An Artificial Neural Network Approach for Three-Zone Distance Protection
This paper presents a neural network-based approach for three-zone distance protection of transmission lines. The proposed neural-network distance relay comprises three modular identical feedforward neural networks. The first unit is trained for main protection of a transmission line section, wherea...
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Published in | International journal of modelling & simulation Vol. 25; no. 4; pp. 291 - 298 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Anaheim, CA
Taylor & Francis
01.01.2005
Calgary, AB Acta Press Zürich |
Subjects | |
Online Access | Get full text |
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Summary: | This paper presents a neural network-based approach for three-zone distance protection of transmission lines. The proposed neural-network distance relay comprises three modular identical feedforward neural networks. The first unit is trained for main protection of a transmission line section, whereas the other two units are trained to provide back-up protection for the adjacent line sections. Each neural network is fed with the fundamental frequency voltage and current magnitudes. The output of each neural unit (1 or 0) thus determines if a fault is internal or external to its protection zone. Coordination of the three neural networks and initiation of the tripping signal is implemented through a digital logic circuit. The simulation results presented in this paper show that the proposed neural-network distance relay is very effective in detection and classification of the fault location, and therefore can be considered as a good tool for main and backup digital distance protection. |
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ISSN: | 0228-6203 1925-7082 |
DOI: | 10.1080/02286203.2005.11442342 |