Multiple Stability Margin Indexes-Oriented Online Risk Evaluation and Adjustment of Power System Based on Digital Twin

Bo Zhou, Yunyang Xu, Xinwei Sun, Xi Ye, Yuhong Wang, Huaqing Dai and Shilin Gao ()
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Bo Zhou: State Grid Sichuan Electric Power Research Institute, Chengdu 610072, China
Yunyang Xu: State Grid Sichuan Electric Power Research Institute, Chengdu 610072, China
Xinwei Sun: State Grid Sichuan Electric Power Research Institute, Chengdu 610072, China
Xi Ye: State Grid Sichuan Electric Power Company, Chengdu 610000, China
Yuhong Wang: College of Electrical Engineering, Sichuan University, Chengdu 610065, China
Huaqing Dai: College of Electrical Engineering, Sichuan University, Chengdu 610065, China
Shilin Gao: College of Electrical Engineering, Sichuan University, Chengdu 610065, China

Energies, 2025, vol. 18, issue 18, 1-36

Abstract: To address the challenges of transient voltage stability in modern power systems with high renewables penetration, this paper proposes a multiple stability margin indexes-oriented online risk evaluation and adjustment framework based on a digital twin platform. The System Voltage Deviation Index ( S VDI ) is first introduced as a quantitative metric to assess transient voltage stability from time-domain simulation results, capturing the system’s dynamic response under large disturbances. An arbitrary Polynomial Chaos (aPC) expansion combined with Sobol sensitivity analysis is then employed to model the nonlinear relationship between S VDI and uncertain inputs such as wind power, photovoltaic output, and dynamic load variations, enabling accurate identification of key nodes influencing stability. Furthermore, an emergency control optimization model is developed that jointly considers voltage, frequency, and rotor angle stability margins, as well as the economic costs of load shedding, with a trajectory sensitivity-based local linearization technique applied to enhance computational efficiency. The proposed method is validated on a hybrid AC/DC test system (CSEE-VS), and results show that, compared with a traditional control strategy, the optimized approach reduces total load shedding from 322.59 MW to 191.40 MW, decreases economic cost from 229.18 to 178.11, and improves the transient rotor angle stability index from 0.31 to 0.34 and the transient frequency stability index from 0.3162 to 1.511, while maintaining acceptable voltage stability performance. These findings demonstrate that the proposed framework can accurately assess online operational risks, pinpoint vulnerable nodes, and generate cost-effective, stability-guaranteeing control strategies, showing strong potential for practical deployment in renewable-integrated power grids.

Keywords: transient voltage stability; multiple stability margin indexes; System Voltage Deviation Index; critical node identification; trajectory sensitivity; emergency control optimization; data-driven modeling; digital twin (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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