Joint Planning of EV Fast Charging Stations and Power Distribution Systems With Balanced Traffic Flow Assignment

Wentao Yang, Weijia Liu, C. Chung, Fushuan Wen

Research output: Contribution to journalArticlepeer-review

40 Scopus Citations

Abstract

To tackle the challenges introduced by the fast-growing charging demand of electric vehicles (EVs), the power distribution systems (PDSs) and fast charging stations (FCSs) of EVs should be planned and operated in a more coordinated fashion. However, existing planning approaches generally aim to minimize investment costs in PDSs while ignoring the risk of worsening traffic conditions. To overcome this research gap, this article integrates the interests of traffic networks into PDS and FCS joint planning model to mitigate negative impacts on traffic conditions caused by installing FCSs. First, a novel microscopic method that is different from traditional assignment methods is proposed to simulate the influences of FCSs on traffic flows and EV charging loads. Then, a multiobjective joint planning model is developed to minimize both the planning costs and unbalanced traffic flows. A new bilayer Benders decomposition algorithm is designed to solve the proposed joint planning model. Numerical results on two practical systems in China validate the feasibility of our microscopic method by comparing the simulated results with real data. Compared with existing approaches, it is also demonstrated that the proposed joint planning approach helps to balance traffic flow assignments and relieve traffic congestion.

Original languageAmerican English
Article number9096550
Pages (from-to)1795-1809
Number of pages15
JournalIEEE Transactions on Industrial Informatics
Volume17
Issue number3
DOIs
StatePublished - Mar 2021

Bibliographical note

Publisher Copyright:
© 2005-2012 IEEE.

NREL Publication Number

  • NREL/JA-5D00-78879

Keywords

  • Bilayer expanded Benders decomposition
  • electric vehicle (EV)
  • joint planning
  • multiagent-based microscopic traffic assignment model (MMTAM)
  • traffic flow assignment

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