Networked Microgrid Topology Reconfiguration to Promote Fairness in Proactive Load Shedding: Article No. 112557

  • Yuqi Zhou
  • , Ahmed Zamzam
  • , Andrey Bernstein

Research output: Contribution to journalArticlepeer-review

Abstract

Increasing occurrences of natural disasters and grid emergency events consistently challenge the safe and reliable operations of power systems. During such emergency situations, system operators may proactively shed load to mitigate risks. However, uncoordinated implementation of load shedding may disrupt electricity supply and even lead to cascading failures. Meanwhile, it is crucial to address potential biases affecting different customers when executing load shedding. This paper addresses the dynamic topology reconfiguration problem for networked microgrids with distributed energy resources under emergency conditions. Specifically, we propose a novel rolling-horizon optimization model that integrates fairness-aware constraints into the networked microgrid topology reconfiguration. Unlike existing approaches that focus solely on efficiency or apply fairness considerations in static settings, our method explicitly incorporates temporal fairness constraints to restrict repeated or excessive load curtailment for load blocks. Moreover, the fairness-aware constraints are specifically developed for the context of dynamic networked microgrid topology reconfiguration, and are designed to be convex or amenable to linear reformulations, which offers a more tractable alternative to traditional models with non-convex formulations. Numerical studies on a modified IEEE 13-bus system and a larger-sized SMART-DS networked microgrid system demonstrate the performance of the proposed algorithm towards more fairness-aware networked microgrid topology reconfiguration decision-making.
Original languageAmerican English
Number of pages10
JournalElectric Power Systems Research
Volume253
DOIs
StatePublished - 2026

NLR Publication Number

  • NLR/JA-5D00-93492

Keywords

  • fairness
  • mixed integer optimization
  • networked microgrids
  • proactive load shedding
  • topology reconfiguration

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