Condition: New. pp. 300.
Condition: New. pp. 300 First Edition NO-PA16APR2015-KAP.
Condition: New. pp. 300.
Language: English
Published by VDM Verlag Dr. Müller, 2011
ISBN 10: 3639363744 ISBN 13: 9783639363746
Seller: Devils in the Detail Ltd, Oxford, United Kingdom
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Language: English
Published by VDM Verlag Dr. Müller, 2011
ISBN 10: 3639363744 ISBN 13: 9783639363746
Seller: preigu, Osnabrück, Germany
Taschenbuch. Condition: Neu. Online Voltage Stability Assessment Using ANN and Continuation Power Flow | Using AI for Real-time Analysis | Rhythm Singh (u. a.) | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639363746 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Language: English
Published by VDM Verlag Dr. Müller, 2011
ISBN 10: 3639363744 ISBN 13: 9783639363746
Seller: Mispah books, Redhill, SURRE, United Kingdom
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Language: English
Published by VDM Verlag Dr. Müller, 2011
ISBN 10: 3639363744 ISBN 13: 9783639363746
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Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Singh RhythmRhythm Singh is Assistant Professor in Electrical & Electronics Engineering Department in Galgotias College of Engineering & Technology India, Chakresh Kumar is Assistant Professor in Electronics & Communication Engineer.
Language: English
Published by VDM Verlag Dr. Müller, 2011
ISBN 10: 3639363744 ISBN 13: 9783639363746
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.