliancesthatareusedindifferenttimeandorbydifferentpeople.Weaskeddirectlyinthequestionnairewhichkindofchangeshappened:auserforinstancesaidthatthehusbandtookcareofthewashingmachineinsteadof thewife. But during the focus groups a gender gap emerged, in several occasions in thediscussioncameoutthatwomeninthehouseholdsare inchargeof thechores,whileat theopposite males are the one more interested in using the platform and “play” with thetechnology.



Figure 20 Family participation to consumption shifting

Maleparticipantsexplicitlystatedhowrolesinfamilyareclearlydefined,withthewifeasa“managerofthehouse”whichtakescareofchargingandprogrammingthestartofappliances,quotingaparticipant:“ifIneedtorepairthewashingmachineIcandoit,butstartingit’shardforme”.Participantstothefocusgroupsdiscussedhowtheytriedtomaketheirwivesmoreinterested or how they tried to teach how to use YouPower, but with few results inestablishingnewpracticeswithinthefamily.

2.2.6.5 Analysis of the electricity consumption & production

Concerningtheelectricityconsumption,afirstanalysisregardstothechangesintheelectricalappliancesequipmentduringCIVISproject.DatafromCIVISFinalQuestionnaireindicatethatboth in CEIS and in CEDIS about 17% of CIVIS families have replaced or installed newelectricalappliances,amongthemmanynewinstallationsconcerninductionhobsanddryers.(seeFigure21).

To the question: “Have you taken measures to reduce electricity consumption?” CIVIS



participantsforthemostpart,about60%,declare“yesasbefore”,agoodpercentage,about20%, “more thanbefore”andonlyabout20%“no”.CIVISparticipantshave therefore ingeneralapositiveattitudeforenergysaving(electricity)andCIVISprojectcontributedforabout20%ofthemtoimprovethisgoodenergybehaviour.

Figure21Resultsofthequestion“Haveyoutakenmeasurestoreduceelectricityconsumption?”



2.3 Results of electrical data analysis in Italian test site Inthefollowingsectionarediscussedtheresultsoftheelectricitydataanalysis inthetwoItalian communities (CEIS and CEDIS) with individual and consortium comparisonsbetweenCIVISperiod(01/07/2015–30/06/2016)andpre-CIVISperiod(consideringthree years and their trend). The electrical data analysis regards PV production, PVinjectionintogrid,PVself-consumption(%),electricalconsumptionfromgrid,totalelectricalconsumption (from grid and from PV self-consumption). Data are provided by the twoItalianDSO(CEISandCEDIS).

2.3.1 CEIS

PV production is generally higherwhen compared to 2014 (21/21 users, CEIS +6.8%) asshowninFigure22.Thisincreasingcanbeattributedtomorefavourableconditionsinsolarradiation.

ForthesamemotivationalsoPVinjectioninCEISgridisgenerallyhigherwhencomparedto2014(18/21users,CEIS+7.4%)asshowninFigure23.

PVself-consumption(%ofself-consumptionof thePVself-produced) is increasedfor11/21ofCEISuserscomparingto2014asshowninFigure24.ThepercentageofPVself-consumptioninCEISisstableataround28%.



Figure22PVproductionofCEISparticipantsinCIVISproject



Figure23PVinjectionintogridofCEISparticipantsinCIVISproject

Figure24PVself-consumption(%)ofCEISparticipantsinCIVISproject

InCIVIS,consideringthetrend2012-2014,electricityconsumptionfromgridisbelowthetrendforhalfofCEISusers(21/42),fortheotherhalfisabove.Inaggregateterms,fortheCEISconsortium, the trendduring the threeyears2012-2014suggests for theCIVISperiod(01/07/2015–30/06/2016)anexpectedincreaseof+5.5%(comparedto2014)asshowninFigure25.Therecordeddataindicateahigherincreasing,+16.1%.Thegeneralhighincreasein electricity consumption from grid is mostly due to the installation of new electricalappliances(dishwasher,dryer,electrichob,electricheater,ICT),supposedtobeparticularlyacceleratedintheperiod2014–2015/2016.

In CIVIS, considering the trend2012-2014, total electricity consumption (fromgrid andfrom PV self-consumption) is below the trend for half of CEIS users (21/42), for theotherhalf is above. Inaggregate terms, for theCEISconsortium, the trendduring the threeyears 2012-2014 suggests for the CIVIS period (01/07/2015 – 30/06/2016) an expectedincreaseof+4.6%(comparedto2014)asshowninFigure26.Therecordeddataindicateahigherincreasing,+14.6%.Thegeneralhighincreaseintotalelectricalconsumption(+14.6%



comparedto2014)ismostlyduetotheinstallationofnewelectricalappliances(dishwasher,dryer,electrichob,electricheater,ICT),supposedtobeparticularlyacceleratedintheperiod2014–2015/2016.

Figure25ElectricalconsumptionfromgridofCEISparticipantsinCIVISproject



Figure26TotalelectricalconsumptionfromgridofCEISparticipantsinCIVISproject

In Summary for CEIS PV self-consumption (% of self-consumption of the PV self-produced)isincreasedfor11/21ofCEISuserscomparingto2014andtotalelectricalconsumption(fromgridand fromPVself-consumption) isbelowthe trend forhalfofCEISusers(21/42).

2.3.2 CEDIS

PV production is generally higher when compared to 2013 (5/6 users, CEDIS +3.0 %) asshowninFigure27.Thisincreasingcanbeattributedtomorefavourableconditionsinsolarradiation.

PVinjectioninCEDISgrid,comparedto2013,increasedfor3/6usersanddecreasedfor3/6



users(overallCEDIS-1.3%)asshowninFigure28.

PVself-consumption(%ofself-consumptionofthePVself-produced)increasedfor4/6ofCEDISuserscomparingto2013asshowninFigure29.The%ofPVself-consumptioninCEDISisaround29%.

