Techniques and methodologies for power quality analysis and disturbances classification in power systems: a review

The relevance of power quality (PQ) issues has recently augmented because of the increased use of power electronic equipment, which results in a voltage deviation and current waveforms. The PQ monitoring is covered by two main subjects: the development of PQ indices to quantify the power supply quality and the electrical disturbances detection such as harmonics, sags, swells etc., which allows knowing the conditions of the electric power systems. In this study a review of techniques and methodologies developed for PQ analysis and power disturbance classification is presented in order to show their major characteristics.

[1]  Davide Lauria,et al.  Indices for the characterisation of bursts of short-duration waveform distortion , 2007 .

[2]  S. Nam,et al.  Classification of power disturbances using feature extraction in time-frequency plane , 2002 .

[3]  Md. Mamun Ibne Reaz,et al.  Advances in Signal Processing and Artificial Intelligence Technologies in the Classification of Power Quality Events: A Survey , 2005 .

[4]  S. J. Huang,et al.  Application of Gabor transform technique to supervise power system transient harmonics , 1996 .

[5]  P. O'Shea,et al.  A High Resolution Spectral Analysis Algorithm for Power System Disturbance Monitoring , 2002, IEEE Power Engineering Review.

[6]  Zhi-yong Li,et al.  Classification of power quality combined disturbances based on phase space reconstruction and support vector machines , 2008 .

[7]  M. Negnevitsky,et al.  A Neural-Fuzzy Classifier for Recognition of Power Quality Disturbances , 2002, IEEE Power Engineering Review.

[8]  Tao Lin,et al.  Real time measurement of power disturbances: Part 1. Survey and a novel complex filter approach , 2006 .

[9]  Tao Lin,et al.  Real-time measurement of power disturbances: Part 2. Implementation and evaluation of the novel complex filter/recursive algorithm , 2006 .

[10]  K.L. Lo,et al.  Wavelet-based fuzzy reasoning approach to power-quality disturbance recognition , 2004, IEEE Transactions on Power Delivery.

[11]  A. Domijan,et al.  Recursive algorithm for real-time measurement of electrical variables in power systems , 2006, IEEE Transactions on Power Delivery.

[12]  Zhen Ren,et al.  Power quality disturbance identification using wavelet packet energy entropy and weighted support vector machines , 2008, Expert Syst. Appl..

[13]  H. Siahkali.  Power quality indexes for continue and discrete disturbances in a distribution area , 2008, 2008 IEEE 2nd International Power and Energy Conference.

[14]  Li Qi,et al.  Prony Analysis for Power System Transient Harmonics , 2007, EURASIP J. Adv. Signal Process..

[15]  Bijaya K. Panigrahi,et al.  Hybrid signal processing and machine intelligence techniques for detection, quantification and classification of power quality disturbances , 2009, Eng. Appl. Artif. Intell..

[16]  A. K. Ghosh,et al.  The classification of power system disturbance waveforms using a neural network approach , 1994 .

[17]  Whei-Min Lin,et al.  Detection and Classification of Multiple Power-Quality Disturbances With Wavelet Multiclass SVM , 2008, IEEE Transactions on Power Delivery.

[18]  G. Panda,et al.  Power Quality Analysis Using S-Transform , 2002, IEEE Power Engineering Review.

[19]  E.F. El-Saadany,et al.  Power quality disturbance classification using the inductive inference approach , 2004, IEEE Transactions on Power Delivery.

[20]  Eduardo Cabal-Yepez,et al.  A Real-Time Smart Sensor for High-Resolution Frequency Estimation in Power Systems , 2009, Sensors.

[21]  Ahmet Serdar Yilmaz,et al.  Frequency domain analysis of power system transients using Welch and Yule–Walker AR methods , 2007 .

[22]  Honggeng Yang,et al.  Short duration disturbance classifying based on S-transform maximum similarity , 2009 .

[23]  Chia-Hung Lin,et al.  Power quality detection with classification enhancible wavelet-probabilistic network in a power system , 2005 .

[24]  Bijaya K. Panigrahi,et al.  Power Quality Disturbance Classification Using Fuzzy C-Means Algorithm and Adaptive Particle Swarm Optimization , 2009, IEEE Transactions on Industrial Electronics.

