PD source location utilizing acoustic TDOA signals in power transformer by fuzzy adaptive Particle Swarm Optimization

Abstract

Partial discharge (PD) source location using acoustic emission (AE) is widely utilized by many trans former manufacturers and power utility engineers in rou tine and critical situation for optimal operation of the electrical power system as well as further risk management and repair planning. The PD detection is not enough to take solution, so identification of PD source is essential to restore apparatus condition. This work aim is to localize the defect geometrically by means of TDOA (time differ ence of arrival) signals from the sensors fixed on the power transformer. The solution for PD source location is ac quired by making these nonlinear equations as optimiza tion problem. In this technique, the inertia weight is effec tively regulated by using 49 and 9 simple IF-THEN fuzzy rules to improve the global optimal solution and impairs the local convergence problem and improves the accuracy in estimating the PD source location. The simulation re sults reveal that PD location accuracy with minimum of maximum deviation error, absolute error and relative error is better when compared to other constant parameter intelligent methods which were reported in the literature.