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|Title:||Power Systems Voltage Stability Using Artificial Neural Network||Authors:||Khaldi, Mohamad||Affiliations:||Department of Electrical Engineering||Keywords:||Power system stability
Power engineering computing
|Issue Date:||2008||Publisher:||IEEE||Part of:||Joint International Conference on Power System Technology and IEEE Power India Conference||Start page:||1||End page:||6||Conference:||Joint International Conference on Power System Technology and IEEE Power India Conference (12-15 Oct. 2008 : New Delhi, India)||Abstract:||
The steady-state operation of maintaining voltage stability is done by switching various controllers scattered all over the network. When a contingency occurs, whether forced or unforced, the dispatcher is to alleviate the problem in a minimum time, cost, and effort. Persistent problem may lead to blackout. The dispatcher is to have the appropriate switching of controllers in terms of type, location, and size to remove the contingency and maintain voltage stability. Wrong switching may worsen the problem and that may lead to blackout. This work proposed and used an Artificial Neural Network (ANN) to assist the dispatcher in the decision making. The ANN is used in the static voltage stability to map instantaneously a contingency to a set of controllers where the types, locations, and amount of switching are induced. The work proposes the type and architecture of the ANN to be used and the training data size.
|URI:||https://scholarhub.balamand.edu.lb/handle/uob/759||Ezproxy URL:||Link to full text||Type:||Conference Paper|
|Appears in Collections:||Department of Electrical Engineering|
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