Classification of power system voltage stability conditions using Kohonen's self-organising feature map and learning vector quantisation

2011 ◽  
Vol 22 (3) ◽  
pp. 412-420 ◽  
Author(s):  
Abhinandan De ◽  
Kabir Chakraborty ◽  
Abhijit Chakrabarti
Keyword(s):  
Power System ◽  
Voltage Stability ◽  
Stability Conditions ◽  
Feature Map ◽  
Learning Vector Quantisation ◽  
Vector Quantisation

scholarly journals POWER SYSTEM CONTINGENCY RANKING BASED ON SHORT-TERM VOLTAGE STABILITY INDICES

2019 ◽  
Vol 49 (4) ◽  
pp. 225-232
Author(s):  
Jaime Dwaigth Pinzon Casallas ◽  
D. G. Colomé
Keyword(s):  
Dynamic Response ◽  
Power System ◽  
New England ◽  
Voltage Stability ◽  
Short Term ◽  
Voltage Instability ◽  
Contingency Ranking ◽  
Dynamic Voltage ◽  
Stability Indices

This paper presents a novel methodology to identify critical contingencies that produce short-term voltage stability problems (STVS). The proposed methodology classifies the state of the pow-er system for each contingency, assessing the voltage stability of the post-contingency dynamic response from the calculation of the maximal Lyapunov expo-nent (MLE) and dynamic voltage indices at each bus and the whole system. In order to determine the crit-ical contingencies, the values of the indices and the results of the classification of the post-contingency state are statistically analysed. The methodology is tested in the New England 39-bus system, obtaining satisfactory results in relation to the identification not only of the most critical contingencies but also of vulnerable buses to voltage instability. New contri-butions of this work are the contingency classifica-tion methodology, the algorithm for calculating dy-namic indices and the method of classification of the operating state as a function of the STVS problem magnitude.

Classification of non-averaged EEG data by learning vector quantisation and the influence of signal preprocessing

1994 ◽  
Vol 32 (5) ◽  
pp. 571-576 ◽  
Author(s):  
D. Flotzinger ◽  
G. Pfurtscheller ◽  
Ch. Neuper ◽  
J. Berger ◽  
W. Mohl
Keyword(s):  
Learning Vector Quantisation ◽  
Vector Quantisation ◽  
Eeg Data ◽  
Signal Preprocessing
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