Scalable Small-Signal Stability Assessment of Power Systems Based on Frequency-Domain Quadratic Constraints

Abstract

Small-signal stability analysis of power electronics-dominated power systems is becoming increasingly challenging due to the large-scale integration of heterogeneous grid-following (GFL) and grid-forming (GFM) converters. Classical centralized methods, such as eigenvalue analysis and the generalized Nyquist criterion, provide direct stability assessment tools but exhibit limited scalability as the system size increases. This motivates scalable analysis methods for stability assessment and device-level diagnosis, and calls for less conservative stability conditions. To this end, this paper proposes a scalable small-signal stability assessment method with quantitative stability indices for multi-converter systems based on frequency-domain quadratic constraints (FQCs). It is shown that several existing stability conditions, including geometric conditions based on the Davis-Wielandt (DW) shell, numerical range, $x$-$z$ graph, scaled relative graph (SRG), mixed gain-phase condition, and passivity condition, are special cases of the FQC-based stability condition. This FQC-based formulation also clarifies the requirements for decentralized verification of these existing stability conditions. To further reduce conservatism, a full-multiplier FQC-based stability condition is developed, based on which an optimization problem is formulated for scalable stability certification and device-level diagnosis using quantitative stability indices without relying on graphical inspection. Combined with the mixed gain-phase condition, this optimization problem forms a hierarchical screening-diagnosis procedure that improves efficiency. Case studies demonstrate that the proposed method is less conservative than existing criteria and can effectively identify problematic devices associated with potential instability risks.