IJERT-EMS
IJERT-EMS

Performance Determination and Limitations of the Conventional Impedance Relay Operation for Improving the Protection of Transmission Lines


Performance Determination and Limitations of the Conventional Impedance Relay Operation for Improving the Protection of Transmission Lines
Authors : Eneh Maxwell E. , E. N. C Okafor, Alor Michael Onyeamaechi, Eneh Victor I.
Publication Date: 27-08-2017

Authors

Author(s):  Eneh Maxwell E. , E. N. C Okafor, Alor Michael Onyeamaechi, Eneh Victor I.

Published in:   International Journal of Engineering Research & Technology

License:  This work is licensed under a Creative Commons Attribution 4.0 International License.

Website: www.ijert.org

Volume/Issue:   Volume. 6 - Issue. 08 , August - 2017

e-ISSN:   2278-0181

Abstract

This paper presented a survey of the performance and limitations of conventional impedance relay operation for improving the protection of transmission line. The fundamentals of transmission lines protection were considered many years ago but theoretical principles as well as the practical applications are still common topics of investigation in power system protection. Particular emphasis has been put in establishing the drawbacks inherent in conventional impedance relay used in most transmission line protection. The convention impedance relay is usually designed on the basis of fixed relay settings. The reach accuracy of the protective relay can therefore be affected by the different fault conditions as well as network configuration changes. The Statistical Package for Social Science (SPSS) analytical approach was used for the analysis of the relay performance. Historical field data provided by Transmission Company of Nigeria was used for the analysis. The result presented in this paper indicates that conventional impedance relay has an operation accuracy of 65.2% in terms of fault location which indicates the need for improvement as to reduce the outage duration. In view of the result, an artificial intelligent technique such as Neural Network, Fuzzy logic System , Genetic Algorithm or combination of any of the two techniques were recommended as an improved technique based on it perfect pattern recognition and decision making ability.

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