A Data-Driven Trajectory Approach for Dynamic VAr Support in Renewable Rich Power Grid

Short-term voltage stability (STVS) of power grids could be jeopardized due to the nonlinear dynamic characteristics of loads such as induction motors (IMs) and the retirement of synchronous generators. Moreover, the appearance of inverter-based generators (IBGs) in the system would make the grids more susceptible to voltage instability. Hence, there is an indispensable need to identify adequate mitigation measures to deal with these enduring challenges. This paper proposes a driven-data trajectory approach to locate the dynamic VAr support (DVS) to maintain STVS in power grids with high penetration of IBGs. The proposed data-driven trajectory approach ranks the best locations for DVS by comparing grid responses of different possible DVS sites with respect to the desired reference response. The developed approach covers the full signature of grid dynamics in generation and load sides. For illustration, this approach is applied to the Reliability and Voltage Stability (RVS) test system designed for STVS analysis. Several scenarios are tested, including various IM penetrations and IBG integration, control and load compositions, to demonstrate the viability and robustness of the proposed approach. Moreover, the STVS performance of the system with the proposed algorithm is verified through the motor stalling scan. The comprehensive assessment shows that the system exhibits the best STVS performance with DVS placement using the proposed method.