Online Voltage Stability Assessment Using ANN and Continuation Power Flow: Using AI for Real-time Analysis - Couverture souple

Singh, Rhythm; Kumar, Chakresh

 
9783639363746: Online Voltage Stability Assessment Using ANN and Continuation Power Flow: Using AI for Real-time Analysis
Couverture souple
ISBN 10 : 3639363744 ISBN 13 : 9783639363746
Editeur : VDM Verlag Dr. Müller, 2011

Synopsis

This book presents an Artificial Neural Network (ANN) based method, involving the usage of Continuation Power Flow Methods, for on-line voltage stability assessment of power systems. A continuation power flow type algorithm is implemented through MATLAB, using the M-file programming approach along with some implementations from the "Voltage Stability Toolbox courtesy of Centre for Electric Power Engineering,Drexel University" and the Power System Analysis Toolbox. This implementation generates the nose curves, used for voltage stability analysis, for IEEE 30 bus test system which, in turn, are used as target outputs for training the ANNs, by finding the distance to voltage collapse from the current system operating point.A single feed forward type Artificial Neural Network (ANN) is to be trained for all the vulnerable load buses of the test systems.A Modal Analysis technique has been implemented to identify the most vulnerable load buses of the IEEE 30 bus test system.The trained ANN is supposed to provide, as output, the Voltage Collapse Proximity Indicators (VCPI) for all the vulnerable load buses of the system, which are a measure of the voltage stability margin for such buses.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

This book presents an Artificial Neural Network (ANN) based method, involving the usage of Continuation Power Flow Methods, for on-line voltage stability assessment of power systems. A continuation power flow type algorithm is implemented through MATLAB, using the M-file programming approach along with some implementations from the "Voltage Stability Toolbox courtesy of Centre for Electric Power Engineering,Drexel University" and the Power System Analysis Toolbox. This implementation generates the nose curves, used for voltage stability analysis, for IEEE 30 bus test system which, in turn, are used as target outputs for training the ANNs, by finding the distance to voltage collapse from the current system operating point.A single feed forward type Artificial Neural Network (ANN) is to be trained for all the vulnerable load buses of the test systems.A Modal Analysis technique has been implemented to identify the most vulnerable load buses of the IEEE 30 bus test system.The trained ANN is supposed to provide, as output, the Voltage Collapse Proximity Indicators (VCPI) for all the vulnerable load buses of the system, which are a measure of the voltage stability margin for such buses.

Biographie de l'auteur

Rhythm Singh is Assistant Professor in Electrical & Electronics Engineering Department in Galgotias College of Engineering & Technology India, Chakresh Kumar is Assistant Professor in Electronics & Communication Engineering Department in Galgotias College of Engineering & Technology,India

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
VDM Verlag Dr. Müller
Date d'édition
2011
Langue
anglais
ISBN 10 
3639363744
ISBN 13 
9783639363746
Reliure
Broché
Nombre de pages
64
Coordonnées du fabricant
non disponible
Personne responsable
non disponible