Hybrid meta heuristic and fuzzy impedance method for fast fault location in power system lines

This study discusses a new and accurate fault location method for power system lines in power networks. The exact location of the fault and the distance of the line from one end are determined by training the proposed positioning system with experimental reference data. Phasor measurement units (PMUs) at one end of the power line effectively monitor the entire system. First, the types of problems are identified and categorized using the PMU measurement signals. The fault location was then diagnosed using a nonlinear modeling technique to locate the fault based on the impedance of one end. Two non-linear fault locating estimation methods are described based on the fuzzy logic system and the fifth-order Taylor expansion polynomial fitting system. The samples have been used to train the parameters of the proposed positioning systems using the Fire Hawk Optimizer (FHO) algorithm. Therefore, the objective is to determine the distance at which the fault occurs, locate the fault spot precisely, and determine the distance from the PMU at the end of the line. The three-bus system for a 200 km long, 220 kV power line has been assessed and verified using the Simulink environment of MATLAB software. The results show how effective the proposed method is at locating the exact location of the power line issue with the least amount of error in a PMU. Finally, with an execution duration of less than 0.16 s, the method has shown a high search speed on a case study model.