Enhancing power grid resilience through an IEC61850-based EV-assisted load restoration

Pouya Jamborsalamati*, M. J. Hossain, Seyedfoad Taghizadeh, Georgios Konstantinou, Moein Manbachi, Payman Dehghanian

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

33 Citations (Scopus)


Contrary to reliability analysis in power systems with the main mission on safely and securely withstanding credible contingencies in day-to-day operations, resilience assessments are centered on high-impact low probability (HILP) events in the grid. This paper proposes an autonomous load restoration architecture founded on IEC 61850-8-1 GOOSE communication protocol to engender an enhanced feeder-level resilience in active power distribution grids. Different from the past research on outage management solutions, most of which 1) are not resilience-driven; 2) are reactive solutions to local single-fault events; and 3) do not address both network built-in flexibilities and flexible resources. The proposed solution harnesses 1) the imported power and flexibility from the neighboring networks; 2) distributed energy resources; and 3) vehicle to grid capacity of electric vehicles aggregations to enhance the feeder-level resourcefulness for agile response and recovery. Through real-time self-reconfiguration strategies, the suggested solution is capable of coping both single and subsequent outage events, and will engender a heightened resilience before and during the contingency period. Moreover, a resilience evaluation framework, which quantifies the contribution of all resources involved in service restoration, is developed. Real-time performance of the designed architecture is evaluated on a real-world power distribution grid using a real-time hardware-in-the-loop platform. Numerical case studies through a number of diverse scenarios demonstrate the efficacy of the proposed restoration solution in practicing an enhanced resilience in power distribution systems in response to HILP scenarios.

Original languageEnglish
Pages (from-to)1799-1810
Number of pages12
JournalIEEE Transactions on Industrial Informatics
Issue number3
Publication statusPublished - Mar 2020


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