Dynamic thermal ratings of overhead transmission lines based on Bayesian Optimization and Random Forest

With the rapid growth of electricity load and the increasing proportion of renewable energy, the capacity of overhead transmission lines based on adverse weather conditions cannot meet the power supply demand. This paper establishes a thermal balance model for transmission lines based on Bayesian Optimization and Random Forest. On this basis, a calculation method for dynamic thermal ratings is proposed. It combines the Random Forest and the heat balance equation. Verification based on operational data from a 220 kV transmission line shows that the proposed method significantly improves accuracy and enhances the transmission capacity of the transmission lines.