W.M. Grady

Power quality assessment via wavelet transform analysis

In this paper we present a new approach to detect, localize, and investigate the feasibility of classifying various types of power quality disturbances. The approach is based on wavelet transform analysis, particularly the dyadic-orthonormal wavelet transform. The key idea underlying the approach is to decompose a given disturbance signal into other signals which represent a smoothed version and a detailed version of the original signal. The decomposition is performed using multiresolution signal decomposition techniques. We demonstrate and test our proposed technique to detect and localize disturbances with actual power line disturbances. In order to enhance the detection outcomes, we utilize the squared wavelet transform coefficients of the analyzed power line signal. Based on the results of the detection and localization, we carry out an initial investigation of the ability to uniquely characterize various types of power quality disturbances. This investigation is based on characterizing the uniqueness of the squared wavelet transform coefficients for each power quality disturbance.

Survey of active power line conditioning methodologies

Active power-line conditioning (APLC) is a concept that can potentially correct network distortion caused by power electronic loads by injecting equal-but-opposite distortion at carefully selected points in a network. Results are presented of an extensive literary survey on the subject of APLCs. Thirty-seven key publications are identified and reviewed. Existing and proposed line-conditioning methodologies are compared, and a list of the advantages and limitations of each is presented. >

Power quality disturbance waveform recognition using wavelet-based neural classifier. I. Theoretical foundation

Existing techniques for recognizing and identifying power quality disturbance waveforms are primarily based on visual inspection of the waveform. It is the purpose of this paper to bring to bear advances, especially in wavelet transforms, artificial neural networks, and the mathematical theory of evidence, to the problem of automatic power quality disturbance waveform recognition. Unlike past attempts to automatically identify disturbance waveforms where the identification is performed in the time domain using an individual artificial neural network, the proposed recognition scheme is carried out in the wavelet domain using a set of multiple neural networks. The outcomes of the networks are then integrated using decision making schemes such as a simple voting scheme or the Dempster-Shafer theory of evidence. With such a configuration, the classifier is capable of providing a degree of belief for the identified disturbance waveform.

Power quality disturbance data compression using wavelet transform methods

In this paper, the authors present a wavelet compression technique for power quality disturbance data. The compression technique is performed through signal decomposition, thresholding of wavelet transform coefficients and signal reconstruction. Threshold values are determined by weighting the absolute maximum value at each scale. Wavelet transform coefficients whose values are below the threshold are discarded, while those that are above the threshold are kept along with their temporal locations. The authors show the efficacy of the technique by compressing actual disturbance data. The file size of the compressed data is only one-sixth to one-third that of the original data. Therefore, the cost related to storing and transmitting the data is significantly reduced.

Power quality disturbance waveform recognition using wavelet-based neural classifier. II. Application

For pt.I see ibid., vol.15, no.1, p.222-8 (2000). A wavelet-based neural classifier is constructed and thoroughly tested under various conditions, The classifier is able to provide a degree of belief for the identified waveform. The degree of belief gives an indication about the goodness of the decision made. It is also equipped with an acceptance threshold so that it can reject ambiguous disturbance waveforms. The classifier is able to achieve the accuracy rate of more than 90% by rejecting less than 10% of the waveforms as ambiguous.

Interharmonics: Theory and Modeling

Some of the most remarkable issues related to interharmonic theory and modeling are presented. Starting from the basic definitions and concepts, attention is first devoted to interharmonic sources. Then, the interharmonic assessment is considered with particular attention to the problem of the frequency resolution and of the computational burden associated with the analysis of periodic steady-state waveforms. Finally, modeling of different kinds of interharmonic sources and the extension of the classical models developed for power system harmonic analysis to include interharmonics are discussed. Numerical results for the issues presented are given with references to case studies constituted by popular schemes of adjustable speed drives.

A direction finder for power quality disturbances based upon disturbance power and energy

While existing techniques are capable of automatically identifying and classifying various types of distribution-level power quality disturbances, they do not provide any information about the locations of the disturbance sources. This paper shows that it is possible to use sampled voltage and current waveforms to determine on which side of a recording device a disturbance originates. This is accomplished by examining the energy flow and peak instantaneous power for both capacitor energizing and voltage sag disturbances. The authors demonstrate the technique by testing it on both ATP-generated waveforms and actual field disturbance data. In both cases, they are able to accurately determine on which side of a recording device the disturbance originates. If enough recording devices are available in a network, the individual readings can be collectively used to pinpoint the locations of disturbance sources.

Effect of supply voltage harmonics on the input current of single-phase diode bridge rectifier loads

This paper describes the effect of supply voltage harmonics on the response of single-phase capacitor-filtered diode bridge rectifier loads. A complete analytical model for calculating the current harmonics of these loads, when energized by nonsinusoidal supply voltages, is presented. The model is then used to investigate the effect of supply voltage harmonics on current harmonics. The key findings of the paper are as follows: (1) the phase angles of supply voltage harmonics determine whether or not these harmonics increase or decrease current distortion. In general, a peaked voltage wave increases input current distortion, whereas a flattened wave has the opposite effect. Because of this complex relationship, voltage crest factor is a much better predictor of total harmonic current distortion than is total harmonic voltage distortion. (2) The current harmonics created by these loads produce voltage harmonics that tend to have a partial self-compensating effect on the current harmonics. >

Electric power quality disturbance detection using wavelet transform analysis

The objective of the paper is to present a novel approach to detect and localize various electric power quality disturbances using wavelet transform analysis. Unlike other approaches where the detection is performed directly in the time domain, detection using wavelet transform analysis approach is carried out in the time-scale domain. As far as detection in power quality disturbance is concerned, one- or two-scale signal decomposition is adequate to discriminate disturbances from their background. This approach is robust in detecting and localizing a wide range of power disturbances such as fast voltage fluctuations, short and long duration voltage variations, and harmonic distortion.<<ETX>>

The application of network objective functions for actively minimizing the impact of voltage harmonics in power systems

The impact of voltage harmonics on a power system can be minimized by using active filters to inject distortion-canceling currents. However, a network objective function must be specified before the optimum filter injection currents can be determined. The authors illustrate the application of a distortion-minimizing procedure with each of the following four network correction strategies, total harmonic voltage distortion, telephone influence factor, motor load-loss function, and single-bus sine wave correction. It is also pointed out that, as with any active device, care must be taken when sitting and controlling an APLC (active power line conditioner) to ensure maximum improvement in network distortion. If a network approach is not used, a poorly located APLC could have an overall negative impact. >