Widespread adoption of electric vehicles (EVs) relies on a dependable public charging station (CS) network. CS locations should assure that vehicle users can reach the CS within the EV driving area. This study introduces a technique for optimal location and sizing of fast CSs (FCSs) that considers transportation loss, grid power loss and build-up costs. Google Maps API, battery state of charge, road traffic density and grid power losses are considered in the suggested method. A recently introduced binary lightning search algorithm is also implemented as an optimisation technique for FCS planning. The capability of the suggested method was tested in an urban area. Results reveal that the suggested technique can obtain the optimal location and sizing of FCS that can aid EV drivers, FCS builders and the utility grid. Furthermore, the suggested method obtained more realistic results compared with the traditional methods.
Optimal location and sizing of fast charging stations for electric vehicles by incorporating traffic and power networks
IET Intelligent Transport Systems ; 12 , 8 ; 947-957
2018-08-08
11 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
FCS planning , public charging station network , electric vehicle charging , power networks , optimal sizing , application program interfaces , build-up costs , traffic networks , EV driving area , optimisation technique , road traffic , optimal location , fast charging stations , binary lightning search algorithm , road traffic density , Google Maps API , battery state-of-charge , utility grid , transportation loss , grid power losses , electric vehicles , battery powered vehicles , search problems , power grids , optimisation , mobile computing , cartography , power engineering computing
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