LAUSR

In this work, an accurate estimation of the amplitudes and frequencies of the flicker components has been proposed using dynamic mode decomposition (DMD). The proposed method consists of Hilbert transform for envelope extraction, DMD for spectral analysis, and finally, the assessment of flicker severity index ( $\Delta {V_{10}}$ ) based on the eye-brain model. The DMD method constructs a shifted-stack matrix of the voltage signal, and thereby it is processed through singular value decomposition (SVD) for extracting the dominant signal parameters. To verify the effectiveness of the proposed technique, voltage flickers are considered with single flicker and multiple flicker components. It is also investigated in presence of sensitive conditions such as harmonic disturbance, power frequency deviation, noisy environment, phase jumps, and transients. The simulation results are compared with the existing techniques in terms of the relative errors of flicker parameters. Finally, a hardware prototype is developed for practical flicker measurement and the proposed algorithm has been implemented on the Raspberry pi board. The experimental results are presented and compared with simulation findings of the proposed technique to prove its applicability.