Causes identification and sources localization method for multistage voltage sag under the influence of high penetration of renewable energy sources

Cause identification and source localization (CIL) of voltage sags is essential for responsibility allocation and mitigation. Multi-stage voltage sags (MSVS) have emerged as a new type of disturbance in power system with high renewable energy sources (RESs) penetration. Driven by the combined effects of multiple emerging causes, MSVS exhibit complex characteristics that differ significantly from the single-cause, single-stage sags in traditional power systems, making conventional CIL methods difficult to apply. To address this gap, this paper proposes a tailored CIL method for MSVS. First, unified current injection expressions are developed for typical MSVS causes, addressing the challenge of characterizing the uncertainty in emerging disturbance sources and enabling precise characterization of disturbances at the injection node. Second, an analytically disturbance response model at the target node under multi-RES coupling is established, overcoming the inapplicability of traditional linear impedance-based model and numerical iteration-based model. Third, a stage-wise CIL method for MSVS based on Bayesian inference is proposed, mitigating the impact of uncertain system errors and allowing accurate and fast CIL for MSVS events. The proposed method is validated using both measured and simulated data, demonstrating its accuracy and applicability for integration into practical monitoring systems.