Please use this identifier to cite or link to this item:
|Title:||Neural networks and static voltage stability in power systems||Authors:||Khaldi, Mohamad||Affiliations:||Department of Electrical Engineering||Keywords:||Static VAr compensators
Power system analysis computing
Power system stability
|Subjects:||Artificial intelligence||Issue Date:||2008||Publisher:||IEEE||Part of:||IEEE International Conference on Industrial Technology||Start page:||1||End page:||6||Conference:||IEEE International Conference on Industrial Technology (21-24 April 2008 : Chengdu, China)||Abstract:||
A power system is an interconnected network of mainly generation, transmission/distribution, and consumption of electrical energy. The steady-state operation of maintaining voltage stability is done by switching various controllers scattered all over the network. Some of the common controllers are the PV or generation buses voltage magnitudes, static reactive power (VAR) compensators, and under load tap transformers. When a contingency occurs, whether forced or unforced, the dispatcher in the Energy Control Center 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. Thus, to do this intricate and delicate switching is a challenging task and requires highly experienced dispatcher. This work proposed and used an Artificial Neural Network (ANN) to assist the dispatcher in the decision making.
|URI:||https://scholarhub.balamand.edu.lb/handle/uob/702||Ezproxy URL:||Link to full text||Type:||Conference Paper|
|Appears in Collections:||Department of Electrical Engineering|
Show full item record
checked on Oct 23, 2021
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.