A spectral decomposition-based approach is proposed to estimate the light flicker caused by electrical arc furnaces (EAFs) where the system frequency deviates significantly due to the EAF operation. Analytical expressions of the instantaneous light flicker sensation are obtained beginning from a voltage waveform and these expressions are used to obtain a flicker estimation method based on the IEC flickermeter. In the proposed method, the leakage effect of the FFT algorithm due to fundamental frequency variation is reduced by employing a spectral amplitude correction around the fundamental frequency. The eye-brain weighting curve is realised comparing the voltage spectrum with the tabulated normalised IEC flickermeter responses for sinusoidal voltage fluctuations of the IEC standard. The proposed method is tested on both simulated data and field data obtained from three different EAF plants. The comparison with the digital realisation of the IEC flickermeter shows that the method gives satisfactory estimations of both the instantaneous flicker sensation and the short term flicker severity with low computational complexity. The method is especially useful for all other conditions such as disturbances and subsequent system transients where the system frequency deviates without the need for online sampling rate adjustment.