ANN sensitivity analysis for identification of relevant features in security assessment

• Type: Article in International Conference Proceedings Book
• Date: 2001

Authors

José Nuno Fidalgo (Author) FEUP; João Peças Lopes (Author) FEUP

Conference proceedings International

Title: 2001 IEEE Porto Power Tech Proceedings

Pages: 274-279

2001 IEEE Porto Power Tech Conference

Porto, 10 September 2001 through 13 September 2001

Indexing

Scopus - 2 Citations

Other information

Authenticus ID: P-007-SPN

DOI: 10.1109/ptc.2001.964755

Abstract (EN): This paper deals with a problem of identification of the best subset of variables that should be used for dynamic security assessment of a power system, when this task is pro-vided by artificial neural networks (ANN)- The approach de-scribed here exploits ANN output sensitivities relatively to the inputs and correlation degrees, to identify the most relevant system variables to be used for an effective security assessment task. The ANNs are initially trained with all low-correlated candidate features, which enables the sensitivity analyses for the initial set of system features. Derivatives of the ANN output relatively to each input are obtained by exploiting the chain rule, similar to the one used for weights adaptation on Back-propagation Algorithm. A description of the application of this approach in a real system is present in the paper. Results obtained in the dynamic security assessment problem of the network of the island of Crete were quite successful. © 2001 IEEE.

Language: English

Type (Professor's evaluation): Scientific