Development of an artificial neural network based relay to detect islanding condition of embedded generation

S. K. Salman; David J. King

Development of an artificial neural network based relay to detect islanding condition of embedded generation

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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
Title of host publication	Proceedings of the 6th International Power Engineering Conference
Place of Publication	Singapore
Publisher	Nanyang Technological University
Pages	75-80
Number of pages	6
ISBN (Print)	9810487908
Publication status	Published - 2003
Event	6th International Power Engineering Conference - Singapore, Singapore Duration: 27 Nov 2003 → 29 Nov 2003 Conference number: 6

Conference

Conference	6th International Power Engineering Conference
Abbreviated title	IPEC 2003
Country	Singapore
City	Singapore
Period	27/11/03 → 29/11/03

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@inproceedings{c57e4121863a478c9a628f652a2afba9,

title = "Development of an artificial neural network based relay to detect islanding condition of embedded generation",

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",

isbn = "9810487908",

pages = "75--80",

booktitle = "Proceedings of the 6th International Power Engineering Conference",

publisher = "Nanyang Technological University",

note = "6th International Power Engineering Conference, IPEC 2003 ; Conference date: 27-11-2003 Through 29-11-2003",

}

TY - GEN

T1 - Development of an artificial neural network based relay to detect islanding condition of embedded generation

AU - Salman, S. K.

AU - King, David J.

N1 - Conference code: 6

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 - Conference contribution

SN - 9810487908

SP - 75

EP - 80

BT - Proceedings of the 6th International Power Engineering Conference

PB - Nanyang Technological University

CY - Singapore

T2 - 6th International Power Engineering Conference

Y2 - 27 November 2003 through 29 November 2003

ER -