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

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. • True grid strength is established through time-domain analyses. • Clustering finds steady-state counterparts of time-domain grid strength metrics. • Grid strength can identify unique credible contingencies. • Faults at buses in the same grid strength cluster show similar voltage responses.