Due to the highly increasing integration of renewable energy sources with the power grid and their fluctuations, besides the recent growth of new power electronics equipment, the noise in power systems has become colored. The colored noise affects the methodologies for power quality parameters’ estimation, such as harmonic and interharmonic components. Estimation of signal parameters via rotational invariance techniques (ESPRIT) as a parametric technique with high resolution has proven its efficiency in the estimation of power signal components’ frequencies, amplitudes, and phases for quality analysis, under the assumption of white Gaussian noise. Since ESPRIT suffers from high computational effort, filter bank ESPRIT (FB-ESPRIT) was suggested for mitigation of the complexity. This manuscript suggests FB-ESPRIT as well for accurate and robust estimation of power signal components’ parameters in the presence of the colored noise. Even though the parametric techniques depend on the Gaussianity of contaminating noise to perform properly, FB-ESPRIT performs well in colored noise. The FB-ESPRIT superiority compared with the conventional ESPRIT and MUSIC techniques was demonstrated through many simulations runs on synthetic power signals with multiple harmonics, interharmonics, and subharmonic components in the presence of noises of different colors and different SNR levels. FB-ESPRIT had a significant efficiency superiority in power quality analysis with a wide gap distance from the other estimators, especially under the high level of colored noise.

This paper presents and discusses the concepts of a gapless-power-quality disturbance recorder (G-PQDR) and a novelty detector. In the G-PQDR, power signals are divided into continuous frames and the energy difference between an actual frame and a reference frame is used for comparison. If the current frame is different from the reference frame, it will be recorded in the equipment and it becomes the new reference frame; otherwise, the frame is discarded and the frequency of the fundamental component is stored. The G-PQDR is able to detect and record the waveforms of the previously known PQ disturbances as well as those of the PQ disturbances not yet observed in power systems, thanks to the novelty detection concept. This characteristic is important in the context of smart grids where hidden disturbances can be detected by this methodology. For efficient data storage by minimizing the volume of the data stored, the G-PQDR uses lossy and lossless compressors. This paper describes the entire process of detection and compression, and compares the performance of the proposed method with that of a commercial-power-quality data recorder. In addition, some of the prototype implementation details are presented.

The fundamental component synchrophasors are widely used nowadays, based on the use of phasor measurement units (PMUs), in several applications in electrical power systems. For the advancement of monitoring technology, harmonic synchrophasor estimation is still a challenge. To make it possible, it is necessary to correctly estimate the harmonic phasor (magnitude and phase of each harmonic component), mainly in scenarios with frequency deviations and noise. In this context, this present article proposes the use of B-spline-based interpolation as a preprocessing algorithm for the discrete Fourier transform (DFT). The performance is evaluated in terms of total vector error (TVE) considering the tests proposed by the IEEE C37.118.1 and IEC 60255-118-1 standards and compared with four different harmonic phasor estimation (HPE) methods, the HPE, sinc interpolation function-based estimator (SIFE), Taylor–Fourier transform (TFT), and flat-top finite impulse response (FT FIR). The proposed method can provide a TVE below 1% for all harmonic phasors, from the first to the fiftieth order, under significant frequency deviation. Also, for real-time validation, the proposed method was implemented in an industrial computer as a software routine capable of processing the signals in real time. The signals are acquired by a commercial merging unit (MU) and the samples are published using the IEC 61850 sampled values (SVs) protocol.

This paper introduces an interconnected type-1 fuzzy algorithm which is trained by a modified version of the Scaled Conjugated Gradient method for impulsive noise cancellation in discrete multitone/orthogonal frequency-division multiplexing (DMT/OFDM)-based systems for broadband power line communications. The advanced algorithm makes use of the fuzzy systems capacity of dealing with uncertainties to reduce the presence of high-power impulsive noises while the DMT/OFDM technique copes with the severe intersymbol interference observed in power line channels. As a result, for a given error probability, a high number of bits can be allotted to each subchannel due to the signal-to-noise ratio enhancements achieved by the proposed fuzzy algorithm. The simulation results show that the novel fuzzy algorithm not only achieve a high data rate, but it also outperforms the standard impulsive noises techniques and other computational intelligence-based techniques, especially in the presence of additive and high-power impulsive noises.