Artificial Neural Network Application in Optimal Coordination of Directional Overcurrent Protective Relays in Electrical Mesh Distribution Network

Abstract:

Directional Overcurrent relays (DOCR) applications in meshed distribution networks (MDN), eliminate short circuit fault current due to the topographical nature of the system. Effective and reliable coordination’s between primary and secondary relay pairs ensures effective coordination achievement. Otherwise, the risk of safety of lives and installations may be compromised alongside with system instability. This paper proposes an Artificial Neural Network (ANN) approach of optimizing the system operation response time of all DOCR within the network to address miscoordination problem due to wrong response time among adjacent DOCRs to the same fault. A modelled series of DOCRs in a simulated IEEE 8-bus test system in DigSilent Power Factory with extracted data from three phase short circuit fault analysis adapted in training a custom ANN. Hence, an improved optimized time is produced from the network output to eliminate miscoordination among the DOCRs.

• Periodical: Applied Mechanics and Materials (Volume 785)
• Pages: 48-52
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.785.48
• Online since: August 2015
• Authors: Osaji Emmanuel*, Mohammad Lutfi Othman, Hashim Hizam, Muhammad Murtadha Othman
• Keywords: Artificial Neural Networks, Directional Overcurrent Relay, Meshed Distribution Networks

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