@ARTICLE{ iet:/content/journals/10.1049/iet-its.2018.5136, author = {Md. Mainul Islam}, author = {Hussain Shareef}, author = {Azah Mohamed}, keywords = {FCS planning;traffic networks;optimisation technique;Google Maps API;road traffic density;build-up costs;fast charging stations;battery state-of-charge;transportation loss;grid power losses;power networks;EV driving area;optimal location;electric vehicles;optimal sizing;utility grid;public charging station network;binary lightning search algorithm;}, ISSN = {1751-956X}, language = {English}, abstract = {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.}, title = {Optimal location and sizing of fast charging stations for electric vehicles by incorporating traffic and power networks}, journal = {IET Intelligent Transport Systems}, issue = {8}, volume = {12}, year = {2018}, month = {October}, pages = {947-957(10)}, publisher ={Institution of Engineering and Technology}, copyright = {© The Institution of Engineering and Technology}, url = {https://digital-library.theiet.org/;jsessionid=16dwvlw931bcb.x-iet-live-01content/journals/10.1049/iet-its.2018.5136} }