Classification of Faults in Power Transmission Lines Using Artificial Neural Networks

This paper shows a new approach to determine the presence of defects and to classify the defect type online based on Artificial Neural Networks (ANNs) in electrical power system transmission lines. This algorithm uses current and voltage signals sampled at 1 KHz as an input for the proposed ANNs without the involvement of a moving data window, so input data will be processed as a string of data. The model depends on three neural networks one for each phase and another fourth neural network for the involvement of the ground during the fault. Response time of the classifier is less than 5 ms. Moreover modern power system requires a fast, robust and accurate technique for online processing. Simulation studies show that the proposed technique is able to distinguish the fault type very accurate. Also this technique succeeded in determining of all defect types under all system conditions, so it is 100 percent accurate, so it is suitable for online application.