Three-phase Voltage Signals Research Articles

Comparative Analysis of Power Quality Instruments in Measuring Power under Distorted Conditions

Abstract This paper aims to evaluate the performance of commercial power quality (PQ) instruments. By using a high precision programmable voltage and current source, five meters from different manufacturers are analyzed and compared. At first, three-phase voltage signals are applied to those PQ instruments, considering harmonic distortion, voltage dip, voltage swell, as well as unbalanced voltages. These events are measured, compared and evaluated considering the different instruments. In addition, voltage and current signals are applied under different conditions, with and without harmonic and unbalances, in order to obtain the measurements of electrical power. After analyzing the data generated in all these tests, efforts are focused on establishing a relationship between the accuracy of the measurements. Considering the percentages of errors, a score is assigned to each instrument. The tests have shown “excellent” and “good” results regarding measuring active and apparent power, as well as power factor. However, for non-active power, almost all instruments had lower performance. This work is relevant considering that Brazil is deploying standardization in terms of power quality measurements aiming towards regulatory procedures and index limits.

Improved fault location algorithm for multi‐location faults, transforming faults and shunt faults in thyristor controlled series capacitor compensated transmission line

Fault location estimation in series compensated transmission lines is quite difficult because a non-linear current dependent circuit appears between the substation and fault point. In particular, the faults which occur at different locations at the same time in different phases known as multi-location faults has not been addressed by researchers. Other types of fault that may occur in transmission lines are transforming faults where one type of fault transforms to another type fault after some time. In this study, a fault location estimation scheme using artificial neural network (ANN) is presented for multi-location faults, transforming faults as well as for commonly occurring shunt faults in thyristor controlled series capacitor (TCSC) compensated transmission line. DB-4 wavelet is used for pre-processing of the three-phase current and voltage signals. The shunt capacitance of the line is considered based on distributed parameter line model. Feasibility of the ANN-based fault location algorithm is tested under a wide variation of parameters, such as fault type, location, fault resistance and fault inception angle. Fault location errors are within 0.001–1% range.

Characterizing Voltage Sags and Swells Using Three-Phase Voltage Ellipse Parameters

This paper presents an algorithm for detection, classification, and characterization of voltage sags and swells in electricity networks using three-phase voltage ellipse parameters. The proposed method employs the instantaneous magnitude of three-phase voltage signals in three axes, which are separated from each other by 120 $^{\circ} $ . Thus, the resultant rotating vector, namely, the three-phase voltage vector, traces an ellipse. Then, the parameters of the ellipse, which include minor axis, major axis, and inclination angle, are used to develop the proposed algorithm for classification and characterization of voltage sags and swells. The proposed method is validated using real data of the IEEE working group and some measured real data of the Belgian transmission grid. The method is further tested for the sags and swells generated due to balanced and unbalanced faults at different buses, in test distribution networks (radial and mesh type) embedded with distributed generation and in a practical distribution network of Australia. This paper also demonstrates the proposed algorithm as a real-time sag/swell monitoring tool.

A New Approach for Classification and Characterization of Voltage Dips and Swells Using 3-D Polarization Ellipse Parameters

This paper presents a new method for the classification and characterization of voltage dips and swells in electricity networks. The proposed method exploits unique signatures and parameters of three-phase voltage signals extracted from the polarization ellipse in 3-D coordinates. Five ellipse parameters, which include azimuthal angle, elevation, tilt, semi-minor axis, and semi-major axis, are used to classify and characterize voltage dips and swells. Seven types of voltage dips, which include a total of 19 groups of dips incorporating different kinds of balanced (three-phase dips) and unbalanced (single-phase or double-phase) dips, are identified and successfully classified using the 3-D polarization ellipse parameters. Two types of voltage swells, which include a total of 6 groups, are also classified using the proposed method. The proposed method is validated using real measurement data, recorded waveforms provided by the IEEE 1159.2 working group, and the data of unbalanced dips associated with phase-angle jumps, voltage drops, and rotations due to loading effects.

