Moisés Vidal Ribeiro

Bridging the gap between signal and power

This article focuses on problems and issues related to PQ and power system diagnostics, in particular those where signal processing techniques are extremely important. PQ is a general term that describes the quality of voltage and current waveforms. PQ problems include all electric power problems or disturbances in the supply system that prevent end-user equipment from operating properly.

Detection of disturbances in voltage signals for power quality analysis using HOS

This paper outlines a higher-order statistics (HOS)-based technique for detecting abnormal conditions in voltage signals. The main advantage introduced by the proposed technique refers to its capability to detect voltage disturbances and their start and end points in a frame whose length corresponds to, at least, samples or of the fundamental component if a sampling rate equal to Hz is considered. This feature allows the detection of disturbances in submultiples or multiples of one-cycle fundamental component if an appropriate sampling rate is considered. From the computational results, one can note that almost all abnormal and normal conditions are correctly detected if s256, 128, 64, 32, and 16 and the SNR is higher than 25 dB. In addition, the proposed technique is compared to a root mean square (rms)-based technique, which was recently developed to detect the presence of some voltage events as well as their sources in a frame whose length ranges from up to one-cycle fundamental component. The numerical results reveal that the proposed technique shows an improved performance when applied not only to synthetic data, but also to real one.

The Compression of Electric Signal Waveforms for Smart Grids: State of the Art and Future Trends

In this paper, we discuss the compression of waveforms obtained from measurements of power system quantities and analyze the reasons why its importance is growing with the advent of smart grid systems. While generation and transmission networks already use a considerable number of automation and measurement devices, a large number of smart monitors and meters are to be deployed in the distribution network to allow broad observability and real-time monitoring. This situation creates new requirements concerning the communication interface, computational intelligence and the ability to process data or signals and also to share information. Therefore, a considerable increase in data exchange and in storage is likely to occur. In this context, one must achieve an efficient use of channel communication bandwidth and a reduced need of storage space for power system data. Here, we review the main compression techniques devised for electric signal waveforms providing an overview of the achievements obtained in the past decades. Additionally, we envision some smart grid scenarios emphasizing open research issues regarding compression of electric signal waveforms. We expect that this paper will contribute to motivate joint research efforts between electrical power system and signal processing communities in the area of signal waveform compression.

A PLL-Based Multirate Structure for Time-Varying Power Systems Harmonic/Interharmonic Estimation

This paper describes a phase-locked-loop (PLL)-based power systems harmonic estimation algorithm, which uses an analysis filter bank and multirate processing. The filter bank is composed of bandpass filters. The initial center frequency of each filter is purposely chosen to be equal to harmonic frequencies. However, an adaptation strategy makes it possible to track time-varying frequencies as well as interharmonic components. A downsampler device follows the filtering stage, reducing the computational burden, especially because undersampling operations are performed. Finally, the last stage is composed of a PLL estimator which provides estimates for amplitude, phase, and frequency of the input signal. The proposed method improves the accuracy, computational effort, and convergence time of the previous harmonic estimator based on cascade PLL configuration.

Power quality event detection based on the divide and conquer principle and innovation concept

The aim of this paper is to introduce a novel real-time digital signal processing technique for power quality disturbance detection. The proposed technique is inspired on the Divide and Conquer Principle and on the Innovation Concept. Essentially, the Divide and Conquer Principle is applied in splitting the monitored disturbance event into stationary and nonstationary components, allowing localized individual signal analysis. Thereafter, the Innovation Concept is introduced for revealing new information not previously observed in the energy of the nonstationary signals and so detecting a new event. In addition, this paper demonstrates a straightforward and feasible way to evaluate the Total Harmonic Distortion (THD) or a distortion measure for voltage signals. Simulation results indicate that the proposed technique is able to accurately detect a variety of voltage disturbances.

