Seite - 182 - in 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
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