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