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Emerging Technologies for Electric and Hybrid Vehicles
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Energies 2016,9, 270 model to address budget limitations and tomaximize the number of peoplewho can complete round-trip itineraries. Yao et al. [36]developedamulti-objectivecollaborativeplanningstrategy to address theoptimalplanning issue in integratedpowerdistribution andEVcharging systems, in which theoverall annual costof investmentandenergy lossesareminimizedsimultaneouslywith maximizationoftheannualtrafficflowcapturedbyfastchargingstations(FCSs).Anequilibrium-based traffic assignmentmodel and decomposition-basedmulti-objective evolutionary algorithmwere developedforobtainingtheoptimalsolution. Sadeghi etal. [37]presentedaMixed-IntegerNon-Linear (MINLP)optimizationapproachfor theoptimalplacementandsizingof fast chargingstations,which consideredthestationdevelopmentcost,EVenergyloss,andelectricgirdlossaswellas the locationof electric substationsandurbanroads.Chung et al. [38] formulatedamulti-periodoptimizationmodel basedonaflow-refueling locationmodel for strategicchargingstation locationplanning,andthen developedacasestudybasedonthereal trafficflowdataof theKoreanExpresswaynetwork in2011. Afteranalyzingthe literature, it canbeconcludedthat themajorityofexistingstudies relatedto theoptimalsitingofEVCSsareconcentratedonMulti-ObjectiveDecisionMaking(MODM)methods, suchas linear/nonlinearprogramming,stochasticprogramming,mixed-integerprogrammingand multilayerprogramming. Inmostcases,heuristicalgorithmssuchasGAandPSOwereapplied to tackle theoptimal solution. However, thereare twomajor critiqueswithsuchMODMapproaches. First, althoughtheaforementionedoptimizationmodelsare remarkable it is less likely theycanbe implementedinpracticeduetothecomplexityofmodelingreal-worldproblems. Second,optimization modelscanonlyaccount forquantitativevariablessuchasconstructioncostandrunningcost, electric grid loss,EVenergylossandsoon,butarenotcapableofmodeling importantqualitativevariables suchasecologicalenvironment (e.g.,deteriorationonsoilandvegetation), etc. In view of this, herein another kind of decision-making method, i.e., the Multiple-Criteria Decision-Makingmethodwillbeemployedtodetermine theoptimalsiteofelectricvehiclecharging stationsfromanextendedsustainabilityperspective. TheMCDMmethodcancomprehensivelycapture thequantitativeandqualitativecriteria thatbothplay important roles inEVCSsiteselection. Themain contributionsof thispaperareas follows: (1) This is thefirst studythat involvesbothquantitativeandqualitativecriteria forEVCSsiting from anextendedsustainabilityperspective,whichovercomes thedefectsof traditionalmathematical programminginaddressingqualitativebutnevertheless important factors. (2) The conventional concept of sustainability is improved through integrating the issues of technology, namelyeconomy, society, environment and technologyperspectives,whichhave notbeenconsideredinpreviousstudies. In thisstudy, the initial criteriaareestablishedbased onextendedsustainability. Furthermore, toobtain themost reliableconsensusamongagroup of experts in a shorter time, FDM is employed to determine the final sub-criteria for EVCS siteselection. (3) ThefuzzyVIKORmethod,whichshowsgoodperformanceinthedecision-makingofalternatives selection,hasbeenapplied inmanyfields. Tothebestofourknowledge, this isanovelhybrid MCDMtechniquebasedoncombinationweightsandfuzzyGRA-VIKORfor theoptimalsitingof EVCSs,whichalsoextends theapplicationdomainsof the fuzzyVIKORmethod. Theproposed modeladdresses the fuzzinessanduncertaintyofsubjective factorsandhumanjudgment,and additionally it considers subjective andobjective informationwithin theweights calculation process.Moreover,GRAareusedtomeasurethedistancesoffuzzynumbersbetweenalternatives to ideal solutions in this study,whichcanbettermeasure thedistancebetweenfuzzynumbersas wellasprovidearankingorderofalternativeswithprecisenumbers. (4) Sinceexpertswithvariousknowledgebackgroundsmayhavedifferentprioritiesas theirmain objective, it isessential toprobethe impactsofsub-criteriaweightsonthefinalresults. Thisstudy is thefirstpaper toresearchtheeconomy,society,environmentandtechnologyperspectives for optimalsitingofEVCSsbychangingthesub-criteriaweights. 182
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Emerging Technologies for Electric and Hybrid Vehicles
Titel
Emerging Technologies for Electric and Hybrid Vehicles
Herausgeber
MDPI
Ort
Basel
Datum
2017
Sprache
englisch
Lizenz
CC BY-NC-ND 4.0
ISBN
978-3-03897-191-7
Abmessungen
17.0 x 24.4 cm
Seiten
376
Schlagwörter
electric vehicle, plug-in hybrid electric vehicle (PHEV), energy sources, energy management strategy, energy-storage system, charging technologies, control algorithms, battery, operating scenario, wireless power transfer (WPT)
Kategorie
Technik
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Emerging Technologies for Electric and Hybrid Vehicles