Stability and control of power grids

Tao Liu, Yue Song, Lipeng Zhu, David J. Hill

Research output: Contribution to journalReview ArticleResearchpeer-review

19 Citations (Scopus)

Abstract

Power grids are critical infrastructure in modern society, and there are well-established theories for the stability and control of traditional power grids under a centralized paradigm. Driven by environmental and sustainability concerns, power grids are undergoing an unprecedented transition, with much more flexibility as well as uncertainty brought by the growing penetration of renewable energy and power electronic devices. A new paradigm for stability and control is under development that uses graph-based, data-based, and distributed analysis tools. This article surveys classic and novel results on the stability and control of power grids to provide a perspective on this both old and new subject.

Original languageEnglish
Pages (from-to)689-716
Number of pages28
JournalAnnual Review of Control, Robotics, and Autonomous Systems
Volume5
DOIs
Publication statusPublished - May 2022
Externally publishedYes

Keywords

  • Deep learning
  • Distributed control
  • Machine learning
  • Network systems
  • Power grids
  • Stability

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