Figure27PVproductionofCEDISparticipantsinCIVISproject



Figure28PVinjectionintogridofCEDISparticipantsinCIVISproject

Figure29PVself-consumption(%)ofCEDISparticipantsinCIVISproject

InCIVIS,consideringthetrend2011-2013,electricityconsumptionfromgridisbelowthetrend for 15/23 of CEDIS users, for the other 8/23 is above as shown in Figure 30. Inaggregate terms, for the CEDIS consortium, the trend during the three years 2011-2013



suggestsfortheCIVISperiod(01/07/2015–30/06/2016)anexpectedincreaseof+24.3%(comparedto2013).Therecordeddataindicatealowerincreasing,+1.3%.

Figure30ElectricalconsumptionfromgridofCEDISparticipantsinCIVISproject

In CIVIS, considering the trend2011-2013, total electricity consumption (fromgrid andfromPV self-consumption) is below the trend for 14/23 of CEDIS users, for the other9/23 is above. In aggregate terms, for the CEDIS consortium, the trend during the threeyears 2011-2013 suggests for the CIVIS period (01/07/2015 – 30/06/2016) an expectedincreaseof+24.5%(comparedto2013)asshowninFigure31.

The recorded data indicate a lower increasing, +2.5 %. This is an important energysavingresultfortheCIVISperiod,areductionof-22%oftotalelectricityconsumptioncomparingtowhatexpectedbythehistoricaltrend,higherthanwhatexpectedinCIVISDoW(reductionpotentialintherangeof3-7%fortheenergyconsumption).



Figure31TotalelectricalconsumptionfromgridofCEDISparticipantsinCIVISproject

In Summary for CEDIS PV self-consumption (% of self-consumption of the PV self-produced) is increased for4/6ofCEDISusers comparing to2013and totalelectricalconsumption(fromgridandfromPVself-consumption)isbelowthetrendfor14/23ofCEDISusers.



2.4 Analysis of the thermal demand To the question: “Have youperformed actions to reduce energy consumption for heating?”CIVISparticipantsforthemostpart,about65%,declare“yesasbefore”,agoodpercentage,about 15 %, “more than before” and only about 20 % “no” as shown in Figure 32. CIVISparticipantshave therefore in general apositive attitude for energy saving (heating)and CIVIS project contributed for about 15% of them to improve this good energybehaviour.

Figure32Resultsofthequestion“Haveyoutakenmeasurestoreducespaceheating

consumption?”

Concerning a quantitative analysis for the thermal demand are not availablemetered data.Moreover,theconsumptiondatareportedbyCIVISusersintheBaselineQuestionnaireandintheFinalQuestionnairearenotconsideredsufficientlyreliableandaccurate.

What is evaluated in the following paragraphs is the behaviour of CIVIS users against astandardfortheindoortemperatureandaspaceheatingdemanddifferencecomparedtothatinthestandardconditions.

Temperaturedatacome fromCIVISsensors for theT indoorandMeteotrentinosensors forthe T outdoor. Data for the evaluation of the space heating demand (conduction losses,ventilation&draughtslosses,solargain,internalgains)comefromCIVISd7.2(CIVISBaselineQuestionnaire,regulations).



2.4.1 Outdoor temperatures in CEIS area and in CEDIS area

In CEIS the reference outdoor temperatures come from the weather station T0414 - SanLorenzo in Banale (Pergoletti). In Figure 33 the hourly values for the CIVIS period(01/07/2015–30/06/2016).

Figure33HourlyvaluesofToutdoorinCEISarea.WeatherstationT0414-SanLorenzoin

Banale(Pergoletti)

InTable8arecomparedmonthlydata fromMeteotrentino in theCIVISperiodandaveragemonthlydatafromPVGIS.

Table8MonthlyvaluesofToutdoorinCEISarea.WeatherstationT0414-SanLorenzoinBanale(Pergoletti)andPVGIS



InCEDISthereferenceoutdoortemperaturescomefromtheweatherstationT0393-Storo.InFigure34thehourlyvaluesfortheCIVISperiod(01/07/2015–30/06/2016).

Figure34HourlyvaluesofToutdoorinCEDISarea.WeatherstationT0393-Storo

InTable9arecomparedmonthlydata fromMeteotrentino in theCIVISperiodandaveragemonthlydatafromPVGIS.

Table9MonthlyvaluesofToutdoorinCEDISarea.WeatherstationT0393–StoroandPVGIS



2.4.2 Indoor temperatures in CEIS area and in CEDIS area

IndoortemperaturesareprovidedatanhourlyresolutionbyCIVISsensors.InItaly,50CIVISfamilies inCEIS area and29 inCEDIS area are equippedwithbuilding indoor temperaturesensors.Considering the winter period (October – April) monthly average temperatures for eachinvolvedfamily,bothinCEISandinCEDISarea,areillustratedinFigure35.

Figure35Monthlyaveragetemperaturesforeachinvolvedfamily(CEISandCEDIS)

Thedatashowthat in theCIVISwinterperiod(1October–30April),onaverage, thethermal behavior of CIVIS users, in the control of T indoor,meets the recommendedstandard value of 20°C. Indeed, at consortium level, in CEIS the average temperature is20.44°CandinCEDIS20.34°C.



2.4.3 Evaluation of overheating in CEIS area and in CEDIS area

Anadditionalanalysisconsiderstheconceptofoverheating.Thethermalstatusofabuildingis considered in overheating if the T indoor > 20°C during the daytime (5-23) and > 16°Cduringthenighttime(23-5),onlyifToutdoor<12°C(needofspaceheating).

