Data-Driven Small-Signal Stability Boundary Based on Damping Ratio Sensitivity

Small-signal stability boundary (SSSB) plays a significant role in operation and control in power system. The small-signal stability is able to assessed quickly and improved by the useful information of SSSB. While SSSB generation faces plenty of challenges in existing methods, such as high computation complexity, massive operating points (OPs) and contingencies should be considered. The proposed paper proposes a data-driven method to generate the stability boundary, by quickly sampling as many as possible the OPs which the damping ratio of its are close to the stability boundary with critical N-1 contingencies. To achieve this goal, a sample method with the self-adapting step size based on the damping ration sensitivity and critical contingencies selection based on the network theory are proposed in this paper. The effectiveness of the proposed method is demonstrated by IEEE 9-bus system and NESTA 162-bus system.