The current study presents a novel approach to the selective identification and localization of voltage fluctuation sources in power grids, considering individual disturbing loads changing their state with a frequency of up to 150 Hz. The implementation of the proposed approach in the existing infrastructure of smart metering allows for the identification and localization of the individual sources of disturbances in real time. The proposed approach first performs the estimation of the modulation signal using a carrier signal estimator, which allows for a modulation signal with a frequency greater than the power frequency to be estimated. In the next step, the estimated modulating signal is decomposed into component signals associated with individual sources of voltage fluctuations using an enhanced empirical wavelet transform. In the last step, a statistical evaluation of the propagation of component signals with a comparable fundamental frequency is performed, which allows for the supply point of a particular disturbing load to be determined. The proposed approach is verified in numerical simulation studies using MATLAB/SIMULINK and in experimental studies carried out in a real low-voltage power grid. The research carried out shows that the proposed approach allows for the selective identification and localization of voltage fluctuation sources changing their state with a frequency of up to 150 Hz, unlike other methods currently used in practice.