POWER QUALITY DISTURBANCE CLASSIFICATION USING S-TRANSFORM AND FUZZY SYSTEMS ORIENTED BY PSO ALGORITHM

In this paper we designated a new method on the basis of s-transform with fuzzy logic and a particle swarm optimization (PSO) algorithm for classification of single and combined power quality (PQ) disturbances. We exploit S-transform to extract features of power quality disturbances and we used the suggested fuzzy system to group power quality events regarding the extracted features. The PSO algorithm serves to precisely show the membership function parameters for the fuzzy systems. We regard the DC offset, noise, spike, interruption, swell, sag, notch, transient, harmonic and flicker as single disturbances. Harmonic with sag, harmonic with sag with transient, harmonic with swell with transient, harmonic with transient, swell with transient and sag with transient are known as combined disturbances for the voltage signal. We studied the suggested approach’s power to find these PQ disturbances as well when white Gaussian noise, with various signal to noise ratio (SNR) values, is added to the waveforms. In the simulation results part, it is shown that the suggested method possesses good average rate of accurate identification for various PQ disturbances.