[25]  Paul S. Wright,et al.  Short-time Fourier transforms and Wigner-Ville distributions applied to the calibration of power frequency harmonic analyzers , 1999, IEEE Trans. Instrum. Meas..

[26]  S. J. Huang,et al.  FPGA Realization of Wavelet Transform for Detection of Electric Power System Disturbances , 2002, IEEE Power Engineering Review.

[27]  M. M. Morcos,et al.  Artificial Intelligence and Advanced Mathematical Tools for Power Quality Applications: A Survey , 2001, IEEE Power Engineering Review.

[28]  A. Y. Chikhani,et al.  Power quality detection and classification using wavelet-multiresolution signal decomposition , 1999 .

[29]  Edward J. Powers,et al.  Characterization of distribution power quality events with Fourier and wavelet transforms , 2000 .

[30]  Jovitha Jerome,et al.  Pattern recognition of power signal disturbances using S Transform and TT Transform , 2010 .

[31]  Mehmet Bayrak,et al.  Application of lifting based wavelet transforms to characterize power quality events , 2007 .

[32]  Pradipta Kishore Dash,et al.  Multiresolution S-transform-based fuzzy recognition system for power quality events , 2004 .

[33]  Z. Gaing.  Wavelet-based neural network for power disturbance recognition and classification , 2004 .

[34]  J. Montaño,et al.  Wavelet and neural structure: a new tool for diagnostic of power system disturbances , 2001 .

[35]  Sang Won Nam,et al.  Efficient feature vector extraction for automatic classification of power quality disturbances , 1998 .

[36]  M. Uyar,et al.  An effective wavelet-based feature extraction method for classification of power quality disturbance signals , 2008 .

[37]  Magdy M. A. Salama,et al.  On-line disturbance classification using nearest neighbor rule , 2001 .

[38]  T.X. Zhu,et al.  Detection and Characterization of Oscillatory Transients Using Matching Pursuits With a Damped Sinusoidal Dictionary , 2007, IEEE Transactions on Power Delivery.

[39]  D. T. Nguyen,et al.  Improving training of radial basis function network for classification of power quality disturbances , 2002 .

[40]  Zahra Moravej,et al.  Power quality events classification and recognition using a novel support vector algorithm , 2009 .

[41]  C. Sankaran.  Power Quality , 2001 .

[42]  Haibo He,et al.  Power quality disturbances analysis based on EDMRA method , 2009 .

[43]  Thanatchai Kulworawanichpong,et al.  Recognition of power quality events by using multiwavelet-based neural networks , 2008 .

[44]  Abhisek Ukil,et al.  Adjusted Haar wavelet for application in the power systems disturbance analysis , 2008, Digit. Signal Process..

[45]  A. Y. Chikhani,et al.  Genetic Algorithms Based Economic Dispatch for Cogeneration Units Considering Multiplant , 2022 .

[46]  Irene Y. H. Gu,et al.  Classification of Underlying Causes of Power Quality Disturbances: Deterministic versus Statistical Methods , 2007, EURASIP J. Adv. Signal Process..

[47]  Pradipta Kishore Dash,et al.  S-transform-based intelligent system for classification of power quality disturbance signals , 2003, IEEE Trans. Ind. Electron..

[48]  A.V. Mamishev,et al.  Classification of power quality events using optimal time-frequency representations-Part 2: application , 2004, IEEE Transactions on Power Delivery.

[49]  Nirmal-Kumar C. Nair,et al.  Adaptive sampling scheme for monitoring oscillations using Prony analysis , 2009 .

[50]  Pradipta Kishore Dash,et al.  Fast Tracking of Power Quality Disturbance Signals Using an Optimized Unscented Filter , 2009, IEEE Transactions on Instrumentation and Measurement.

[51]  K. M. El-Naggar,et al.  A genetic based algorithm for measurement of power system disturbances , 2006 .

[52]  A.V. Mamishev,et al.  Classification of power quality events using optimal time-frequency representations-Part 1: theory , 2004, IEEE Transactions on Power Delivery.

[53]  F. Choong,et al.  Expert System for Power Quality Disturbance Classifier , 2007, IEEE Transactions on Power Delivery.

[54]  U. D. Dwivedi,et al.  A Wavelet-based Denoising Technique for Improved Monitoring and Characterization of Power Quality Disturbances , 2009 .

