Identification of critical clusters in inverter-based microgrids

Andrey Gorbunov, Jimmy Chih Hsien Peng, Petr Vorobev

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

In this paper, we investigate the stability properties of inverter-based microgrids by establishing the possible presence of the so-called critical clusters - groups of inverters with their control settings being close to the stability boundary. For this, we consider the spectrum of the weighted admittance matrix of the network and show that its distinct eigenvalues correspond to inverter clusters, whose structure can be revealed by the corresponding eigenvector. We show that the maximum eigenvalue of the weighted admittance matrix corresponds to the cluster, closest to stability boundary. We also establish that there exists a boundary on the value of this eigenvalue, that corresponds to the stability of the overall system. Thus, we make it possible to certify the stability of the system and find the groups of inverters in which control settings are closest to the stability boundary.

Original languageEnglish
Article number106731
JournalElectric Power Systems Research
Volume189
DOIs
Publication statusPublished - Dec 2020

Keywords

  • Droop controlled inverters
  • Inverter-based microgrids
  • Reduced-order models
  • Small signal stability
  • Stability assessment

Fingerprint

Dive into the research topics of 'Identification of critical clusters in inverter-based microgrids'. Together they form a unique fingerprint.

Cite this