Reasoning on Critical Clearing Time with the Rules Extracted from a Multilayer Perceptron Artificial Neural Network

Author

Lin, Y.J.

Author_Institution

I-Shout Univ., Kaohsiung

fYear

2007

fDate

5-8 Nov. 2007

Firstpage

1

Lastpage

6

Abstract

In the past two decades, artificial neural networks (ANN) have been employed to determine the critical clearing time (CCT). This issue mainly concerns the prediction rather than the explanation. ANNs were considered to be black boxes, unlike decision trees which rules could be deduced from. This paper describes the procedures for reasoning CCT by means of rules extracted from a multilayer perceptron (MLP) artificial neural network. Those extracted rules are presented in ´IF-THEN´ statement. Case studies of two power systems shall justify the proposal.

Keywords

multilayer perceptrons; power engineering computing; power system transient stability; ANN; IF-THEN statement; black boxes; critical clearing time; multilayer perceptron artificial neural network; power systems; Artificial neural networks; Multilayer perceptrons; Neurons; Power system analysis computing; Power system faults; Power system measurements; Power system simulation; Power system stability; Power system transients; Training data; Critical Clearing Time (CCT); MultiLayer Perceptron (MLP); Transient stability;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems Applications to Power Systems, 2007. ISAP 2007. International Conference on

Conference_Location

Toki Messe, Niigata

Print_ISBN

978-986-01-2607-5

Electronic_ISBN

978-986-01-2607-5

Type

conf

DOI

10.1109/ISAP.2007.4441601

Filename

4441601