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A Neuro-Fuzzy Approach for the Fault Location Estimation of Unsynchronized Two-Terminal Transmission Lines
Overhead transmission line is an element of electrical power systems that are most frequently experienced short circuit faults compared to other power system elements. Short circuit faults on overhead transmission line cause a relatively large current and therefore can damage mechanically the electrical equipment connected to the system. The protection system is essentially needed in this situation. In addition, it takes a piece of equipment that can detect the location of fault in order to expedite the repair process, especially if the fault is permanent state. In this paper, a neuro-fuzzy aprroach for short circuit fault location estimation which uses data from both ends of overhead transmission line is described. The approach utilizes the advantages of digital relaying which are available today. The unsynchronized data of fault voltages and currents at two-end of overhead transmission line is applied in this technique. The accurate fault location estimation technique has irrespective of source impedances, fault resistances, fault types, and load currents. Simulation of short circuit fault of transmission line has done by using EDSA software. Short circuit currents and voltages from both ends of overhead transmission line have used to input data of neuro-fuzzy method in Matlab program. Simulation results demonstrate the accuracy of the method. The results shows that the lowest estimation error for single phase to ground fault with the variation of fault resistances of 0 ohms, 10 ohms, 50 ohms, and 100 ohms, respectively, is 0.0027%, while the highest estimation error is 0.2962%.
Keywords
Neuro-Fuzzy, Two-Terminal Fault Location Algorithm, Transmission Line, Unsynchronized Sampling.
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