The individual% of hours in overheating are illustrated in Figure 36.Monthly consortiumperformanceisreportedinTable10.Atconsortiumlevel,%hoursinoverheatingarelessinCEDIS(2.5%)thaninCEIS(15.2%).

Overall, in Italy, the use of temperature sensors andT indoor visualization helped agood control of spaceheatingdemand (SHdemand) inCIVISproject (only anoverall11.4%ofhoursinoverheating).

Table10Monthly%hoursinoverheatingforeachconsortium(CEISandCEDIS)duringCIVISperiod(01/07/2015–30/06/2016)



Figure36Percentagehoursinoverheatingforeachinvolvedfamily(CEISandCEDIS)during

CIVISperiod(01/07/2015–30/06/2016)

2.4.4 Space heating demand in CEIS area and in CEDIS area

Forthespaceheatingdemand it isevaluated,athourlyresolution,duringCIVISperiod ,andfor each CIVIS user, the % difference of the sum of demand for conduction (𝑄?) and forventilation & draughts (𝑄@) in the standard indoor temperature (20°C) and in the realmonitoredindoortemperature.

Inparticular,foreachhour:

𝑄? = 𝐻? ∗ (𝑇CD? − 𝑇EFG)

where𝐻?isthetransmissionheatexchange,individuallyevaluatedind7.2,𝑇CD?theoutdoortemperature (Meteotrentino),𝑇EFG the indoor temperature (20°C in the first case and realmonitoredindoortemperaturebyCIVISsensorsinthesecondcase).



𝑄@ = 𝐻@ ∗ (𝑇CD? − 𝑇EFG)

where𝐻@isthetransmissionheatexchange,individuallyevaluatedind7.2,𝑇CD?theoutdoortemperature (Meteotrentino),𝑇EFG the indoor temperature (20°C in the first case and realmonitoredindoortemperaturebyCIVISsensorsinthesecondcase).

Individual results of this comparison (standard vs real T indoor), during CIVIS period(01/07/2015–30/06/2016),arereportedinFigure37.

Figure37SpaceheatingdemandevaluationinCEISandCEDIS(standardvsrealTind)during

CIVISperiod(01/07/2015–30/06/2016)

Thedatashowthat, in theCIVISwinterperiod(1October–30April),onaveragethethermal behaviour of CIVIS users, in the control of space heating, meets therecommendedstandardvalues.MonthlyconsortiumperformanceisreportedinTable11(CEIS+4.2%SHdemand,CEDIS-1.6%SHdemand,CIVISITALY+2.3%).



Table11MonthlySHdemandevaluationinCEISandCEDIS(standardvsrealTind)duringCIVISperiod(01/07/2015–30/06/2016)



3 Evaluation of actions in Swedish Test site

3.1 Summary of actions carried out in Swedish Test site InHammarbySjöstad testbed, twousecaseswere implemented.The firstone is related tobuilding level energy efficiency and the creationof a social network around that,while thesecondone focusedon apartment-level energy efficiency. For the apartment level use case,theapphasbeendeployedintwohousingassociationsandtheSmappeekitsweredeployedin 27households, in order to get higher resolution consumption, data fromappliances andcontrolpossibilitiesthroughsmartplugs.

InFårdala testbed,10householdswereequippedwithSmappeekits inorder togethigherresolution electricity consumption data, obtaining data about appliances consumption andcontrolpossibilitiesthroughsmartplugs.Moreover,30householdswereequippedwithMaxEQ3 smart heating control systems,whichwill enable control of the heating systemby theusers.Figure38presentsandoverviewoftheactionscarriedoutintheSwedishtestsite.

Figure38SummaryofactionscarriedoutinSwedishTestsite



It is important to mention that; with the MAX EQ3 system the users can change thetemperatures insidethehousesusingthesmartphoneapporwebportal. Italsoallowstheusers to set temperature profiles thus enabling them to lower the temperature during thenightorwhentheyarenotathome.

3.2 Data collection and analysis In view of the abovementioned interventions, the following parameterwere collected andanalysedwiththepurposeofevaluatingtheCIVISmeasures.

• Heating(normalizedforweathervariations)andelectricitydataathousingassociationlevelinordertocorrelateditwithdifferentenergyefficiencymeasuresintroducedinthebuildingenergysystems.

• App usage and social data through focus groups and interviews with the energymanagersregardingtheimpactoftheCIVISplatform.

• Individualelectricityand(whereapplicable)hotwaterconsumptiondataathouseholdlevel.

• Smappee usage data, analysis of user’s interaction with the system and impactassessmentthroughinterviewsandfollowup.

• Individual heatingdata (normalized forweather variations) in order to evaluate theimpactofheatingcontrolthroughMAXeq3controlsystem.

• EvaluationofindoortemperatureprofilessetthroughMAXeq3controlsystem.• Analysisofuser’sinteractionwithMAXcontrolsystemthroughinterviewsandfollow

upwiththeusers

Basedontheabovedatacollected,evaluationmethodologieswereselectedtodeterminetheimpactofeachintervention.ThisissummarizedinTable12.



Table12OverviewofevaluationmethodologyforvariousinterventionsintheSweidishtestsiteIntervention RelevantParameter(s) EvaluationMethodologyVisualizationofhousingassociationlevelenergydataandenergymeasuresimplementedbyotherassociations.

• Heatingandelectricitydataincludinghistoricaldata.

• Measuresimplemented.• Qualitativeassessmentofsocialinteraction.

• Appusagedata.

• Comparisonbetweenhistoricaldataandconsumptiondataafterimplementationofmeasures(Afternormalization).

• Interviews/focusgroupswithenergymanagerstogaugetheimpact.

Visualizationofhouseholdlevelenergydataandenergytips.

• Electricityandhotwaterconsumptiondata.

• Appusagedata.

• Comparisonbetweenbaselineanddataafterdeployment.

