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Please use this identifier to cite or link to this item: http://hdl.handle.net/10373/1281

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Title: Investigation into the application of artificial neural networks for detecting loss of mains conditions
Authors: Salman, S. K.
King, David J.
Affiliation: University of Abertay Dundee. School of Computing & Engineering Systems
Keywords: Neural networks (Computer science)
Issue Date: 2003
Publisher: Aristotle University of Thessaloniki
Type: Conference Paper
Refereed: peer-reviewed
Rights: Published version (c)Aristotle University of Thessaloniki
Citation: Salman, S.K. and King, D.J. 2003. Investigation into the application of artificial neural networks for detecting loss of mains conditions. 38th Universities Power Engineering Conference, Thessaloniki, Greece, 1-3 September 2003
Abstract: With the increase of number of embedded generators (EGs) in public utility networks the need for adequate protection schemes has become extremely important. In particular, safety problems that arise due to loss of mains (LOM), and the inability of current protection, under certain circumstances, to detect it means that there is a lot of current research into possible alternative methods for detecting LOM. Also, the use of artificial intelligence (AI) in power system operation is becoming widespread. In particular, artificial neural networks (ANN) are being developed to tackle a number of power system control and protection problems. One of the most important things to consider when using ANN is deciding upon appropriate and relevant training/testing data. This paper results from a project to find a new method of detection of LOM for EG using ANN, and outlines the methods used to develop suitable training/testing data
URI: http://hdl.handle.net/10373/1281
Appears in Collections:Computing & Engineering Systems Collection

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