Title :
Security analysis for system operation using Bayes classifier
Author :
Kim, Hyungchul ; Singh, C.
Author_Institution :
Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA
Abstract :
This paper proposes a Bayes classifier for security assessment in power systems. In power system security analysis, characterization of certain contingencies using voltage stability and load curtailment is a cumbersome and time-consuming process. Bayes classifier provides assessment of system security without complicated contingency analysis and can reduce the computational burden. Security status of a given feature vector can be determined by maximum a posteriori probability rule based on Bayes rule. The case study of WSCC system is presented to demonstrate the efficiency of this approach.
Keywords :
Bayes methods; fuzzy neural nets; power system security; power system transient stability; probability; ANN; Bayes classifier; Bayes rule; WSCC system; artificial neural network; load curtailment; optimal power flow; posteriori probability; power system operation; power system security; transient stability; voltage stability; Artificial neural networks; Bayesian methods; Circuit stability; Data security; Power system analysis computing; Power system security; Power system stability; Power system transients; Stability analysis; Voltage;
Conference_Titel :
Power Engineering Society General Meeting, 2003, IEEE
Print_ISBN :
0-7803-7989-6
DOI :
10.1109/PES.2003.1270385