Research on probabilistic inference methods for power grid icing risk assessment: a systematic analysis incorporating ultra-high voltage line ratios

Abstract

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IntroductionPower grid icing is a severe natural hazard that threatens the safe and stable operation of power systems. With the expansion of ultra-high voltage (UHV) power grids, systematic assessment of icing disaster risks has become increasingly crucial.MethodsThis paper proposes a probabilistic inference approach for power grid icing risk assessment, which employs a Poisson process model to characterize the nonlinear relationship between line failure probability and ice thickness, combined with Monte Carlo simulation techniques to evaluate overall system risk.ResultsResearch findings indicate that critical ice thickness and failure sensitivity coefficients significantly impact the grid’s disaster resistance capability, particularly when the proportion of high-load UHV lines increases, leading to nonlinear growth in system risk. Quantitative analysis reveals that when UHV lines account for 50% of the system, the maximum risk can exceed 15 times that of conventional line scenarios.DiscussionThe research outcomes provide theoretical foundations for power grid icing disaster prevention and mitigation, offering important guidance for optimizing grid planning and enhancing system resilience.

Keywords

• power grid icing
• probabilistic inference
• risk assessment
• Monte Carlo simulation
• ultra-high voltage lines
• system vulnerability