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Quantifying power system strength to identify unique credible contingencies in renewable-dominated power systems

  • Boise State University

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

A key challenge of the new power system with high penetration of inverter-based resources is the accurate quantification of system strength in inverter-dominated grids. This quantification is essential to support effective system planning. However, current metrics based on the short-circuit ratio are inadequate for assessing the true strength of inverter-dominated grids. Another important topic of modern power system studies is the selection of credible contingencies. The more credible these contingencies, the more robust the resulting analysis. However, existing contingency selection methods often fail to capture key dynamic behaviors, particularly during system disturbances. This research addresses these challenges by proposing a grid strength metric derived from time-domain and consistent with industry-standard definitions to quantify system strength at the bus level. To connect this proposed index with metrics from the steady-state domain, a multimetric validation approach is used, incorporating error, correlation, and clustering analysis to compare and identify a suitable steady-state substitute. Among the evaluated metrics, short-circuit power is identified as the most suitable substitute for the test system, rather than the traditional short-circuit ratio. Building on this foundation, a clustering-based algorithm is introduced to determine credible contingencies based on the grouping of buses with similar grid strength values. The method reduces the number of contingencies to unique credible ones while preserving the accuracy of dynamic response assessments. Tested and validated on a modified IEEE 43-bus renewable-dominated industrial microgrid, this research presents a practical methodology for grid strength quantification, comparison, validation, enhancement, and credible contingency selection.

Original languageEnglish
Article number111271
JournalInternational Journal of Electrical Power and Energy Systems
Volume172
Early online date23 Oct 2025
DOIs
StatePublished - Nov 2025

Keywords

  • Cluster analysis
  • Contingency analysis
  • Correlation analysis
  • FIDVR
  • Power system strength
  • Renewable dominated microgrid
  • Short-circuit ratio

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