Optimal Coordination of Electric Vehicles for Virtual Power Plants with Dynamic Communication Spectrum Allocation

Bin Zhou, Kuan Zhang, Ka Wing Chan, Canbing Li, Xi Lu, Siqi Bu, Xiang Gao

Research output: Journal article publicationJournal articleAcademic researchpeer-review

41 Citations (Scopus)


This article proposes an optimal coordinated scheduling of electric vehicles (EVs) for a virtual power plant (VPP) considering communication reliability. Recent advancements on wireless technologies offer flexible communication solutions with wide coverage and low-cost deployment for smart grid. Nevertheless, the imperfect communication may deteriorate the monitoring and controlling performance of distributed energy resources. An interactive approach is presented for combined optimization of dynamic spectrum allocation and EV scheduling in the VPP to coordinate charging/discharging strategies of massive and dispersed EVs. In the proposed approach, a dynamic partitioning model of the multi-user multi-channel cognitive radio is used to cope with the vehicle-to-grid (V2G) communication issue due to variable EV parking behaviors, and a two-stage V2G dispatch scheme is proposed for the wind-solar-EV VPP to maximize its overall daily profit. Furthermore, the effects of packet loss probability on the VPP scheduling performance and battery degradation cost are thoroughly analyzed and investigated. Comparative studies have been implemented to demonstrate the superior performance of the proposed methodology under various imperfect communication conditions.

Original languageEnglish
Article number9064888
Pages (from-to)450-462
Number of pages13
JournalIEEE Transactions on Industrial Informatics
Issue number1
Publication statusPublished - Jan 2021


  • Smart grid
  • stochastic optimization
  • vehicle to grid
  • virtual power plant
  • wireless communication

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Computer Science Applications
  • Electrical and Electronic Engineering


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