Distribution Network Electric Vehicle Hosting Capacity Maximization: A Chargeable Region Optimization Model

Jian Zhao, Jianhui Wang, Zhao Xu, Cheng Wang, Can Wan, Chen Chen

Research output: Journal article publicationJournal articleAcademic researchpeer-review

29 Citations (Scopus)

Abstract

To coordinate electric vehicle (EV) charging, the EV aggregator (EVA) is usually assumed to obtain the privilege from EV owners (EVOs) to determine the EV charging profile, and complex communication between EVA and EVOs is demanded, which poses difficulties for practical applications. In contrast, this paper proposes the concept of an EV chargeable region to evaluate the distribution network (DN) EV hosting capacity, i.e., how much EV charging demand can be accommodated in a DN, within which the technical constraints of DN (e.g., voltage deviation) are guaranteed and EVOs' charging requests are maximally ensured. The optimization of the EV chargeable region is formulated as a two-stage robust optimization model with adjustable uncertainty set. The EV chargeable region and DN decision variables are optimized in the first stage and the feasibility in the real-time worst-case scenario is checked in the second stage, considering the uncertainty of EV charging demand and DN active and reactive power. A modified column and constraint generation and outer approximation method is adopted to address the proposed problem. Simulations on an IEEE 123-node DN demonstrate the effectiveness of the proposed model.
Original languageEnglish
Article number7817888
Pages (from-to)4119-4130
Number of pages12
JournalIEEE Transactions on Power Systems
Volume32
Issue number5
DOIs
Publication statusPublished - 1 Sep 2017

Keywords

  • Adjustable uncertainty set
  • chargeable region
  • charging strategy
  • distribution network
  • electric vehicle
  • hosting capacity
  • robust optimization
  • two-stage optimization

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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