Open AccessHierarchical optimal planning approach for plug‐in electric vehicle fast charging stations based on temporal‐SoC charging demand characterisation
Author(s) -
Sun Siyang,
Yang Qiang,
Yan Wenjun
Publication year - 2018
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2017.1894
Subject(s) - sizing , computer science , charging station , electric vehicle , state of charge , automotive engineering , queueing theory , plug in , simulation , operations research , engineering , battery (electricity) , computer network , power (physics) , physics , quantum mechanics , programming language , art , visual arts
Fast charging stations are critical infrastructures to enable a high penetration level of plug‐in electric vehicles (PEVs) into future distribution networks. The fast charging stations need to be carefully planned to meet the PEV charging demand as well as reduce costs. This study addresses this technical challenge and proposes a hierarchical planning solution for both sitting and sizing of PEV fast charging stations based on a temporal‐SoC (state‐of‐charge) characterisation and modelling of PEV fast charging demand. The optimal sitting of fast charging stations is firstly determined to ensure minimising the total number of stations and meeting the PEV fast charging demand considering the constraints of transportation networks and the expected PEV remaining mileage. Then the sizing (number of chargers and waiting spaces) of fast charging station is optimised by the use of M/M/s/N queuing model, so as to maximise the expected profit of the operator. The proposed solution is evaluated through a set of case studies for a range of scenarios, and numerical simulation results have confirmed the effectiveness of the proposed solution.