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Energies 2016,9, 270
examinetherationalityandstabilityof theproposedframeworkandanalysis results, thesensitivity
analysisofνvalueandsub-criteriaweightsarepresented.
Table6showsthat thesub-criteriaC9andC10affiliatedwith theenvironmentalaspectobtain
muchmore attention from the expert group, which reflects the strategy and energy saving and
environmentprotectiongoalsof theChinesegovernment.Meanwhile, thesub-criteriaaffiliatedwith
economicdevelopment are not so important as before,which is consistentwith thedevelopment
goalsofChina.Asweallknow, inrecentyears, transportationandelectricity industryhassuffered
pressuresandchallenges fromthe“twelfthfive-year”planandtheenvironmentalprotection lawof
China,which indicates theresponsibilityandtargetof these industries forenvironmentprotection.
Moreover, thesevereenvironmentandresource issueshaveposedundesirableconditions tohumans
for living. Therefore, theenvironmentalaspecthasbeengivenmoreconsiderationbyexperts for the
optimalsitingforEVCSs inChina.
Asmentionedabove, this studyuses thevariationofvvalues todemonstrate thatallof themdo
notaffect theanalysis results (Figure4). Thevvaluesarepostulatedtochangefrom0.1 to0.9,while
therankingordersoffiveEVCSsaresame,namelyA3>A5>A2>A1>A4.Andthus, this studycan
confirmthat theresultsobtainedbyusingtheproposedmodelarereliableandeffective.
Figure4.Sensitivityanalysisofvvalue foreachalternative.
Next, a sensitivity analysis on the impacts of sub-criteriaweights for optimal EVCS siting is
presented, soas toobtainbetter insightofevaluationresultsandverify therobustnessofevaluation
results.Accordingto thecriteria, thirteensub-criteriaaredividedinto fouranalysisaspects,namely
economy,society,environmentandtechnology.All sub-criteriahave10%,20%and30%lessweight
thanthebaseweightand10%,20%and30%moreweight thanthebaseweight (allbaseweightsare
showninTable6).
It canbeseenthat inFigure5, theQiofA5andA1decreasewhenthesub-criterionC1becomes
less important. TheQiofA2increaseswhentheweightofC1becomesmore important,andit ranks
fourth, surpassedbyA1.However,nomatterhowtheC1weightchanges, theQiofA3alwayshas the
lowest score, indicating thebestalternative.AsC2 isgivenmore importance,only theQiofA2shows
asmall rising tendency,while the scoresofotheralternatives remain relatively stablealthoughC2
carries largeweight in theoptimalEVCSsiting. In thecaseofC3, theQiofA1andA5dramaticallyrise
alongwithweight increase,whichgetscloser to thatofA4andA2, respectively.A3andA4arestill the
optimalandworst sites thesameas in thebasecase.Apparently,C1andC3aresensiblesub-criteria
whichdramaticallyaffect theoptimalEVCSsitingresults.However,nomatterhowtheweights in the
economygroupchange,A3 isalways thebestchoice in theoptimalsitingofEVCSinTianjin.
195
Emerging Technologies for Electric and Hybrid Vehicles
- Title
- Emerging Technologies for Electric and Hybrid Vehicles
- Editor
- MDPI
- Location
- Basel
- Date
- 2017
- Language
- English
- License
- CC BY-NC-ND 4.0
- ISBN
- 978-3-03897-191-7
- Size
- 17.0 x 24.4 cm
- Pages
- 376
- Keywords
- 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)
- Category
- Technik