[55]  Arturo Garcia-Perez,et al.  Automatic Online Diagnosis Algorithm for Broken-Bar Detection on Induction Motors Based on Discrete Wavelet Transform for FPGA Implementation , 2008, IEEE Transactions on Industrial Electronics.

[56]  Magdy M. A. Salama,et al.  Wavelet-based signal processing for disturbance classification and measurement , 2002 .

[57]  Pradipta Kishore Dash,et al.  Hybrid S-transform and Kalman filtering approach for detection and measurement of short duration disturbances in power networks , 2004, IEEE Transactions on Instrumentation and Measurement.

[58]  Salvatore Nuccio,et al.  A Phase-Locked Loop for the Synchronization of Power Quality Instruments in the Presence of Stationary and Transient Disturbances , 2007, IEEE Transactions on Instrumentation and Measurement.

[59]  A. Elmitwally,et al.  Proposed wavelet-neurofuzzy combined system for power quality violations detection and diagnosis , 2001 .

[60]  A.R. Messina,et al.  A Refined Hilbert–Huang Transform With Applications to Interarea Oscillation Monitoring , 2009, IEEE Transactions on Power Systems.

[61]  Daniel J. Trudnowski,et al.  Signal Processing Methods for Estimating Small-Signal Dynamic Properties from Measured Responses , 2009 .

[62]  A. Domijan,et al.  On power quality indices and real time measurement , 2005, IEEE Transactions on Power Delivery.

[63]  P. Pillay,et al.  Application of wavelets to model short-term power system disturbances , 1996 .

[64]  J Thambirajah,et al.  A Multivariate Approach Towards Interarea Oscillation Damping Estimation Under Ambient Conditions Via Independent Component Analysis and Random Decrement , 2011, IEEE Transactions on Power Systems.

[65]  A. Cruz Serra,et al.  PQ Monitoring System for Real-Time Detection and Classification of Disturbances in a Single-Phase Power System , 2008, IEEE Transactions on Instrumentation and Measurement.

[66]  D. O. Koval.  Power system disturbance patterns , 1989 .

[67]  R. Sukanesh,et al.  POWER QUALITY DISTURBANCE CLASSIFICATION USING S-TRANSFORM AND RADIAL BASIS NETWORK , 2009, Appl. Artif. Intell..

[68]  Bijaya Ketan Panigrahi,et al.  Detection and classification of power quality disturbances using S-transform and modular neural network , 2008 .

[69]  Irene Yu-Hua Gu,et al.  Signal processing of power quality disturbances , 2006 .

[70]  Emilia Nowaczyk.  Method of Reducing Error in Calculations of Active Power from Signal Samples , 2007 .

[71]  Thai Nguyen,et al.  Power quality disturbance classification utilizing S-transform and binary feature matrix method , 2009 .

[72]  Edward J. Powers,et al.  Power quality disturbance waveform recognition using wavelet-based neural classifier. I. Theoretical foundation , 2000 .

[73]  B. K. Panigrahi,et al.  Optimal feature selection for classification of power quality disturbances using wavelet packet-based fuzzy k-nearest neighbour algorithm , 2009 .

[74]  Om P. Malik,et al.  Detection and classification of power quality disturbances in noisy conditions , 2003 .

[75]  Zahra Moravej,et al.  Detection and Classification of Power Quality Disturbances Using Wavelet Transform and Support Vector Machines , 2009 .

[76]  Shiping Su,et al.  A new power quality detection device based on embedded technique , 2008, 2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies.

[77]  J.C. Montano,et al.  Classification of Electrical Disturbances in Real Time Using Neural Networks , 2007, IEEE Transactions on Power Delivery.

[78]  Michel Meunier,et al.  Detection and measurement of power quality disturbances using wavelet transform , 2000 .

[79]  M. R. Iravani,et al.  Wavelet based on-line disturbance detection for power quality applications , 2000 .

[80]  Pierluigi Caramia,et al.  Power Quality Indices in Liberalized Markets , 2009 .

[81]  S. Mishra,et al.  Detection and Classification of Power Quality Disturbances Using S-Transform and Probabilistic Neural Network , 2008, IEEE Transactions on Power Delivery.

[82]  Peter Minns,et al.  Electric power quality disturbance classification using self-adapting artificial neural networks , 2002 .

