Phasor Estimation for Grid Power Monitoring: Least Square vs. Linear Kalman Filter

International audienc

Theory and application of time-frequency analysis to transient phenomena in electric power and other physical systems

textThis dissertation provides a new theoretical scheme of signal processing: cross time-frequency analysis. The proposed cross time-frequency analysis is applied to various types of real-world signals and systems in order to verify the feasibility and applicability of the proposed theory. The application of time-frequency analysis is focused on electric power and other physical systems. Unfortunately, classical Fourier-based methodologies and power quality indices are not directly applicable for the assessment and localization of transient power quality phenomena. Hence, in this dissertation, application of time-frequency analysis is discussed for the assessment and localization of transient power quality events. Through the use of joint time and frequency localized “energy” distributions, a set of time-frequency based transient power quality indices are presented and applied to real-world disturbance signals. Also, a solution for the spatial localization of transient disturbances is presented. It rests upon calculating a time and frequency localized “phase difference” via cross time-frequency analysis. By evaluating the phase difference of voltage and current at the time and frequency of interest and at different spatial points, one can identify the direction of transient disturbance energy flow in order to pinpoint the location of the transient disturbance source. In addition, applications of time-frequency theory have been extended to various types of real-world physical signals and systems. A new reflectometry methodology, time-frequency domain reflectometry, is proposed and demonstrated with experimental results. Also, cross time-frequency analysis has been utilized for the characterization of ocean wave group propagation, and applied to transient postural sway signals to identify the effects of aging and sensory systems on human postural control systems.Electrical and Computer Engineerin

Comprehensive Review on Detection and Classification of Power Quality Disturbances in Utility Grid With Renewable Energy Penetration

The global concern with power quality is increasing due to the penetration of renewable energy (RE) sources to cater the energy demands and meet de-carbonization targets. Power quality (PQ) disturbances are found to be more predominant with RE penetration due to the variable outputs and interfacing converters. There is a need to recognize and mitigate PQ disturbances to supply clean power to the consumer. This article presents a critical review of techniques used for detection and classification PQ disturbances in the utility grid with renewable energy penetration. The broad perspective of this review paper is to provide various concepts utilized for extraction of the features to detect and classify the PQ disturbances even in the noisy environment. More than 220 research publications have been critically reviewed, classified and listed for quick reference of the engineers, scientists and academicians working in the power quality area

Performance of Modified S-Transform for Power Quality Disturbance Detection and Classification

Detection and classification of power quality (PQ) disturbances are an important consideration to electrical utility companies and many industrial customers so that diagnosis and mitigation of such disturbance can be implemented quickly. Power quality signal consists of stationary and non-stationary events which need a robust signal processing technique to analyse the signals. In this paper, Modified STransform (MST) was used to analyse single and multiple power quality signals. MST is a modified version of S-transform with improved time-frequency resolution. The power quality signals that are considered in this study are voltage swell, sag, interruption, harmonic, interharmonic, transient, sag plus harmonic and swell plus harmonics. The performance of the proposed method has been studied under noisy and unnoisy condition. Hard thresholding technique has been applied with MST while analysing noisy PQ signals. The result shows that MST is able to give higher classification rate with better time and frequency distribution (TFD) spectrum of the PQ disturbances.

Power System Transients: Impacts of Non-Ideal Sensors on Measurement-Based Applications

The power system is comprised of thousands of lines, generation sources, transformers, and other equipment responsible for servicing millions of customers. Such a complex apparatus requires constant monitoring and protection schemes capable of keeping the system operational, reliable, and resilient. To achieve these goals, measurement is a critical role in the continued functionality of the power system. However, measurement devices are never completely reliable, and are susceptible to inherent irregularities; imparting potentially misleading distortions on measurements containing high-frequency components. This dissertation analyzes some of these effects, as well as the way they may impact certain applications in the grid that utilize these kinds of measurements. This dissertation first presents background on existing measurement technologies currently in use in the power grid, with extra emphasis placed on point-on-wave (PoW) sensors, those designed to capture oscillographic records of voltage and current signals. Next, a waveform “playback” system, developed at Oak Ridge National Laboratory’s Distributed Energy Communications \& Control (DECC) laboratory was used for comparisons between various line-post-monitor PoW sensors when subjected to different high-frequency current disturbances. Each of the three sensors exhibited unique quirks in these spectral regions, both in terms of harmonic magnitude and phase angle. A goodness-of-fit metric for comparing an ideal reference sensor with the test sensors was adopted from the literature and showed the extremes to which two test sensors vastly under performed when compared to the third. The subsequent chapter analyzes these behaviors under a statistical lens, using kernel density estimation to fit probability density functions (PDFs) to error distributions at specific harmonic frequencies resulting from sensor frequency response distortions. The remaining two chapters of the dissertation are concerned with resultant effects on applications that require high-frequency transient data. First, a detection algorithm is presented, and its performance when subjected to statistical errors inherent in these sensors is quantified. The dissertation culminates with a study on an artificial intelligence (AI) technique for estimating the location of capacitor switching transients, as well as learning prediction intervals that indicate the level of uncertainty present in the data caused by sensor frequency response irregularities

Lead Acid Battery Analysis using S-Transform

This paper proposes a new signal processing technique using time-frequency distribution (TFD), namely S-transform (ST) for battery parameters estimation. Compared to other TFDs such as short time Fourier transform (STFT) and wavelet transform (WT), ST technique offers more promising results in a low frequency application analysis, especially battery. The results of the ST are the parameters of instantaneous means square voltage (VRMS (t)), instantaneous direct current voltage (VDC (t)) and instantaneous alternating current voltage (VAC (t)) extracted from the time-frequency representation (TFR). Simulation through MATLAB has been conducted using equivalent circuit model (ECM), using 12 V lead acid (LA) battery with capacities from 1.0 Ah to 10.0 Ah. For the battery model, charging/discharging signal has been used to estimate the battery parameters from the ST technique to determine battery characteristics. From the signal characteristics of battery capacity versus VAC (t) obtained, new equation is proposed based on the curve fitting tool. The advantage of this technique embraces a better capability in estimating battery parameters at low frequency component, resulting in better frequency and time resolutions compared to previous TFDs

Three-phase phase-locked loop synchronization algorithms for grid-connected renewable energy systems:A review

The increasing penetration of distributed renewable energy sources (RES) requires appropriate control techniques in order to remain interconnected and contribute in a proper way to the overall grid stability, whenever disturbances occur. In addition, the disconnection of RES due to synchronization problems must be avoided as this may result in penalties and loss of energy generation to RES operators. The control of RES mainly depends on the synchronization algorithm, which should be fast and accurately detect the grid voltage status (e.g., phase, amplitude, and frequency). Typically, phase-locked loop (PLL) synchronization techniques are used for the grid voltage monitoring. The design and performance of PLL directly affect the dynamics of the RES grid side converter (GSC). This paper presents the characteristics, design guidelines and features of advanced state-of-the-art PLL-based synchronization algorithms under normal, abnormal and harmonically-distorted grid conditions. Experimental tests on the selected PLL methods under different grid conditions are presented, followed by a comparative benchmarking and selection guide. Finally, corresponding PLL tuning procedures are discussed.This work was supported by the supported by the Research Promotion Foundation (RPF) of Cyprus under Project KOINA/SOLAR-ERA.NET/1215/06