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

S. K. Salman, David J. King

Research output: Contribution to conference › Abstract

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 languageEnglish
StatePublished - 2003
Event38th International Universities Power Engineering Conference - Thessaloniki, Greece

Conference

Conference38th International Universities Power Engineering Conference
Abbreviated titleUPEC 2003
CountryGreece
CityThessaloniki
Period1/09/03 → 3/09/03

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Neural networks
Testing
Public utilities
Artificial intelligence
Control systems

Cite this

Salman, S. K., & King, D. J. (2003). Investigation into the application of artificial neural networks for detecting loss of mains conditions. Abstract from 38th International Universities Power Engineering Conference, Thessaloniki, Greece.

Salman, S. K.; King, David J. / Investigation into the application of artificial neural networks for detecting loss of mains conditions.

2003. Abstract from 38th International Universities Power Engineering Conference, Thessaloniki, Greece.

Research output: Contribution to conference › Abstract

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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",

}

Salman, SK & King, DJ 2003, 'Investigation into the application of artificial neural networks for detecting loss of mains conditions' 38th International Universities Power Engineering Conference, Thessaloniki, Greece, 1/09/03 - 3/09/03, .

Investigation into the application of artificial neural networks for detecting loss of mains conditions. / Salman, S. K.; King, David J.

2003. Abstract from 38th International Universities Power Engineering Conference, Thessaloniki, Greece.

Research output: Contribution to conference › Abstract

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

ER -

Salman SK, King DJ. Investigation into the application of artificial neural networks for detecting loss of mains conditions. 2003. Abstract from 38th International Universities Power Engineering Conference, Thessaloniki, Greece.