[83]  Md. Mamun Ibne Reaz,et al.  Prototyping of Wavelet Transform, Artificial Neural Network and Fuzzy Logic for Power Quality Disturbance Classifier , 2007 .

[84]  Shyh-Jier Huang,et al.  Application of wavelets to classify power system disturbances , 1998 .

[85]  Sami Ekici,et al.  Classification of power system disturbances using support vector machines , 2009, Expert Syst. Appl..

[86]  S. Osowski.  SVD technique for estimation of harmonic components in a power system: a statistical approach , 1994 .

[87]  Ganapati Panda,et al.  Power quality disturbance data compression, detection, and classification using integrated spline wavelet and S-transform , 2002 .

[88]  G. Carpinelli,et al.  Adaptive Prony Method for the Calculation of Power-Quality Indices in the Presence of Nonstationary Disturbance Waveforms , 2009, IEEE Transactions on Power Delivery.

[89]  Subhransu Ranjan Samantaray,et al.  Decision tree-initialised fuzzy rule-based approach for power quality events classification , 2010 .

[90]  Azah Mohamed,et al.  Rule based system for power quality disturbance classification incorporating S-transform features , 2010, Expert Syst. Appl..

[91]  G. Jang,et al.  Time-Frequency Analysis of Power-Quality Disturbances via the Gabor–Wigner Transform , 2010, IEEE Transactions on Power Delivery.

[92]  Arturo Roman Messina,et al.  Inter-area Oscillations in Power Systems , 2009 .

[93]  R. Betancourt,et al.  Analysis and Characterization of Power System Nonlinear Oscillations Us- ing Hilbert Spectral Analysis , 2007 .

[94]  Jong-Beom Lee,et al.  A fuzzy-expert system for classifying power quality disturbances , 2004 .

[95]  M. Kezunovic,et al.  A Novel Software Implementation Concept for Power Quality Study , 2001, IEEE Power Engineering Review.

[96]  Ahmet Teke,et al.  Fast sag/swell detection method for fuzzy logic controlled dynamic voltage restorer , 2010 .

[97]  John G. Proakis,et al.  Digital Signal Processing: Principles, Algorithms, and Applications , 1992 .

[98]  Mario Oleskovicz,et al.  Power quality analysis applying a hybrid methodology with wavelet transforms and neural networks , 2009 .

[99]  J Stones.  43 – Power Quality , 2003 .

[100]  J. Lara-Cardoso,et al.  Low-Cost Power Harmonics Analyzer of Nonlinear Loads Based on FPGA , 2008, 2008 IEEE Instrumentation and Measurement Technology Conference.

[101]  Rengang Yang,et al.  Power-Quality Disturbance Recognition Using S-Transform , 2007, IEEE Transactions on Power Delivery.

[102]  Muhsin Tunay Gençoglu,et al.  An expert system based on S-transform and neural network for automatic classification of power quality disturbances , 2009, Expert Syst. Appl..

[103]  H Markiewicz,et al.  Voltage Disturbances Standard EN 50160 - Voltage Characteristics in Public Distribution Systems , 2008 .

[104]  Magdy M. A. Salama,et al.  Power quality monitoring using an integrated Fourier linear combiner and fuzzy expert system , 1999 .

[105]  Ahmed M. Gaouda.  Power system disturbance modeling under deregulated environment , 2007, J. Frankl. Inst..

[106]  Zhe Chen,et al.  Power quality detection and classification using digital filters , 2001, 2001 IEEE Porto Power Tech Proceedings (Cat. No.01EX502).

[107]  Shyh-Jier Huang,et al.  Application of Morlet wavelets to supervise power system disturbances , 1999 .

[108]  S. Santoso,et al.  Power quality assessment via wavelet transform analysis , 1996 .

[109]  T. Lobos,et al.  Automated classification of power-quality disturbances using SVM and RBF networks , 2006, IEEE Transactions on Power Delivery.

[110]  Peter J. O'Shea,et al.  The use of sliding spectral windows for parameter estimation in power system disturbance monitoring , 2000 .

[111]  J. F. Hauer,et al.  Initial results in Prony analysis of power system response signals , 1990 .

[112]  Liu Xian-cheng,et al.  IEC 61000-4-30:Introduction of 2008 Version Standard of EMC-Experiment and Measurement Technology-Methods of Power Quality Measurement , 2010 .