4.4 Article

Hierarchical optimal planning approach for plug-in electric vehicle fast charging stations based on temporal-SoC charging demand characterisation

Journal

IET GENERATION TRANSMISSION & DISTRIBUTION
Volume 12, Issue 20, Pages 4388-4395

Publisher

INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-gtd.2017.1894

Keywords

battery powered vehicles; power distribution planning; power distribution economics; queueing theory; electric vehicle charging; expected profit maximisation; M; M; s; N queuing model; transportation networks; temporal-state-of-charge characterisation; PEV fast charging station sizing; PEV fast charging station sitting; cost reduction; PEV fast charging demand; future distribution networks; temporal-SoC charging demand characterisation; plug-in electric vehicle fast charging stations; hierarchical optimal planning approach

Funding

  1. National Natural Science Foundation of China [51777183]
  2. Natural Science Foundation of Zhejiang Province [LZ15E070001]
  3. Jiangsu Province [BK20161142]

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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.

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