Comparison of Empirical Mode Decomposition and Wavelet Transform for Power Quality Assessment in FPGA

This paper focused on the execution of a new field-programmable gate array (FPGA) based method for a signal processing algorithm to detect power quality disturbance in real-time for a grid-connected PV system. The real-time implementation of a signal processing algorithm to detect disturbances is still under the premature stage. To demonstrate the grid and distribution generation disturbances scenario in real-time, a PV connected with the emulated grid is taken into consideration for experiment analysis, which is capable to replicate the grid's behavior under normal operating conditions. Discrete Wavelet Transform (DWT), Empirical Mode Decomposition (EMD) and Hilbert transform (HT) are a novel signal analysis technique which decomposes the signals into a different frequency component and extract hidden features of the signal to detect the disturbances. In the noisy scenario, DWT performance is deteriorated compared to EMD. Hilbert transform is applied to 1st IMF of EMD to gain instantaneous amplitude and phase of the signal.