A Novel MDL-based Compression Method for Power Quality Applications

This paper introduces a novel source coding method for voltage and current signals, called fundamental, harmonic and transient coding method (FHTCM), which is a generalization of the enhanced disturbance compression method (EDCM). The proposed method makes use of notch filtering-warped discrete Fourier transform (NF-WDFT) technique for estimating the parameters (amplitude, frequency, and phase) of the fundamental and harmonic components acquired from power lines so that only the transient components are compressed with wavelet transform (WT) coding technique. For the WT-based compression of transient components, we formulate a minimum description length (MDL) criterion, taking into account the selection of wavelet bases in a dictionary, wavelet decomposition structure, and quantization. Computational simulations have verified that the proposed method outperforms the EDCM as well as the traditional WT-based compression techniques

An enhanced data compression method for applications in power quality analysis

This paper presents an enhanced method for data compression using a wavelet transform, to be applied in power systems signals for quality evaluation. The proposed approach is based on a previous estimation of the sinusoidal components of the signal under analysis, so that it could be subtracted from the original data in order to generate a transient type signal, which is subsequently applied to the compression techniques. The approach employs the Kalman filter and the adaptive notch filter techniques to provide the estimation of the sinusoidal components. Taking into account the wavelet property of sparse representation makes an improvement in the compression rate and in the signal degradation is attained. Finally, a proposed frame format to store the coded signal is presented.

A Controlled Filtering Method for Estimating Harmonics of Off-Nominal Frequencies

The increasing use of power electronics in power systems causes a high injection of harmonic components which can in turn interfere with utility equipment and customer loads. Therefore, the correct estimation and measurement of harmonics have become an important issue. If the power frequency of the signal is steady and near the nominal value, the discrete Fourier transform (DFT) can be used and good estimation performance is achieved. However, there are considerable power frequency variations on isolated systems such as shipboard power systems, micro-grids and smart-grids. When these variations occur there may be significant errors in the estimates using the DFT. In order to deal with this problem, this work presents a novel technique based on demodulation of the power line signal and subsequent filtering for harmonics estimation. The main features of the proposed harmonic estimation technique are: precise and accurate estimation of harmonics of off-nominal frequencies and fast estimation of harmonics (about two cycles of the fundamental component). Simulation results show that the proposed technique performs well in comparison with the DFT and can be a good candidate to replace it in cases where the power frequency is subject to considerable variations.

An improved method for signal processing and compression in power quality evaluation

This paper introduces a new waveform coding technique, based on wavelet transform, for power quality monitoring purposes. The proposed enhanced data compression method (EDCM) presents a complete adaptive signal processing approach to estimate the fundamental sinusoidal component and separate it from the transient ones in the monitored signal. When these nonstationary components are submitted to the compression technique, the sparse representation property of the wavelet transform provides an improvement in the compression ratio. Also, the degradation inserted by the lossy compression process is minimized. Simulation results confirm the effectiveness of the proposed method when compared to the standard solution, characterized by the compression of the whole monitored signal.

Clustered-orthogonal frequency division multiplexing for power line communication: when is it beneficial?

This study presents a comprehensive analysis to highlight advantages and disadvantages, in terms of channel capacity and computational complexity (CC), of a so-called clustered-orthogonal frequency division multiplexing (OFDM) scheme for power line communication (PLC) technologies for access networks. By taking into account filtering, decimation and upsampling techniques, the implementations of two transmitter schemes, named 𝒫(·)-I and 𝒫(·)-II, and three receivers ones, named 𝒬(·)-I, 𝒬(·)-II and 𝒬(·)-III, that can be easily derived from the hermitian symmetric OFDM (HS-OFDM) scheme are discussed. Numerical results show that the clustered-OFDM schemes based on HS-OFDM provide the same bit-error-rate performance as that of HS-OFDM, double sideband-OFDM and single sideband-OFDM. Also, clustered-OFDM based on the combination of 𝒬(·)-II and 𝒬(·)-III offers the lowest CC for both baseband and passband data communications. Further, it is demonstrated that the clustered-OFDM schemes can trade off channel capacity for CC, which can give rise to low-priced transceivers for PLC technologies. Finally, a comparative analysis of clustered-OFDM and orthogonal frequency division multiple access (OFDMA) points out the scenarios in which clustered-OFDM can be competitive if the complexity of the OFDM transceiver is a primary consideration.