A data-driven approach for characterising the charging demand of electric vehicles: A UK case study

Applied Energy

Volumn 162, Issue , 2016, Pages 763-771

  Xydas, Erotokritos ^a   Marmaras, Charalampos ^a   Cipcigan, Liana M ^a   Jenkins, Nick ^a   Carroll, Steve ^b   Barker, Myles ^b  

^a CARDIFF UNIVERSITY   (United Kingdom)

^b LOUGHBOROUGH UNIVERSITY   (United Kingdom)

Author keywords

Characterisation model; Data analysis; Data mining; Electric vehicles charging events

Indexed keywords

CHARGING (BATTERIES); CRASHWORTHINESS; DATA REDUCTION; ELECTRIC VEHICLES; VEHICLES;

CHARGING DEMANDS; DATA MINING MODELS; DATA-DRIVEN APPROACH; ELECTRIC VEHICLE CHARGING; FUZZY-BASED MODELS; GEOGRAPHICAL AREA; LOW EMISSION VEHICLES; MODELLING FRAMEWORK;

DATA MINING;

DATA ACQUISITION; DATA MINING; DEMAND ANALYSIS; DISTRIBUTION SYSTEM; ELECTRIC VEHICLE; FUZZY MATHEMATICS; TRAFFIC EMISSION;

UNITED KINGDOM;

EID: 84946615957     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2015.10.151     Document Type: Article

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