• UserinteractionwithCIVISplatform

ControlandrealtimevisualizationofhouseholdelectricityandapplianceusagethroughSmappee.

• Electricityusagedata.• Followupwithusers• Smappeeusagedata


• Userinterviews/focusgroups

ControlofheatingsystemsthroughMAXeq3controlsystem.

• Heatingdata• Followupwithusers


Userinterviews/focusgroups



3.3 Hammarby Sjöstad Housing Associations Intervention InHammarbySjöstad,datafrom14housingassociationsasshowninTable13wasavailableandtheseweresubsequentlyinvitedtojointheCIVISappstartingfromOctober2015.Atthefinishof theproject8outof the14housingassociationshad joinedtheproject.Theenergymanagers of the housing associationwere given a run through of the app. Various energyactions carried out by the associationwere added to the app by energymanagers some oftheseactionsarelistedinTable14.Table13ListofBRFswheredatacollectionforCIVIStookplacewithCIVISusersmarkedby*BRF Area(m2) Apartments Constructionyear VentilationtypeÄlven* 8231 69 2003 FVPGrynnan* 10974 121 2004 FHolmen* 12914 114 2002 FTXSjöportalen1 8447 89 2003 FTXSjöstaden1* 16616 167 2003 FSjöstadsviken 8349 83 2007 FStrandkanten 3941 50 2004 FRedaren 8072 104 2008 FSicklaKanal* 7706 66 2002 FTXSeglatsen* 15692 137 2007 FVPSlusstornet 9186 82 2004 FBåtbyggaren1 13535 135 2008 F

HammarbyKanal* 4889 38 2002 FHammarbyEkbacke* 8405 60 2002 F

*PartoftheCIVISapp



Table14AsampleofenergyactionsenerterdbytheenergymanagersintheYouPowerapp.BRF Action Time

Älven Ventilationoptimization Aug-15

Grynnan Loweredventilationflowrateinthegarage Feb-13

Outdoorgroundheatingturnedoff Oct-12

Holmen None

Sjöstaden1 Roofinsulation May-15

Heatrecoveryheatpumpsforventilation Feb-16

SicklaKanal ElectricitymeteringinLaundry Jan-15

Seglatsen Heatrecoveryheatpumpsforventilation Oct-14

IndividualmeteringforDHW Nov-12

HammarbyKanal Ventilationoptimization

Sub-meteringforhotandcoldwaterconsumption

HammarbyEkbacke None

3.3.1 CIVIS app utilization

The primary focus of the CIVIS app (YouPower) in Hammarby Sjöstad was the energymanagersofthehousingassociations.Theappallowedtheenergymanagerstomonitortheirenergy use (heating and electricity), compare with previous year’s consumption and theaverageconsumption in theareaandaddenergyactionscarriedout inhousingassociation.Figure39presentsascreenshotoftheareapopulatedwiththehousingassociationdata.Interms of app usage two parameters the “cooperative actions expanded *(interaction withactions input by the energymanager) and “cooperative viewed” (interactionwith the pageshowingenergydataofcooperatives)ispresentedinFigure40.Sincethispartoftheappwasorientedprimarilytowardstheenergymanagers(8users),thegraphshowsalmostconsistentinteractionwith the app since deployment inNovember 2015 till August 2016. The periodbetweenJuneandJulyisholidayseasonandhencethenumbersareconsiderablylower.



Figure39ScreenshotoftheCIVISappinHammarbySjöstadpopulatedbytheactivehousingassociations.Thecolorsoftheassociationisbasedonascaleoftheirenergyconsumption.



Figure40YouPowerusagedatafortwoparameters;the“cooperativeactionsexpanded"and

“cooperativeviewed”(Nov2015-Aug2016)

3.3.2 Energy Analysis

Inordertocarryouttheenergyanalysisof thehousingassociationsenergyusetheheatingdata was normalized for both weather variations as well as for area. For weathernormalization, the methodology from the Swedish Metrological Agency was employed6.Temperature data for Stockholm from the Stockholm Environmental Administration7 wasused and degree days were subsequently calculated for the time period under study. ThedegreedaysarepresentedinTable15.6www.smhi.se7www.slb.nu



Table15DegreedaysforStockholmfor2013-2016comparedwiththe"NormalYear"degreedays.

2016 2015 2014 2013 NormalYear

January 657,9 499,3 572,1 628,6 519,2February 478,5 440,2 411,3 511 485,3March 428,3 406,7 387,8 581,6 546,6Quarter1 1564,7 1346,2 1371,2 1721,2 1551,1April 323,2 288,7 286,6 362,6 326,2May 126,2 211,7 196,6 119,8 250,8June 47,6 80,6 92,5 33,4 0Quarter2 497 581 575,7 515,8 660,8July 28,8 5,8 9,4 0August 1,3 40,4 12,7 32,6September 104,4 102 122,6 164,1Quarter3 134,5 148,2 144,7 221,7October 274,7 232,4 243,2 344,1November 359,4 344,2 379,3 416,8December 400,2 512 422,1 533,0Quarter4 1034,3 1088,6 1044,6 1293,9

Figure 41 presents the annual heating and hotwater consumption data obtained from theDSOandnormalized forweathervariationandarea foryears2012-2015.Data for theyear2016 being incomplete, the monthly data is presented later in Figure 43 and Figure 44.Similarly, Figure 42 presents the annual electricity consumption data for the housingassociations for the years 2012-2015. In this case, one challenge has been the ability toseparatethebuildingserviceselectricityfromthetotalelectricityconsumptioninsomecaseswherethehousingassociationspurchaseboththeelectricityforthehouseholdsaswellasthebuilding services electricity and the households are subsequently billed by the association.Therefore, in this case the electricity data for the housing associations Älven, Sjöstaden 1,Seglatsen and Sickla Kanal depicts the total electricity consumption while for the rest itdepicts only the building services electricity and the households purchase their ownelectricityfromtheDSO.FromFigure41andFigure42,housingassociationÄlven,GrynnanandSeglatsenwereableto



achieveconsiderablesavingsinheatingconsumptionwhileassociationsGrynnanandHolmenwere able to cut down on their electricity consumption. In case of Seglatsen therewas anincrease in electricity consumption due the installation of heat recovery heat pump. Theactionscarriedoutbytheassociationareanalysedfurtherbasedonthemonthlyconsumptiondata.

