External Risk Assessment for Substations Based on Single and Superimposed Anomaly Risks

Abstract

Substations, as critical components of the power system, are frequently exposed to various external risks during operation. Without timely monitoring and effective evaluation, the risks caused by anomalies can undermine the stability of the mining area’s power system, potentially leading to significant production interruptions and safety accidents. However, current research mainly focuses on the substation internal risks. Regrettably, there is currently a lack of implementable external risk assessment methods for substations. To detect substation external risk level effectively, an external risk assessment method for substations based on single and superimposed anomaly risks is proposed. First, the CAVF (Identification credibility C, anomaly area proportion A, anomaly development velocity V and correction factor F) external risk assessment model is constructed, based on the improved PES (Probability, Exposure, Sequel) operational risk assessment method. Next, the collaborative set pair analysis of uncertain AHP (Analytic Hierarchy Process) is used to assign weights to the importance of different anomalies, addressing the differences in the impact of each anomaly and the fuzziness of expert judgment. Then, the IDO (Identity Difference Opposition) contact measure method is adopted to determine the substation external risk level under multiple superimposed anomalies, with the importance weight vector of anomalies. Finally, the substation external risk level is evaluated, comprehensively considering the risks of single and multiple superimposed anomalies. A case in an actual scenario shows the effectiveness of the proposed method, highlighting its significant impact on optimizing maintenance configurations and ensuring the safe operation of substations.

Keywords

• Substation
• state assessment
• external risk levels
• CAVF model
• IDO contact measure method