Abstract
| 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 |
| State | Published - 2003 |
| Event | 6th International Power Engineering Conference - Singapore, Singapore |
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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Development of an artificial neural network based relay to detect islanding condition of embedded generation. / Salman, S. K.; King, David J.
Proceedings of the 6th International Power Engineering Conference. Singapore : Nanyang Technological University, 2003. p. 75-80.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - CHAP
T1 - Development of an artificial neural network based relay to detect islanding condition of embedded generation
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 - Conference contribution
SN - 9810487908
SP - 75
EP - 80
BT - Proceedings of the 6th International Power Engineering Conference
PB - Nanyang Technological University
ER -