面向可靠性提升的电动汽车充电基础设施协同优化规划

Translated title of the contribution: Collaborative optimization planning of electric vehicle charging infrastructure for reliability improvement

Jinpeng Meng, Yue Xiang, Chenghong Gu, Shijie Chen, Junyong Liu

Research output: Contribution to journalArticlepeer-review

17 Citations (SciVal)

Abstract

In order to realize the scientific configuration of charging infrastructure under the large-scale development trend of EVs(Electric Vehicles), an optimal planning method of charging infrastructure collaborative service is proposed for the "EV-road-grid" coupled system. Based on the analysis of charging demand, an EV cluster control strategy is proposed to simulate the control mode for reliability loss consumption under the condition of insufficient power supply. Based on quasi-sequential Monte Carlo simulation method and considering users' preference for charging power, a collaborative service model of multi-type charging infrastructures within the station is designed. Aiming at the charging infrastructure planning problem, a new multi-objective optimal planning model is proposed, which is oriented to the collaborative improvement of power grid's operation reliability and EVs' travel reliability, and the influence of investment cost and user satisfaction is considered. The feasibility and validity of the proposed method are verified by the simulation and analysis of the "EV-road-grid" coupled system under various scenarios and objects.

Translated title of the contributionCollaborative optimization planning of electric vehicle charging infrastructure for reliability improvement
Original languageChinese (Traditional)
Pages (from-to)36-44
Number of pages9
JournalDianli Zidonghua Shebei/Electric Power Automation Equipment
Volume41
Issue number6
Early online date10 Jun 2021
DOIs
Publication statusPublished - 10 Jun 2021

Keywords

  • Charging infrastructure planning
  • Electric vehicles
  • Multi-type charging infrastructures
  • Quasi-sequential Monte Carlo simulation
  • Reliability

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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