Abstract
An online conductor thermal overload risk assessment method is presented. Bayesian time-series models are used to model weather conditions along the transmission lines. An estimate of the thermal overload risk is obtained by Monte Carlo simulation. We predict the thermal overload risk for the next hour based on the current weather conditions and power system operating conditions. The predicted risk of thermal overload is useful for online decision-making in a stressed operational environment.
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