DocumentCode :
2355207
Title :
Power system voltage stability analysis using ANN and Continuation Power Flow Methods
Author :
Balasubramanian, R. ; Singh, Rhythm
Author_Institution :
Centre for Energy Studies, Indian Inst. of Technol., Delhi, India
fYear :
2011
fDate :
25-28 Sept. 2011
Firstpage :
1
Lastpage :
7
Abstract :
This project 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 using the MATLAB toolbox. This implementation generates the nose curves, used for voltage stability analysis for the 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. 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.
Keywords :
load flow; neural nets; power engineering computing; power system stability; ANN; IEEE 30 bus test system; MATLAB toolbox; VCPI; artificial neural network; continuation power flow methods; continuation power flow type algorithm; on-line voltage stability assessment; power system voltage stability analysis; voltage collapse proximity indicators; Artificial neural networks; Generators; Load flow; Loading; Power system stability; Reactive power; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent System Application to Power Systems (ISAP), 2011 16th International Conference on
Conference_Location :
Hersonissos
Print_ISBN :
978-1-4577-0807-7
Electronic_ISBN :
978-1-4577-0808-4
Type :
conf
DOI :
10.1109/ISAP.2011.6082192
Filename :
6082192
Link To Document :
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