Dynamic stability assessment of a medium size power system towards large disturbances case study of the blackout of August 2014 of the Tunisian power system

2017 ◽  
Author(s):  
Amal Hasni ◽  
Hamdi Khadraoui ◽  
Faouzi Bacha
Keyword(s):  
Power System ◽  
Dynamic Stability ◽  
Medium Size ◽  
Stability Assessment

Dynamic stability assessment model of a parallel AC-DC power system

1977 ◽  
Vol 96 (4) ◽  
pp. 1296-1304 ◽  
Author(s):  
J.W. Klein ◽  
C.H. Ong ◽  
P.C. Krause ◽  
R.A. Fernandes
Keyword(s):  
Power System ◽  
Dynamic Stability ◽  
Assessment Model ◽  
Stability Assessment ◽  
Dc Power

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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