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

Author

Zhang, Jun ; Pu, Jian ; McCalley, James D. ; Stern, Hal ; Gallus, William A., Jr.

Author_Institution

Dept. of Electr. Eng. & Comput. Eng., Iowa State Univ., Ames, IA, USA

Volume

17

Issue

3

fYear

2002

fDate

7/1/2002 12:00:00 AM

Firstpage

770

Lastpage

778

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.

Keywords

Bayes methods; Monte Carlo methods; power system security; power transmission lines; time series; Bayesian time series models; Markov Chain Monte Carlo; on-line conductor thermal overload risk assessment method; on-line decision making; power system operating conditions; predicted risk; security assessment; stressed operational environment; thermal overload risk estimation; transmission lines; weather conditions modeling; Bayesian methods; Conductors; Monte Carlo methods; Power system modeling; Power system simulation; Power transmission lines; Risk management; Thermal conductivity; Transmission lines; Weather forecasting;

fLanguage

English

Journal_Title

Power Delivery, IEEE Transactions on

Publisher

ieee

ISSN

0885-8977

Type

jour

DOI

10.1109/TPWRD.2002.1022802

Filename

1022802