Toward Resilient Modern Power Systems: From Single-Domain to Cross-Domain Resilience Enhancement

Hao Huang, H. Vincent Poor, Katherine R. Davis, Thomas J. Overbye, Astrid Layton, Ana E. Goulart, Saman Zonouz

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

| Modern power systems are the backbone of our society, supplying electric energy for daily activities. With the integration of communication networks and high penetration of renewable energy sources (RESs), modern power systems have evolved into a cross-domain multilayer complex system of systems with improved efficiency, controllability, and sustainability. However, increasing numbers of unexpected events, including natural disasters, extreme weather, and cyberattacks, are compromising the functionality of modern power systems and causing tremendous societal and economic losses. Resilience, a desirable property, is needed in modern power systems to ensure their capability to withstand all kinds of hazards while maintaining their functions. This article presents a systematic review of recent power system resilience enhancement techniques and proposes new directions for enhancing modern power systems’ resilience considering their cross-domain multilayer features. We first answer the question, “what is power system resilience?” from the perspectives of its definition, constituents, and categorization. It is important to recognize that power system resilience depends on two interdependent factors: network design and system operation. Following that, we present a review of articles published since 2016 that have developed innovative methodologies to improve power system resilience and categorize them into infrastructural resilience enhancement and operational resilience enhancement. We discuss their problem formulations and proposed quantifiable resilience measures, as well as point out their merits and limitations. Finally, we argue that it is paramount to leverage higher order subgraph studies and scientific machine learning (SciML) for modern power systems to capture the interdependence and interactions across heterogeneous networks and data for holistically enhancing their infrastructural and operational resilience.

Original languageEnglish (US)
Pages (from-to)365-398
Number of pages34
JournalProceedings of the IEEE
Volume112
Issue number4
DOIs
StatePublished - Apr 1 2024
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Electrical and Electronic Engineering

Keywords

  • Enhancing resilience
  • higher order subgraph analyses
  • modern power systems
  • power system resilience
  • scientific machine learning (SciML)

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