Generating Unit Model Validation and Calibration Through Synchrophasor Measurements

This paper presents a rule-based approach using synchrophasor measurements for generating unit model validation and calibration. The proposed method utilizes frequency and three-phase voltage signals recorded by phasor measurement unit at the point of common coupling of unit transformers to the high voltage grid. In the simulation setup, by taking the hybrid data simulation technique in use, the signals are being injected to the subsystem of generating units through a voltage source, which models the truncated external grid. The measured and simulated active power oscillations are then compared to each other and the effects of generating unit parameters on the oscillation mismatches are extracted. The maximum amplitude and damping ratio of oscillations are two main aspects of the observed mismatches. To recognize the most effective parameters on these aspects, a sensitivity analysis technique is applied. Next, identified parameters are adjusted to calibrate the generating unit dynamic model. Finally, quantitative and qualitative perspectives of the proposed method are investigated through different sorts of actual disturbances. The obtained results demonstrate that the final calibrated model outperforms the existing one, and it can be used for power system planning and operation studies. Time domain simulations are performed by DIgSILENT power factory software.

Power Quality Monitoring and Control Using Virtual Instrumentation System

This paper presents and develops a LabVIEW based mathematical model for power quality analysis and enhancement. The different types of power quality problems such as voltage sag, voltage swell, power frequency distortions, and harmonic distortions can be identified and controlled suitably. Besides standard undisturbed three-phase voltage signal waveforms, six different categories of the PQ disturbances characteristic for real-time power distribution networks can be simulated on the basis of developed virtual instruments: voltage swells, sags, interruptions, high-order voltage harmonics, swells with harmonics and sags with harmonics. Each of simulated PQ disturbances can be predefined and easily changed according to user requirements, using various combinations of the control settings implemented on the virtual instrument front panel. All computations are carried out using LabVIEW 9.0.

Optimal feature selection for classification of the power quality events using wavelet transform and least squares support vector machines

In this paper, a new optimal feature selection based power quality event recognition system is proposed for the classification of power quality events. While Apriori algorithm is capable of processing categorical data, an effective feature vector, which represents distinctive features of digital power quality event data, has been obtained by means of the proposed k-means based Apriori algorithm feature selection approach. The proposed k-means based Apriori algorithm feature selection approach is presented with a power quality event recognition system. In the power quality event recognition system, normalization and segmentation processes have been applied to three-phase event voltage signals. Using 9-level multiresolution analysis, wavelet transform coefficients of the event signals have been obtained. By applying nine different feature extraction processes to these coefficients, a 90 dimensional feature vector belonging to three-phase event voltage signals has been extracted. Optimal feature vector has been obtained by applying the k-means based Apriori algorithm feature selection approach to the obtained feature vector, which has been applied as the last step to the input of the least squares support vector machine classifier and recognition performance results have been obtained. Real power quality event data have been used to evaluate the performance of the proposed feature selection approach and power quality event recognition system. According to the results, the proposed k-means based Apriori algorithm feature selection approach and power quality event recognition system are efficient, reliable and applicable and classify three-phase event types with a high degree of accuracy.

Two‐channel control of three‐phase inverters for distortion reduction

A new two-phase, independent control strategy for three-phase three-wire static inverters to reduce unbalance in output voltage is proposed. The three-phase voltage and current signals are processed by the ideal Clarke transform block to yield two single-phase signals, which contain information regarding unbalance and harmonics which may be present in the three-phase signals. If the two single-phase voltage signals could be controlled so that they become equal in magnitude with a phase shift of 90° (ideal alpha beta signals), then the corresponding terminal three-phase voltage signals would become balanced. Singlephase observers are employed to control the fundamental components in the two identical d-q frames created. Simultaneously, when the harmonics are eliminated in the two single-phase channels, the corresponding three-phase voltage signals would become distortion free. Feed-forward compensation can be carried out using the equivalent series-impedance parameters, estimated on-line using a simple identification algorithm. This procedure is not sensitive to frequency and can take care of the voltage drop in the distribution transformer. The simulation and experimental results for a field programmable gate array (FPGA) controlled 60 V table top inverter fabricated in the laboratory are provided

Wavelet Singular Entropy-Based Islanding Detection in Distributed Generation

The paper presents wavelet singular entropy (WSE)-based islanding detection in distributed generation (DG) interfaced to the microgrid. Initially, the three-phase voltage signals retrieved at the target DG location are processed through wavelet transform (WT) to derive detailed coefficient at different levels of decomposition. From the detailed coefficients, the singular value matrix is generated and the WSE for each phase is calculated. Finally, the WSE index (WSEI) for islanding detection is computed by adding the WSE of each phase. The proposed WSEI is able to detect islanding within 10 ms (half cycle) from the event inception, showing the speed of the developed technique. It is observed that WSEI is highly effective in islanding detection, including different islanding and nonislanding conditions in the initial test system and standard microgrid with wide variations in operating parameters.

