Name
Abstract | ||
|---|---|---|
The main objective of this paper is the implementation of an alternative protection model to transmission lines applying Artificial Neural Networks (ANN). An improvement in performance to the conventional distance relay is expected once the ANNs can learn the different fault conditions as well as network changes in order to operate in less rime correctly: In this work, the relay protection zone (96% of a transmission line length) was determined by forward and reverse single-line-to-ground fault condition. The input data shows the trip/no trip decision of a protection system. The approach used in this paper utilizes the voltage and current post-fault samples as input to a moving data window. The implemented neural network should capture the knowledge for the correct relay operation facing the different network conditions. |
Year | DOI | Venue |
|---|---|---|
1998 | 10.1109/SBRN.1998.731040 | SBRN |
Keywords | Field | DocType |
artificial neural network applied,power system protection,artificial neural network,artificial neural networks,neural networks,transmission lines,mathematics,neural network,power transmission lines,transmission line,neural nets,protective relaying,solids | Telecommunications,Computer science,Electronic engineering,Electric power transmission,Artificial intelligence,Artificial neural network,Network conditions,Protection system,Pattern recognition,Transmission line,Voltage,Power-system protection,Relay | Conference |
ISBN | Citations | PageRank |
0-8186-8629-4 | 0 | 0.34 |
References | Authors | |
1 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| M. Oleskovicz | 1 | 0 | 0.68 |
| D. Coury | 2 | 1 | 1.45 |
| A. Carvalho | 3 | 0 | 0.34 |