Electric Vehicle Load Management: An Architecture for Heterogeneous Nodes

Kun Qian, Robert W. Brehm, Thomas Ebel, Rebecca Adam

Research output: Contribution to journalJournal articleResearchpeer-review

25 Downloads (Pure)

Abstract

Integrating electric vehicle (EV) charging infrastructures into the utility grids requires solutions for coordinated charging of EVs. Load management systems aim at computing coordinated charging schedules for electric vehicles based on predetermined charging objectives. Contributions on coordinated charging for EVs predominantly assume that the EVs or the charging stations are controllable entities in the load management systems. However, in practice, charging infrastructures may consist of controllable and uncontrollable entities. This paper proposes architecture and control strategies for EV charging infrastructures consisting of controllable and uncontrollable entities. Simulations based on real-world charging sessions show how the share of uncontrollable entities in a charging infrastructure affects the performance of different control strategies in the system architecture. We show that a certain number of uncontrollable entities in a charging infrastructure does not affect the scheduling objectives significantly. EV fleet and charging infrastructure operators can develop pragmatic investment and operation strategies based on the proposed control strategy and architecture.
Original languageEnglish
JournalIEEE Access
ISSN2169-3536
DOIs
Publication statusPublished - Jun 2022

Keywords

  • electric vehicles , scheduling strategy , aggregator , control architecture

Fingerprint

Dive into the research topics of 'Electric Vehicle Load Management: An Architecture for Heterogeneous Nodes'. Together they form a unique fingerprint.

Cite this