Figure41Normalizedannualheating&hotwaterconsumptiondataforCIVISusers(KWh/m2-

year)

Älven Grynnan Holmen Sjöstaden1 SicklaKanal Seglatsen HammarbyKanal

HammarbyEkbacke

2015 65,7 150,5 77,8 156,6 98,1 41,4 127,2 116,5

2014 63,3 148,8 75,8 153,3 96,2 80,4 125,8 115,7

2013 74,0 157,8 76,0 141,9 101,2 102,9 119,6 119,5

2012 72,6 159,7 74,3 135,1 110,2 101,5 123,1 112,8

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Figure42AnnualelectricityconsumptiondataforCIVISuserassociations(2012-2015)in

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Figure43andFigure44.presentthetotalmonthlyconsumptionforheatingandelectricity(inMWh) from January2014 toAugust 2016 to study the impact of the actions carriedout indetailsforsomeofthehousingassociations.• BRFÄlven:VentilationoptimizationwascarriedoutinAugust2015,howevertheenergy

usewentup.Thismotivationforcarryingouttheoptimizationwasissuesrelatedtolowerthermalcomfortandasaresultaslightincreaseinenergyconsumptioncanbenoticedinbothheatingandelectricity.

Älven Grynnan Holmen Sjöstaden1 SicklaKanal Seglatsen HammarbyKanal

HammarbyEkbacke

2015 54,4 26,1 32,1 48,2 51,2 56,8 30,3 16,8

2014 54,4 25,8 33,6 50,1 49,0 51,2 30,5 16,5

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• BRFGrynnan:Inthiscase,therearereductionsinheatingin2016duetoadjustmentsofventilationsystemaswellinelectricityduetoturningofftheoutdooricemeltingsystem.

• BRF Sjöstaden 1: In this association, extra insulation was added to the roof of thebuildingsinMay2015whichleadtoadecreaseinheatingconsumption.However,majorsavings were accomplished due to the installation of heat recovery heat pumps inFebruary 2016. This lead to some increase in electricity consumption but the overallimpactisprominentlypositive.

• BRF Seglatsen: This housing association accomplished the largest savings by installingrecoveryheatpumps inthebuilding,reducingtheheatingconsumptionbyaround60%.Overallconsideringtheriseinelectricityconsumptionthecostsavingsperyearamounttoabout40%ofthetotal.

• BRF Hammarby Kanal: was able to accomplish some savings based on ventilationoptimization.

• BRF Hammarby Ekbacke: Even though not mentioned in the actions in the app, thisassociation has been piloting “Goal based energy reduction” program with Dalkia forimproving the energy systemwith visible savings since the end of 2015. The programoffersanewbusinessmodeltothehousingassociationswherepartofthesavingsgoestothe ESCO for a fixed time period, while the housing association avoids having to payupfrontcostsfortheactions.



Figure43Monthlynormalizedheating(MWh)andelectricity(MWh)dataforhousing

associationsÄlven,Grynnan,HolmenandSjöstaden1for2014-2016

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Figure44Monthlynormalizedheating(MWh)andelectricity(MWh)dataforhousing

associationsSeglatsen,SicklaKanal,HammarbyKanalandHammarbyEkbackefor2014-2016

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3.4 Household Energy Visualization and Tips App in Hammarby Sjöstad

The CIVIS YouPower app for households was deployed in two housing association inHammarbySjöstad.InBRFSeglatsen,137householdswereinvitedtojointheprojectoutofwhich36householdssigneduptotheapp.InBRFGrynnan,121householdswereinvitedoutof which 10 households signed up. The data from 137 households in Seglatsen has beenmonitored for last13months inorder tostudy thepatternsofconsumption.Figure46andFigure 47 present the household electricity and domestic hot water consumption datacategorizedaccording to the sizeof theapartments.Onaverage theconsumption increasedwiththesizeof theapartments,however inthecaseof5roomapartments itwas lowerforelectricity than the 4 room apartments and for hot water all the rest. This anomaly wasinvestigated and the reasonwas itwas primarily householdswith older childrenwho hadalreadymovedoutoftheparents’housesleadingtoalowerconsumption.

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Electricity(KWh) 148,7 180,7 275,0 328,7 280,1Hotwater(m3) 1,8 1,6 2,4 3,0 1,3

Another interesting aspect visible in the datawas considerably higher consumption duringthewinterseason.This increasewassubstantiallyhigher thantheexpected increaseduetohigheruseoflightingduringthewinter.Oninvestigationthiswasattributedtotheuseoffloorheatinginthebathroomsinthelargerapartments.The app usage statistics for the household part are presented in Figure 45. Since thedeploymentinNovember2015theappusagewasconsiderablyhighwhichsubsequentspikesoccurringperiodically.TheappusagedatahasbeenfurtheranalysedinD5.3.



Figure45AppusagedataforhouseholdpartofYouPowerapp.



Figure46Min,MaxandMedianelectricityconsumptionin137apartmentsinBRFSeglatsen

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TheenergyconsumptionoftheusersforthehouseholdpartofYoupowerapparepresentedinFigure48andFigure49wheretheredhorizontallinesdepictingthetimeofdeployment.However,nodirectsavingsarevisibleintheenergydatainthecaseofBRFSeglatsenusers.Thisanalysisisfurthercomplicatedbutthelimitationofonly13monthsofdataavailabilityandthehighseasonalvariationofconsumption.Similarly,inthecaseoftheusersinGrynnanslightsavingsarevisibleinsomeoftheusers.