Accurate Single-Phase Fault-Location Method for Transmission Lines Based on K-Nearest Neighbor Algorithm Using One-End Voltage

In this paper, some useful features are extracted from voltage signals measured at one terminal of the transmission line, which are highly efficient for accurate fault locating. These features are the amplitude of harmonic components, which are extracted after fault inception through applying discrete Fourier transform on one cycle of three-phase voltage signals and then are normalized by a transformation. In this paper, the location of single-line-to-ground faults as the most probable type of fault in the transmission networks is considered. The SLG fault locator, which is designed based on the simple algorithm of k-nearest neighbor ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</i> -NN) in regression mode, estimates the location of fault related to the new input pattern based on existing available patterns. The proposed approach only needs the measured data from one terminal; hence, data communication between both ends of the line and synchronization are not required. In addition, current signals are not used; therefore, the proposed approach is immune against current-transformer saturation and its related errors. Tests conducted on an untransposed transmission line indicate that the proposed fault locator has accurate performance despite simultaneous changes in fault location, fault inception angle, fault resistance, and magnitude and direction of load current.

Development of a Data Acquisition System for the Testing and Verification of Electrical Power Quality Meters

This paper presents the development of a software supported acquisition system for metrological verification and testing of the equipment for monitoring and analysis of the basic electrical power quality parameters. The described procedure consists of two functionally connected segments. The first segment involves generation of the reference three-phase voltage signals, including the possibility of simulation of the various power quality disturbances, typical for electrical power distribution networks. The second part of this procedure includes the real-time recording of power quality disturbances in three-phase distribution networks. The procedure is functionally supported by the virtual instrumentation concept, including a software application developed in LabVIEW environment and data acquisition boards NI 6713 and NI 9215A. The software support of this system performs graphical presentation of the previously generated and recorded signal waveforms. A number of the control functions and buttons, implemented on the virtual instrument front panels, are provided to adjust the basic signal acquisition, generation and recording parameters.

Automatic classification of power quality events and disturbances using wavelet transform and support vector machines

In this study, a new approach for the classification of power quality events is presented. Also, power quality disturbances, which occur in each phase of the power system after a fault event, are classified with the proposed system. In the proposed recognition system, three-phase voltage signals are used in order to identify the type of power quality events. Three-phase voltage signals are subjected to normalisation and segmentation processes. A wavelet transform method is used in order to obtain the distinctive features of event signals. An efficient feature vector, which represents the distinctive characteristics of three-phase event voltage signals and reduces data size, is extracted by applying the two-stage feature extraction process. Power quality event types are determined by using a support vector machine classifier. At the last stage of intelligent recognition system, types of power quality disturbances regarding each fault event are identified by doing a further analysis. Real power system data are used to evaluate the performance of the proposed approach. According to the obtained results, proposed intelligent recognition system classifies power quality event types with a high accuracy. The analyses and results also show that the proposed approach is efficient, reliable and applicable.

A Novel Sensorless Algorithm of the Trapezoidal Back-Electromagnetic Force Brushless DC Motors from Near-Zero to High Speeds

This paper proposes a novel sensorless drive method for the brushless DC (BLDC) motors. It provides an accurate and robust position and speed estimation from the near-zero speed to the rated speed. The proposed sensorless algorithm uses a trapezoidal waveform of the back- electromotive force (EMF) signal with speed information. The back-EMF signals are estimated based on the three-phase current and terminal voltage signals. The validity of the proposed method is verified through both simulation and experimental results.

Detection and classification of voltage disturbances using a Fuzzy-ARTMAP-wavelet network

This paper presents a method for automatic detection and classification of voltage disturbances for problems related to power quality using signal processing techniques and intelligent systems. This support tool for decision making is composed of four modules. The first module continuously evaluates the system's operation state. The second module extracts the essential features from the three-phase voltage signal based on the discrete wavelet transform, multiresolution analysis and entropy norm concepts. The signal signature is processed via standardization and codification in the third module. The fourth module classifies the type of disorder using a Fuzzy-ARTMAP neural network. A total of 7023 power quality events, including voltage swell, voltage sag, outage, harmonics, swell with harmonics, sag with harmonics, oscillatory transient and flicker, were obtained through mathematical models and simulations using the ATP software. To demonstrate the performance of this method, an application is submitted considering a real electric energy distribution system composed of 134 buses with measurements performed on a 13.8 kV and 7.065 MVA feeder. The results indicate that the proposed method is efficient, robust and has high computing performance (low processing time), which allows, a priori, its application in real time.

