A signal analysis approach towards detection and classification of power quality disturbances

Massive increase in usage of semi-conductor devices, nonlinear and linear loads, power electronic converters and inverters has triggered a huge issue in power sector throughout the world. Excessive heat generation by semiconductor devices, power & data losses and equipment failure are some of the observed indications in case of poor power quality. Electrical and electronics devices are becoming smaller and more complex to power quality deviations due to the evolution of electronics industry due to which PQD has become a complete subject which is divided into two subsections identification and classification. This paper aims both sections, on the basis of outcomes of the detection, we carried out controlled experimentation to uniquely characterize multiple classes or events of power quality disturbances (PQDs) affecting the quality of supplied power. Effectiveness of the proposed methodology in discriminating PQDs can be visualized without including typical analytical tools. Due to this computational burden is minimized as compared to the prevailing approaches. All these PQ disturbances have been simulated and examined with MA TLAB software. Additionally, primary causes of this power quality disturbances have been simulated and discussed with the need of linking these with the respective power quality disturbances. The sustainability of the adapted technique is verified by both the simulation and experimentation.