Figure48Electricityconsumptionprofiles(KWh)forYouPowerusersinBRFSeglatsenJune

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Figure49Electricityconsumptionprofiles(KWh)forYouPowerusersinBRFGrynnanJan2015-

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3.5 Smappee In total 27 households (10 in Fårdala and 17 in Hammarby Sjöstad) were equipped withsmartenergymonitors(SMAPPEE)toprovidehighresolution(5min)electricityusagedata.Thedevicerecognizesthemainappliancesinthehouseholdandallowstheuserslabelthemandkeeptrackoftheirconsumption.Additionally,eachhouseholdwasprovidedwith7smartplugsthatallowcontrolofappliancesremotely.The energy consumption data and interaction data for the households was analysed andfollow up interviewswere subsequently conducted to determine the impact of the system.Theconsumptiondata forhouseholds inFårdala ispresented inFigure50.Twohouseholdseventually dropped out of the study in February and April hence partial data is available.OverallinFrådala,someminorsavingswereobservedintheresults.

Figure50Smappeeusers'consumptiondatainFårdala(KWh)

InHammarbySjöstad, the results (as shown inFigure51were less clear andnoparticularpatternsemerged.However,someuserswereabletoachievesavingsduringthestudyperiod.The results can be further explained by studying the interaction data for the Smappeesinstalled.Forthispurpose,thenumberofapplianceslabelledandthenumberofsmartplugs

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inusebythehouseholdswasstudiedasshowninFigure52.Overall,fiveusersdidn’tmanagetolabelanyappliances,while6userswereabletolabelmorethan10appliances.Itmustbenotedthatthetotalnumberofappliancesshownheredoesn’trepresentthetotalappliancesat home, as Smappee at times treats for example each hot plate in the stove as a separateentity.Intermsofsmartplugs,8usersinstalled3ormoreplugs.

Figure51Smappeeusers’consumptiondatainHammarbySjöstad(KWh)

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Figure52No.ofappliancesdetected,labelledandnoofplugsinstalled.

3.5.1 Interview with Smappee users

InordertobetterunderstandthehouseholdsexperiencewithSmappee15interviewswereheldintotal,6inFardalaand9inHammarbySjostad.Onaverageeachinterviewlastedabout45minutessomeofthekeyfindingsofthestudyare:• Ingeneral,therespondentshadagoodinitialimpressionofSmappeeespeciallybecause

theycouldinstantaneouslymonitortheirconsumption.Someoftheuserswereconfusedabouthowthesystemworkedandhadsomefrustrationaboutlabellingtheappliances.

• OnethingthatalmostallparticipantshadincommonwasthattheysaidthatlabellingappliancesinSmappeewastoohard.5participantshadnoteventriedtolabelan

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applianceandoneofthemhadnotevenunderstoodthatSmappeewasabletodetectindividualappliances.2ofthe15participantshadlabelledoneappliancebutsaidthattheymadeamistakewhentheydidthat.Therestoftheparticipants(8ofthe15)hadtriedtolabelasmanyappliancesaspossiblebutstoppedwhentheyeithermadeamistakeorbecausetheyfeltthatitwastoohardorwhentheydidnotthinkitwasworthit.

• Userswhohadlabelledsomeappliancesdidthatduringthefirstcoupleofweeks.Theysaidthattheythoughtitwasfuntowalkaroundandhuntappliancesinthehouse.Buttheystoppeddoingthatlateron,eitherbecausetheyhadlabelledtheonesthatwereobvioustothem,orbecausetheythoughtitwas,ingeneral,toohardtocontinue.

• OnlytwooftheparticipantsusedSmappeeonaregularbasis,thetwoofthemuseditmanytimesaday.TheothershaduseditmanytimesaweekduringthefirstcoupleofweeksbutthenstartedtolookatSmappeemorerarely.

• Mostoftheparticipantsusedthemainscreen,wheretheirreal-timeconsumptionandtheiralways-onconsumptiondisplays,mostfrequently.Theylookedatthereal-timeconsumptioninordertogetanoverviewifeverythinglookscorrectaccordingtothem.

• TheplugsthataredeliveredwithSmappeewerenotusedthatfrequentlyinapartments.Acommonthoughtoftheuserswholiveinapartmentsisthattheyaremoresuitedforhouseswithtwofloors,whereyoucanturnthingsoffattheotherfloorandyouwillnothavetowalkalongdistancetodothat.

• Almostalloftheparticipantssaidthattheycouldnotchangethewaytheyusemostoftheirappliancessincetheappliancesfillapracticalpurpose.However,alittlebitlessthanhalfoftheparticipantshadinsomesmallwaychangedtheirconsumptionbehaviourduetoSmappee.



3.6 MAX Heating Control System Additionally,in30householdsasmartheatingcontrolsystemwasdeployedenablinguserstocontrol the indoortemperaturebyofferingcontrolofradiatorthermostatvalves(MAXeq3)through smart phone or web portal. The system also allows for collection of indoortemperaturesinthehouses.Figure53showsthetypicalinstallationconfigurationinFårdalawhereseveral thermostats/roomsaregroupedtogetherwith thewall thermostatandsomeroomssuchasstoragewereconfiguredindependentlytoallowflexibilityofuse.Theusersingeneral were consulted during the configuration process. The users can then set weeklytemperatureprofiles.The temperatureprofileshavebeenrecordedandarebeinganalysed.Figure 55 shows the analysis of indoor temperatures in different part of the house set byusersduringtheweekdaysandweekends.

Figure53TypicalinstallationconfigurationforMaxheatingcontrolsysteminFårdala.

