Fast dynamic stability analysis of a power system using artificial neural networks

2007 ◽  
Vol 8 (3) ◽  
pp. 207-212
Author(s):  
D. Kukolj ◽  
D. Popovic ◽  
F. Kulic ◽  
Z. Gorecan
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Stability Analysis ◽  
Power System ◽  
Dynamic Stability ◽  
Artificial Neural ◽  
Fast Dynamic

scholarly journals Feature subset selection in dynamic stability assessment power system using artificial neural networks

2015 ◽  
Vol 18 (2) ◽  
pp. 15-24
Author(s):  
Au Ngoc Nguyen ◽  
Anh Huy Nguyen ◽  
Binh Thi Thanh Phan
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Power System ◽  
Dynamic Stability ◽  
Subset Selection ◽  
Feature Subset Selection ◽  
Feature Subset ◽  
Stability Assessment ◽  
Classification Rate ◽  
Artificial Neural

This paper presents method of feature subset selection in dynamic stability assessment (DSA) power system using artificial neural networks (ANN). In the application of ANN on DSA power system, feature subset selection aims to reduce the number of training features, cost and memory computer. However, the major challenge is to reduce the number of features but classification rate gets a high accuracy. This paper proposes applying Sequential Forward Selection (SFS), Sequential Backward Selection (SBS), Sequential Forward Floating Selection (SFFS) and Feature Ranking (FR) algorithm to feature subset selection. The effectiveness of the algorithms was tested on the GSO-37bus power system. With the same number of features, the calculation results show that SFS algorithm yielded higher classification rate than FR, SBS algorithm. SFS algorithm yielded the same classification rate as SFFS algorithm.

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