Preventing Distribution Grid Congestion by Integrating Indirect Control in a Hierarchical Electric Vehicles Management System

Junjie Hu, Chengyong Si, Morten Lind, Rongshan Yu

Research output: Contribution to journalJournal articleResearchpeer-review

428 Downloads (Pure)


In this paper, a hierarchical management system is proposed to integrate electric vehicles (EVs) into a distribution grid. Three types of actors are included in the system: Distribution system operators (DSOs), Fleet operators (FOs) and EV owners. In contrast to a typical hierarchical control system where the upper level controller directly controls the lower level subordinated nodes, this study aims to integrate two common indirect control methods:market-based control and price-based control into the hierarchical electric vehicles management system. Specifically, on the lower level of the hierarchy, the FOs coordinate the charging behaviors of their EV users using a price-based control method. A parametric utility model is used on the lower level to characterize price elasticity of electric vehicles and thus used by the FO to coordinate the individual EV charging. On the upper level of the hierarchy, the distribution system operator uses the market-based control strategy to coordinate the limited power capacity of power transformer with fleet operators. To facilitate the application of the two indirect control methods into the system, a model describing decision tasks in control is used to specify the essential functions that are needed in the control system. The simulations illustrate the effectiveness of the proposed solutions.
Original languageEnglish
JournalI E E E Transactions on Transportation Electrification
Issue number3
Pages (from-to)290-299
Number of pages10
Publication statusPublished - 2016

Bibliographical note

(c) 2015 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.


  • Congestion prevention
  • Electric vehicles
  • Hierarchical control
  • Indirect control
  • Price elasticity model

Cite this