Advanced distance protection scheme for long Transmission lines in Electric Power systems using multiple classified ANFIS networks

The advanced application of artificial intelligent approaches was introduced recently in protection of transmission line in Electric Power Systems (EPS). These approaches started with introducing Fuzzy Logic (FL) in the last decades of the last century. Furthermore, Artificial Neural Network (ANN) was introduced to tackle different problems in EPS. One of these important problems is the protection of transmission line with different lengthes. In this proposed research, the application of Adaptive Neuro-Fuzzy Inference System (ANFIS) for Distance Relay Protection for long Transmission line in Electrical Power Systems (EPS) will be introduced and discussed. The proposed approach focuses on fault detection, classification, and location in long Transmission lines. Furthermore, all these issues will be addressed in details. The ANFIS can be viewed as a fuzzy system, a neural network or fuzzy neural network. The objective of this paper is applying the ANFIS technique on protection of long Transmission lines. It aims; firstly, to detect the fault occurrence in very short time and isolate the faulty section of the long transmission lines. Secondly to classify the fault type and deduce which of the three phases are exposed to the fault. Finally, locating the fault will be achieved easily even the procedure here is completely different from short and medium transmission lines. The input data of the ANFIS detection units are firstly derived from the fundamental values of the voltage and current measurements (using digital signal processing via Fourier transform).