Fault Identification in Sub-Station by Using Neuro-Fuzzy Technique - Anirudh Yadav; Vinay Kumar Harit (Institute of Advanced Engineering and Science, 2017)
Fault identification and its diagnosis is an important issue in present scenario of power system, as huge amount of electric power is utilized. Random types of faults occur in substation, which leads to irregular and discontinue supply of power from generating to consumer point. Fault detection is an important concept of power system which is to be studied and new method has to develop for fault detection and removal of it. This paper proposed on-line fault detection and identification of fault-type by using Neuro-Fuzzy method in substation. Combination of Artificial Neural Network (ANN) and Fuzzy Logic (FL), results in gaining learning capabilities of fuzzy logic. Variation of current according to fault is used for identification. Fuzzy controller display output condition in form of (0,1).Here, single line-to ground (LG) fault, line-to-line (LL) fault, double line-to ground (LLG)/ LLL fault are considered.