Investigation into the application of artificial neural networks for detecting loss of mains conditions

S. K. Salman; David J. King

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

Original language	English
Publication status	Published - 2003
Event	38th International Universities Power Engineering Conference - Aristotle University of Thessaloniki, Thessaloniki, Greece Duration: 1 Sep 2003 → 3 Sep 2003

Conference

Conference	38th International Universities Power Engineering Conference
Abbreviated title	UPEC 2003
Country/Territory	Greece
City	Thessaloniki
Period	1/09/03 → 3/09/03

Cite this

@conference{8b2ddc09208143e7a8b859d433768101,

title = "Investigation into the application of artificial neural networks for detecting loss of mains conditions",

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",

author = "Salman, {S. K.} and King, {David J.}",

year = "2003",

language = "English",

note = "38th International Universities Power Engineering Conference, UPEC 2003 ; Conference date: 01-09-2003 Through 03-09-2003",

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TY - CONF

T1 - Investigation into the application of artificial neural networks for detecting loss of mains conditions

AU - Salman, S. K.

AU - King, David J.

PY - 2003

Y1 - 2003

N2 - 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

AB - 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

M3 - Abstract

T2 - 38th International Universities Power Engineering Conference

Y2 - 1 September 2003 through 3 September 2003

ER -

Investigation into the application of artificial neural networks for detecting loss of mains conditions

Abstract

Conference

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