IJEBM | Analysis of Distance Protection for EHV Transmission Lines Using Artificial Neural Network

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Analysis of Distance Protection for EHV Transmission Lines Using Artificial Neural Network

Ezema C.N , Iloh J.P.I , Obi P.I.

International Journal of Engineering, Business And Management(IJEBM), Vol-1,Issue-2, July - August 2017, Pages 1-14 ,

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Abstract:

The main goal of this work is to locate fault in an electric power system with the optimal practically achievable accuracy. The method employed in this work makes use of phase voltages and phase currents (scaled with respect to their pre-fault values) as inputs to the neural networks. Typical faults such as single line-ground, line-line, double line-ground and three phase faults were considered and separate Artificial Neural Networks (ANNs) have been proposed for each of these faults. Since Back Propagation neural networks are very efficient when a sufficiently large training data set is available, it has been chosen for all the three steps in the fault location process namely fault detection, classification and fault location. The average and the maximum error percentages are in tolerable ranges and hence the networkâ€™s performance is considered satisfactory. It can be seen that there is a steady decrease in the gradient and also that the number of validation fails did not exceed 1 during the entire process which indicates smooth and efficient training because the validation and the test phases reached the Mean Square Error performance (MSE) goal at the same time approximately.

Keywords:

Double-Circuit Line Fault, Ground Fault Location, Line â€“ Line Faults, Fault Location Algorithms.

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