Page - 201 - in Emerging Technologies for Electric and Hybrid Vehicles

energies Article RobustPeak-ShavingforaNeighborhoodwith ElectricVehicles MarcoE.T.Gerards*andJohannL.Hurink FacultyofElectricalEngineering,MathematicsandComputerScience,7500AEEnschede,TheNetherlands; j.l.hurink@utwente.nl * Correspondence:m.e.t.gerards@utwente.nl;Tel.: +31-53-489-4896 AcademicEditor:ChunhuaLiu Received: 4May2016;Accepted: 21 July2016;Published: 28 July2016 Abstract: DemandSideManagement (DSM) is apopular approach for grid-awarepeak-shaving. Themost commonly usedDSMmethods either have no look ahead feature and risk deploying flexibility too early, or theyplan aheadusingpredictions,which are in general not very reliable. To counter this, aDSMapproach is presented that does not rely ondetailed power predictions, butonlyusesa feweasytopredict characteristics. Byusingthesecharacteristicsalone,nearoptimal results can be achieved for electric vehicle (EV) charging, and a boundon themaximal relative deviation isgiven. This result is extended toanalgorithmthat controls agroupofEVssuch that a transformerpeak isavoided,whilesimultaneouslykeepingthe individualhouseprofilesasflatas possibletoavoidcableoverloadingandforimprovedpowerquality. Thisapproachisevaluatedusing differentdatasets tocompare theresultswith thestate-of-the-art research. Theevaluationshowsthat thepresentedapproachiscapableofpeak-shavingatthetransformerlevel,whilekeepingthevoltages wellwithin legalbounds,keepingthecable loadlowandobtaining lowlosses. Furtheradvantages of themethodologyarea lowcommunicationoverhead, lowcomputational requirementsandease of implementation. Keywords: adaptivescheduling;demandsidemanagement;electricvehicles;optimalscheduling; smartgrids 1. Introduction In the future, we expect an increasing penetration of electric vehicles, photovoltaic panels, heatpumpsandwindturbines.Asespeciallyheatpumpsandelectricvehiclescreaterelatively large andsynchronizedpeaks,oftenat timeswhenthere is little renewableenergyavailable, thebalance betweenproductionandconsumptionofelectricitybecomesmoreandmoreanurgent issue. To counter the problems that arise due to this trend (for a survey, see [1]), Demand Side Management (DSM) techniques can be deployed to prevent peaks. Here, DSM is the collective termforasetof techniquesthatcontrol theproductionorconsumptionwithinthecustomers’premises. Acentralentity (e.g., thenetworkoperator) requestscustomers,viaasteeringsignal, toadapt their production or consumption in order to shape the load profile of a certain subgroup of the grid (e.g., agroupofhouses). Thesecustomerscaneitheradapt theirbehaviormanually,or install adevice that is referredtoasaHomeEnergyManagementSystem(HEMS),whichmakessuchdecisionson theirbehalf. In the latter situation, theHEMSshouldstartappliances (referredtoassmartappliances) whentheconsumptionshouldbe increased,orshouldadvanceordelay theuseofsuchanappliance whentheconsumptionshouldbedecreased. Inaddition,energystorage (e.g., batteries) canbeusedto mitigateasurplusof renewableenergybycharging,andapeakintheconsumptionbydischarging. In thisarticle,wefocusonelectricvehiclesas they introducebothasignificant load,andprovidea lot offlexibility. Energies 2016,9, 594;doi:10.3390/en9080594 www.mdpi.com/journal/energies201