Identification of voltage quality problems under different types of Sag/Swell faults with Fast Fourier Transform analysis

Typical power quality (PQ) disturbances include sag, swell, harmonics, transients and temporary, momentary and sustained interruptions in a power distribution network. Among all these disturbances, sags and swells get prime importance, as they can cause sufficient damage to industrial consumer's equipment and can ultimately lead to shut down of their system. To be able to detect existence of sag, swell and identify its cause for determining mitigation options, Due to the correlativity and redundancy of the features, the identification method for voltage sag and swell disturbance source is low accuracy, to determine the probable origin of the event leading to the voltage sag. It is usual to have power quality related events, more specifically a sag or swell, surfacing at the distribution level due to a fault at the transmission level. This paper presents a new approaches for the identification and analysis of the two main power quality parameters (sags and swells) using Fast Fourier Transform analysis. The proposed Fast Fourier Transform is modeled in such a way that to identify the type of fault, duration of fault and the depth of fault. The simulation results show that comprehensive feature indices with less time requirement for identification and the identification accuracy which is obtained using FFT analysis indices is higher than the conventional identification features indices in the classification and identification of disturbance sources of voltage sag and swell under different types of symmetrical and un-symmetrical fault conditions.