Optimal Operation Control Strategies for Active Distribution Networks under Multiple States: A Systematic Review

  • Jingtao Zhao
  • , Zhi Wu
  • , Huan Long
  • , Huapeng Sun
  • , Xi Wu
  • , Chingchuen Chan
  • , Mohammad Shahidehpour

Research output: Journal article publicationReview articleAcademic researchpeer-review

5 Citations (Scopus)

Abstract

With the large-scale integration of distributed renewable generation (DRG) and increasing proportion of power electronic equipment, the traditional power distribution network (DN) is evolving into an active distribution network (ADN). The operation state of an ADN, which is equipped with DRGs, could rapidly change among multiple states, which include steady, alert, and fault states. It is essential to manage large-scale DRG and enable the safe and economic operation of ADNs. In this paper, the current operation control strategies of ADNs under multiple states are reviewed with the interpretation of each state and the transition among the three aforementioned states. The multi-state identification indicators and identification methods are summarized in detail. The multi-state regulation capacity quantification methods are analyzed considering controllable resources, quantification indicators, and quantification methods. A detailed survey of optimal operation control strategies, including multiple state operations, is presented, and key problems and outlooks for the expansion of ADN are discussed.

Original languageEnglish
Pages (from-to)1333-1344
Number of pages12
JournalJournal of Modern Power Systems and Clean Energy
Volume12
Issue number5
DOIs
Publication statusPublished - Sept 2024

Keywords

  • active distribution network (ADN)
  • identification indicator
  • Multi-state control strategy
  • regulation capacity quantification

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Energy Engineering and Power Technology

Fingerprint

Dive into the research topics of 'Optimal Operation Control Strategies for Active Distribution Networks under Multiple States: A Systematic Review'. Together they form a unique fingerprint.

Cite this