Detection and Position Location of Partial Ddischarges in Transformer Using Advanced Acoustic and Electromagnetic Signal Based Technique

Abstract

Results and discussion: newlineSignal propagation in circular, octagonal, hexagonal and point shaped obstacles analyzed. Simulation work extended with aluminum ceramic, iron, and mica material to understand the effect of the material on signal propagation. newlineSensor based acoustic emission technique implemented for PD detection. To detect PD source location after detection, it is critical to find the exact location of PD source in the equipment. Research work proposed use of Adaptive GWO algorithm for localization of PD source using acoustic emission technique. A novel randomization technique termed adaptive technique is integrated with GWO and exercised on unconstraint test benchmark function and accurate location of partial discharge in the transformer. Integration of new randomization adaptive technique provides potential to GWO algorithm to attain optimal global solution and faster convergence. A simulation carried out in 5000mm X 3000mm X 4000mm dimension problem space, actual PD source coordinate at (4500, 2600, 3700) and obtained PD source coordinates by AGWO is at (4398.06, 2475.49, 3664.26). Percentage error in x, y and z coordinates is 2.265%, 4.778%, and 0.965% respectively. An AGWO result (Comprehensive error is 164.83mm) is more accurate than Genetic Algorithm (Comprehensive error is 398.10mm) and Quantum Genetic Algorithm (Comprehensive error is 168.45 mm) (27). As well results of AGWO is superior to Particle Swarm Optimization (Comprehensive error is 181.55mm), Linear PSO algorithm (Comprehensive error is 182.99mm) and Simulated Annealing (SA) algorithm (Comprehensive error is 174.94mm). Also, AGWO (elapsed time is 126.52 sec.) is faster than GWO (elapsed time is 168.39 sec.) based PD localization technique. newline