Title :
A Bayesian Approach for Short-Term Transmission Line Thermal Overload Risk Assessment
Author :
Zhang, Juyong ; Pu, Jiexin ; McCalley, James ; Stern, Helman ; Gallus, W.
Author_Institution :
Iowa State University
fDate :
5/1/2002 12:00:00 AM
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.
Keywords :
Bayesian methods; Conductors; Power system modeling; Power system simulation; Power transmission lines; Risk management; Thermal conductivity; Thermal stresses; Transmission lines; Weather forecasting; Bayesian analysis; Markov chain Monte; Security assessment; transmission line thermal overload risk assessment;
Journal_Title :
Power Engineering Review, IEEE
DOI :
10.1109/MPER.2002.4312239