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Unpublished Paper
Power System Security Margin Prediction Using Radial Basis Function Networks
Computer Science Technical Reports
  • Guozhong Zhou, Iowa State University
  • James D. McCalley, Iowa State University
  • Vasant Honavar, Iowa State University
Publication Date
6-27-1997
Technical Report Number
TR97-10
Abstract

This paper presents a method to predict the postcontingency security margin using radial basis function (RBF) networks. A genetic algorithm-based feature selection tool is developed to obtain the most predictive attributes for use in RBF networks. The proposed method is applied to a thermal overload problem for demonstration. Simulation results show that the proposed method gives satisfactory results and the running time decreases by a factor of 10 compared with using multilayer perceptrons.

Citation Information
Guozhong Zhou, James D. McCalley and Vasant Honavar. "Power System Security Margin Prediction Using Radial Basis Function Networks" (1997)
Available at: http://works.bepress.com/james-mccalley/4/