A Bayesian approach for short-term transmission line thermal overload risk assessment

Abstract

An on-line conductor thermal overload risk assessment method is presented in this paper. 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 (MC) 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 on-line decision making in a stressed operational environment.