Intelligent Computation Method for Compensation of Arc Suppression Coils Based on Dynamic Parameter Optimization Models

This study proposes an intelligent compensation calculation method for arc suppression coils based on dynamic parameter optimization, which effectively improves the accuracy of capacitance current compensation and system stability through multi-source data fusion, multifactor correction models, and closed-loop optimization strategies. First, power grid equipment parameters are integrated with environmental data to construct a dynamic matrix and establish temperature/humidity correction models. Second, a dynamic compensation degree calculation model is designed, combining real-time inductive current, dynamic capacitive current, and time variables. Through adaptive adjustment strategies, the peak detuning degree is reduced, and the response time is shortened. Additionally, a multidimensional resonance risk assessment model is established, introducing dynamic risk indicators to improve fault detection rates and reduce false alarm rates.