Abstract:To address the challenges of high uncertainty and operational complexity brought by the integration of a high proportion of renewable energy in new-type power systems, and to ensure safe and stable operation, this paper proposes a dynamic risk assessment method based on a variable grid group structure. Centered on power quality as the core indicator, the method establishes a comprehensive risk assessment framework encompassing data preprocessing, feature analysis, predictive modeling, and risk warning. By integrating the AHP-TOPSIS algorithm, it quantifies risk levels and accurately identifies key risk areas. The introduction of the dynamic variable grid group structure enhances the system"s adaptability to complex operational environments and significantly improves the sensitivity and accuracy of risk assessment under dynamic conditions. Case studies demonstrate that the proposed method can effectively identify potential risk regions within new-type power systems, with assessment results closely matching actual operating conditions, thereby validating its effectiveness and feasibility. The findings provide a solid theoretical foundation and practical reference for improving the safety, stability, and operational efficiency of new-type power systems, offering valuable guidance for dynamic risk management in complex power networks.