Fixed-Reference-Frame Phase-Locked Loop for Grid Synchronization Under Unbalanced Operation

This paper presents a grid synchronization scheme aimed to provide an estimation of the angular frequency and both the positive and negative sequences of the fundamental component of an unbalanced three-phase signal. These sequences are provided in fixed-reference-frame coordinates, and thus, the proposed algorithm is referred to as fixed-reference-frame phase-locked loop (PLL) (FRF-PLL). In fact, the FRF-PLL does not require transformation of variables into the synchronous frame coordinates as in most PLL schemes. Therefore, the proposed scheme is not based on the phase angle detection. Instead, the angular frequency is detected and used for synchronization purposes. The design of the FRF-PLL is based on a complete description of the source voltage involving both positive and negative sequences in stationary coordinates and considering the angular frequency as an uncertain parameter. Therefore, the FRF-PLL is intended to perform properly under severe unbalanced conditions and to be robust against angular frequency variations, sags, and swells in the three-phase utility voltage signal. Due to the selective nature of the scheme, it shows certain capability to alleviate the effect of harmonic distortion that is present in the utility voltage signal.

Frequency Estimation of Three-Phase Power System Using Weighted-Least-Square Algorithm and Adaptive FIR Filtering

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> A new technique for estimation of the instantaneous frequency based on simultaneous sampling of three-phase voltage signals is presented. The structure consists of two decoupled modules: the first is for adaptive filtering of input signals, and the second is for frequency estimation. A suitable and robust algorithm for frequency estimation is obtained. This technique provides better performance, compared with the technique based on a single-phase signal in relation to waveforms with noise. The technique is particularly important when asymmetric sags generate zero voltage in one of the three phases. In addition, it allows the measurement of the instantaneous frequency value of real signals for single- or three-phase systems. To demonstrate the performance of the developed algorithm, computer-simulated data records and calibrator-generated signals are processed. The proposed algorithm has been put to test with distorted three-phase voltage signals. </para>

A new digital transformation for harmonics and DC offset removal for the distance fault locator algorithm

This paper presents a new application of Park's transformations to identifying the positive sequence of the fundamental components of the three-phase voltage or current signals needed for fault locator algorithm. The problem is solved in two steps; in the first, we identify and filter the DC offset as well as harmonics that contaminated the signals using Park's transformation. In the second step, the digital residuals, which are the difference between the original signal and the harmonics plus the DC offset, are the digital samples of the positive sequence component of the fundamental waveforms. These samples are then used to estimate digitally the positive sequence of the fundamental components using the least error squares estimation algorithm. It is obvious to state here if the fundamental components are balanced, the estimated positive sequence components equals the fundamental components. The paper starts by reviewing the new transformation matrices, then the proposed steps beyond the algorithm are explained, and finally results for simulated examples and for actual recorded data are reported.

A signal processing module for power system applications

This paper presents a unified power signal processor (PSP) for use in various applications in power systems. The introduced PSP is capable of providing a large number of signals and pieces of information which are frequently required for control, protection, status evaluation, and power quality monitoring of power systems. The PSP receives a set of locally measured three-phase voltage and current signals and provides their fundamental components, amplitudes, phase angles, frequency, harmonics, instantaneous and stationary symmetrical components, active and reactive currents and powers, power factor, and the total harmonic distortion. Simplicity and integrity of its structure as well as its robustness with respect to internal parameters and external disturbances and noise render the proposed scheme very attractive for practical implementations.

Switch sequencer circuit for safe commutation of a matrix converter

The authors present a simple logic circuit for controlling the commutation procedure of a matrix converter. The three-phase PWM voltage signals and the current direction are input variables. The logic circuit determines transitional switching patterns to follow in each phase and generates them sequentially. It produces accurate outputs under any input signal combination with a structure that is simple, requiring only a few logic gates. >