An Accurate Fault Detection and Classification Algorithm for Double Circuit Transmission Lines Using Artificial Neural Network
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 6
Abstract
This paper presents a new and accurate fault detection and classification strategy for double circuit transmission lines based on artificial neural network. The mutual coupling effect in double circuit transmission lines causes problems to the conventional protection relays. The nonlinearity of this effect can be solved by artificial neural networks by identifying different impressions of the fault current signals. The proposed protection method uses only the post fault current signals amplitudes from the sending end of line for the detection and classification of all types of the faults. The proposed protection method is evaluated under several fault conditions such as the fault inception angle, the fault resistance and the fault location. Thus, simulations under MATLAB environment were made on a 220KV double circuit transmission line and the simulation results show that the suggested method is able to detect and classify all possible faults to know phase-ground, phase-phase, phase-phase-ground and three-phase with a high accuracy degree under varying system conditions.
Authors and Affiliations
Ankush kohale, Mr. Lumesh Kumar Sahu
Keywords
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- EP ID EP24694
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