TheinstallationoftheMaxsystemwascarriedoutstartingDecember2015.Theheatingdatafromthehouseholdswasnormalizedinordertomeasuretheimpact.Thedatawascomparedwith the normalized corresponding quarters data from previous years which served as abaselineforcomparison.ThedataforthehouseholdsispresentedinTable16.thetablehasbeendividedintothreeareasofFårdalaEken,VallenandTallenduetothedifferenceintypes



ofhouses.Figure54showsthepercentagechanceinenergyconsumptioninthehouseholdsforbothquartersafter installationofMax systemcompared to thebaseline.Overall for thefirstquarter8%savingsonaveragewereachievedwhileforthesecondquarteritwas17%onaverage.Insomecases,therewasanincreaseintheheatingconsumption.Thiswasduetothe fact that thehouseholdshadcompletelyshutoff theradiatorvalves insomepartof thehouseandduetoinstallingMaxtheseweresetaccordingtotheuniversalprofileschosenbytheusers.



Table16NormalizedheatingdataforQ1andQ22016alongwithcorrespondingaveragebaselines(KWh).

ID Year Quarter Heating Normalized Quarter Heating NormalizeE1 2016 1 4298 4261 2 568 755E1 AvgBL 1 3236 2 700 1189E2 2016 1 5964 5912 2 1676 2228E2 AvgBL 1 6384 2 2230 2547E3 2016 1 3539 3508 2 771 1025E3 AvgBL 1 3483 2 577 1026E4 2016 1 4783 4741 2 1812 2409E4 AvgBL 1 5011 2 2089 2315E5 2016 1 4510 4471 2 1444 1920E5 AvgBL 1 4761 2 1500 1783E6 2016 1 4555 4515 2 1392 1851E6 AvgBL 1 3910 2 1167 1643E7 2016 1 4180 4144 2 1999 2658E7 AvgBL 1 4243 2 1640 1753E8 2016 1 2406 2385 2 382 508E8 AvgBL 1 3298 2 1282 1521E9 2016 1 5020 4976 2 1223 1626E9 AvgBL 1 5600 2 1979 2354E10 2016 1 3229 3201 2 626 832E10 AvgBL 1 3211 2 889 1163E11 2016 1 4184 4148 2 1004 1335E11 AvgBL 1 5269 2 2154 2337V1 2016 1 9105 9026 2 2646 3518V1 AvgBL 1 9535 2 3502 3496V2 2016 1 7480 7415 2 1862 2476V2 AvgBL 1 6880 2 1738 2163V3 2016 1 7717 7650 2 2176 2893V3 AvgBL 1 7748 2 2482 2965V4 2016 1 6705 6647 2 1952 2595V4 AvgBL 1 7307 2 1631 2252V5 2016 1 5807 5757 2 1855 2466V5 AvgBL 1 7562 2 1682 2328T1 2016 1 5265 5219 2 1309 1740T1 AvgBL 1 5547 2 1864 2160T2 2016 1 4247 4210 2 1021 1357T2 AvgBL 1 4135 2 1859 1995T3 2016 1 4199 4162 2 799 1062T3 AvgBL 1 5149 2 1958 2131T4 2016 1 3343 3314 2 463 616T4 AvgBL 1 4063 2 1343 1288T5 2016 1 4661 4620 2 1142 1518T5 AvgBL 1 4964 2 1647 1846T6 2016 1 3460 3430 2 458 609T6 AvgBL 1 3564 2 453 1070T7 2016 1 3772 3739 2 807 1073T7 AvgBL 1 4329 2 1158 1595T8 2016 1 4808 4766 2 1422 1891T8 AvgBL 1 5088 2 1907 2432T9 2016 1 3417 3387 2 556 739T9 AvgBL 1 4375 2 1700 1638



Figure54PercentagechangeinconsumptioncomparedtobaselineforMaxusersinFårdala

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Figure55Average,minandmaxtemperatureprofilesforindoortemperatures(DegreeC)forMaxusersinFårdala



3.6.1 Max survey results

A survey was conducted in order to study the perception of users about the system. Thesurveywasansweredby13users.ThehighlightsofsomeoftheresultsareshowninFigure56-Figure62.ThesurveyisdiscussedinfurtherdetailinDeliverable5.3.Overall,thegeneralimpressionof the systemwaspositivewithover75%respondentsansweringgoodorverygood. In termsof levelofdifficultyofusing thesystem6users found itsatisfactorywhile6found it simpleor very simple touse. In termsof initial expectations, 76%expressed theirsatisfaction with the system while about 85% of the respondents used it to lower thetemperatures that aren’t frequentlyusedand for setting scheduling function forwhen theyarenothomeorasleeptolowerthetemperature.About60%oftheusersinteractedwiththesystem frequently and themain formof interactionwas through the smartphoneapp.TheresultsfromthesurveyarefurtherdiscussedinD5.3.

Figure56OverallimpressionoftheMaxusers(1)verybadto(5)verygood



Figure57Levelofdifficultyofusefrom(1)verydifficultto(5)verysimple

Figure58Frequencyofinteractionwiththesystemfrom(1)neverto(5)veryoften

Figure59Modeofinteractionwiththesystem.



Figure60Satisfactionlevelofusers.

Figure61Percentageofusersthatloweredthetemperatureislessfrequentlyusedrooms.

Figure62Percentageofusersthatusedtheschedulingfunction.



4 CONCLUSION

ThemainobjectiveofWP7hasbeen to test theeffects, in termsofreducedenergyuseandreduced CO2 emissions, of the technology proposed within the CIVIS project, by runningextensive real-life evaluation tests on the two pilot sites. The following objectives areidentified:

• Tomeasure the reductionof energy consumptionandofCO2emissions through theintroductionoftheCIVISICTplatform.

