Supraharmonic analysis by filter bank and compressive sensing

Abstract Smart grids encourage the use of new technologies such as electric vehicles, smart metering, as well as the use of renewable energy sources. One of the crucial challenges in designing smart grids is to improve the quality of the power delivered. Besides harmonic current generation in the frequency range below 2 kHz, these new technologies are also responsible for current emission in the range of 2–150 kHz, commonly known as supraharmonic emission. The supraharmonic analysis has not been explored for years, due to the lack of standards and equipment that are capable of reaching this frequency range. In recent years, the frequency range above 2 kHz has become the object of study by power quality researchers. This work proposes a technique to access the supraharmonics with reduced sampling rate and resolution enhancement. The technique is based on analog filter bank and compressive sensing. The use of the filter bank allows the reduction of the number of samples processed by the Fast Fourier Transform (FFT). In addition, it is proposed a method to improve frequency resolution of supraharmonic estimation, based on the technique of compressive sensing (CS). The use of the CS algorithm allows to achieve enhanced frequency accuracy without significantly extending the total observation time.