Power system blackout risk assessment considering compound typhoon-rainstorm conditions
DOI：10.19783/j.cnki.pspc.260197
Key Words:compound typhoon-rainstorm events  Copula functions  return period  climate-sensitive model  blackout risk assessment
Author NameAffiliation
CHENG Yinuo Department of Electrical Engineering, North China Electric Power University, Baoding 071003, China 
REN Hui Department of Electrical Engineering, North China Electric Power University, Baoding 071003, China 
GAO Qianying Department of Electrical Engineering, North China Electric Power University, Baoding 071003, China 
YU Shenglong Department of Electrical Engineering, North China Electric Power University, Baoding 071003, China 
ZHEN Zhao Department of Electrical Engineering, North China Electric Power University, Baoding 071003, China 
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Abstract:To evaluate power system large-scale blackout risks under compound typhoon-rainstorm events, a risk assessment method that explicitly considers compound climate conditions is proposed. First, Bayesian model averaging (BMA) is employed to integrate multiple candidate marginal distributions. Combined with Copula functions, a robust wind-rain joint probability model for small samples is constructed. Constrained by the joint return period, a Gaussian mixture model (GMM) is further adopted to cluster and generate three representative compound climate scenarios. Second, a climate-sensitive multi-type source-load model is developed to characterize the coordinated responses of restricted wind-solar-hydro power outputs and meteorological load variations. Finally, a multi-dimensional blackout risk index system is formulated by integrating equipment vulnerability models with cascading failure simulations, incorporating outage consequences and annual occurrence probabilities. Simulation results show that the strong-wind scenario poses a significantly higher blackout risk than the other scenarios, while moderate-intensity but high-frequency events yield the highest annual expected risk, highlighting their long-term risk contribution. The proposed method effectively quantifies the differentiated compound-scenario risks and provides a quantitative basis for coastal power grid disaster prevention planning.
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