• Toanalysethesocialandeconomicdriversforthesuccess(orfailure)ofthemeasures.

This sectionprovidesa summaryof the findings relating to theseobjectives foreachof thetwopilotsites,followedbygeneralconclusionsandimplicationsfromtheworkpackage.

TheoverallimpactintheStockholmtestsitecanbesummarizedas:

• Thehousingassociationaspectoftheprojectwasquitesuccessfulinachievingimpact.The initiative was highly appreciated by the various stakeholders and varioussuggestionsweremade in order to improve and continue theprocess.As a result, acontinuationproject fundedby the SwedishEnergyAgencywas launched to expandthe work in this area with a goal of recruiting 100 housing associations. Furtherdevelopmentoftheplatformforthataspectisongoingandvariousstakeholdershavebeen engaged in the process. It must be noted here that at the housing associationlevel, the calculating the impact of such a project in terms of kWh reductions ischallengingsince thedecision-makingprocessesareusuallyveryslowand formajoractionscantakeseveralyears.

• At the household level, various challenges became obvious in terms of engaging theusersandchangingtheirbehaviour.Themonetarysavingspotentialinmostcaseswasnotsubstantialenoughtoengagetheusersina longtermshift.Thiswasparticularlyobvious in Hammarby Sjöstad which has a higher average income compared to theStockholmaverage.Additionally, insomecasescompetingappswereavailabletotheusers from the DSOwith visualizations of energy use, whichmay have affected theuptake.

• ForSmappeeintervention,mostoftheusersfoundthesystemcomplexandhencethe



full potentialwasnot utilized. It didmanage to engage theusers initiallywith someusersmoreinterestedintheadvancedfunctionalitiesthantheothers.

• TheMaxinterventioninFårdalawassuccessfuloverall.Thethree-monthbillingcyclemayhaveaffectedthefullutilizationofpotentialsincetheuserscouldn’tdirectlyseetheimpactontheirenergyuse.ThisleadtothehousingassociationinvestinginanICTplatformwhichwill bedeployedby the endof theyear andwill enable theusers toviewtheirconsumptionatahigherresolution.

SummaryofItalianresults:

• Themain findings in termsof energy impacts for theToUsignals implemented inStoroandSanLorenzoshowedthatstatisticallysignificantresultsforshiftingenergyusedidnotemerge; the small sample size surely contributed to this.However, findings did suggestthat PV owners were both more engaged with the ToU signals on YouPower and alsoslightlymoresuccessfulinfollowingthem(CEDIS).

• PVself-consumption(%ofself-consumptionofthePVelectricity)increasedfor11/21ofCEISuserscomparingto2014andfor4/6ofCEDISuserscomparedto2013.

• Overall, in Italy, the use of temperature sensors and indoor temperature visualizationhelpedagoodcontrolofspaceheatingdemand(SHdemand)intheCIVISproject(onlyanoverall11.4%ofhoursofoverheating).ThedatashowsthatintheCIVISwinterperiod(1October–30April),onaverage,thethermalbehaviourofCIVISusersinthecontrolofTindoor,meetstherecommendedstandardvalueof20°C.

Conclusionsandoutlook:

• Interventions demonstrated the feasibility of user engagement though betterinformationonenergyusagepatterns.

• Mostifnotalloftheseinterventionsexhibitscalability,whichmeanstheycaneasilybetransferredtoothercontexts.

• Ingeneral,themostsuccessfulaspectsofCIVISinterventionsinvolvedmultiplierssuchasHousingAssociationsorLocalAuthorities



• Significant challenges were faced in terms of data availability and timing of theinterventions, which should be addressed in future trials. Ideally, there should be atime lag between interventions and monitoring, and before and after data, over aperiodofseveralyears,arerequired.

• Inaddition,samplesizesandcompositionsshouldberepresentativelychoseninorderto obtain statistically significant results; this should be borne in mind for futureprojects.

• Often monetary savings alone were not enough to motivate users to change theirbehaviour,whichconfirmsfindingsonbarriers,marketfailuresandthereboundeffectfromtheliterature.

• WhilsttherolloutofsmartinterfacesandappswassuccessfullyachievedinthecontextofCIVIS,theimplementationofa“socialnetworkforenergy”,i.e.theCIVISvisionwasnotcompletelyachieved.

• This goal couldbepursued in futureprojects inorder toovercomeexistingbarriersandappealtootherincentivesthanpurelyeconomic.

Intermsofoverallquantitativeimpactofsocialaspectsonenergyconsumption,thishasbeendifficulttodetermineincertaincasesduetolimitedmonitoringtimeandpartialavailabilityofhistoricaldata.Inthiscaseacomparisonsuchasbetweenatestgroupandacontrolgroupofuserscannotbeaccuratelymadeduetotheinabilitytoisolatetheimpactofinterventionsinan open socio-technical system. The quantitative evaluations/comparisons were therefore,wherenecessary, supportedby variousqualitativemethodologies such as interviews, focusgroupsandsurveys.Onemajorchallengetowardsquantificationoftheresultswasthelackofhigh quality datawhich had to be supported by the installation of additional sensors (notoriginally envisaged in the project), thus leading to shorter evaluation periods. In order tofullydeterminetheimpactofsocialrelatedmeasuresonenergyconsumption, longerperiodof energydata collection aswell asmoredetailedmonitoring of energybehaviour throughhigherlevelofuserengagementoradditionaltrackingthroughapps/sensorsofusers’actionsneedtobecarriedout.Thisisparticularlyimportanttoevaluatelongtermbehaviourchangesandtheimpactofreboundeffects.

Documents

Deliverable D7.3 Final Evaluation report · Document Title Final Evaluation report Version 1 Status Resubmission Work Package WP7 Deliverable Type R1 Contractual Date of delivery