Fast Discrete S-transform Research Articles

A power quality detection and classification algorithm based on FDST and hyper-parameter tuned light-GBM using memetic firefly algorithm

Presently, the issue of power quality (PQ) disturbances in electrical power system has been greater than before owing to increased use of power electronics based nonlinear loads. This work has proposed a hybrid PQ detection and classification algorithm that uses fast-discrete-S-transform (FDST) as feature extraction (FE) technique and memetic firefly algorithm (MFA) based Light-gradient-boost-machine (LGBM) as a classifier. In general, 25 types of PQ signals, comprising both single and multiple disturbances, are studied considering the IEEE-1159 standard. A 3.2 kHz sampling frequency is used on ten cycles of distorted waveforms for the FE. The experimental results clearly proves the effectiveness of the proposed approach with high detection accuracy (99.714% with synthetic data and 99.66% with simulated data), less computational complexity and immune to noisy environments. To end, this work has performed a comparative study with other contemporary FE techniques and classifiers, and in addition with other previously published work.

An Effective Index for Islanding Detection Based on Fast Discrete S-Transform

Passive methods of islanding detection have the advantage of not perturbing the system, but they suffer from large Non-Detection Zone (NDZ) and unpredictable detection time. In this paper, a new passive scheme for islanding detection, based on estimating a new index derived from summation of impedance values in all frequencies along the time at the Point of Common Coupling (PCC), is introduced using Fast Discrete S-Transform (FDST) method. The proposed method maintains both time and frequency information and as a result, helps to decrease the detection time. A frequency dependent model is proposed for characterizing the interconnection changes when islanding happens. The Cumulative Impedance Index (CII) is proposed to discriminate between islanding condition and normal operation. This technique is combined with under/over voltage protection method to decrease NDZ. Simulations for different conditions of normal and islanding operations verify the proposed algorithm. In all cases, islanding is detected within 0.01 s, and NDZ is decreased to 1% of power mismatch between local load and Distributed Generator (DG) output. The results demonstrate the capability of the method to islanding detection with minimum delay and least NDZ.

A Hybrid Time Frequency Response and Fuzzy Decision Tree for Non-stationary Signal Analysis and Pattern Recognition

A Fourier kernel based time-frequency transform is a proven candidate for non-stationary signal analysis and pattern recognition because of its ability to predict time localized spectrum and global phase reference characteristics. However, it suffers from heavy computational overhead and large execution time. The paper, therefore, uses a novel fast discrete sparse S-transform (SST) suitable for extracting time frequency response to monitor non-stationary signal parameters, which can be ultimately used for disturbance detection, and their pattern classification. From the sparse S-transform matrix, some relevant features have been extracted which are used to distinguish among different non-stationary signals by a fuzzy decision tree based classifier. This algorithm is robust under noisy conditions. Various power quality as well as chirp signals have been simulated and tested with the proposed technique in noisy conditions as well. Some real time mechanical faulty signals have been collected to demonstrate the efficiency of the proposed algorithm. All the simulation results imply that the proposed technique is very much efficient.

Fast discrete s-transform and extreme learning machine based approach to islanding detection in grid-connected distributed generation

This paper presents an approach for islanding detection in distributed generation systems (DGs) using fast discrete s-transform (FDST) algorithm and bidirectional extreme learning machine (BELM) classifier. The system undertaken for this study comprises of two different kinds of DGs such as hydro turbine governor system and wind turbine generator. The analysis starts with extracting the non-stationary negative sequence voltage and current signals at DG end and then the instantaneous amplitude and frequency information are extracted through FDST algorithm. From this information, different distinguishing features are computed such as energy and standard deviation of amplitude to track the islanded event from different non-islanded events. The obtained features are examined through an extreme learning machine classifier to discriminate islanding and non-islanding events, under various operating conditions of distribution system. The accuracy of the proposed method is compared with other recently published techniques by various researchers to justify its improved performance for islanding detection.

A Time-Frequency Transform Based Fault Detectionand Classificationof STATCOM Integrated Single Circuit Transmission Line

<p align="center"> </p><p align="center"> </p><table width="593" border="1" cellspacing="0" cellpadding="0"><tbody><tr><td valign="top" width="387"><p>This paper discusses the time-frequency transform based fault detection and classification of STATCOM (Static synchronous compensator) integrated single circuit transmission line. Here, fast-discrete S-Transform (FDST) based time-frequency transformation is proposed for evaluation of fault detection and classification including STATCOM in transmission line. The STATCOM is placed at mid-point of transmission line. The system starts processing by extracting the current signals from both end of current transformer (CT) connected in transmission line. The current signals from CT’s are fed to FDST to compute the spectral energy (SE) of phase current at both end of the line. The differential spectral energy (DSE) is evaluated by subtracting the SE obtained from sending end and SE obtained from receiving end of the line. The DSE is the key indicator for deciding the fault pattern detection and classification of transmission line. This proposed scheme is simulated using MATLAB simulink R2010a version and successfully tested under various parameter condition such as fault resistance (Rf),source impedance (SI), fault inception angle (FIA) and reverse flow of current. The proposed approach is simple, reliable and efficient as the processing speed is very fast to detect the fault within a cycle period of FDT (fault detection time).</p></td></tr></tbody></table>

An enhanced fault detection and location estimation method for TCSC compensated line connecting wind farm

The paper presents a new approach to enhance the fault detection, and location determination based on travelling waves using Fast Discrete S-transform (FDST) for TCSC compensated lines connecting to wind farm. The FDST is applied to the modal components of measured currents at each terminal to detect the arrival time of the first travelling wave (transient) produced by the fault. The proposed method includes detecting the terminal with fastest arrival time of wave to identify the faulted section and estimate the fault location by using proper distance index. The simulation results have demonstrated good performance of the proposed scheme under different fault locations, fault resistances, fault inception angles, fault types, faulted sections, variations in TCSC parameters and changing wind speeds. The performance validation on the real-time digital simulator (RTDS) platform enhances the applicability of the proposed protection scheme for the TCSC based compensated line integrated with wind farm. The performance comparison with the conventional travelling wave fault location algorithms using Continuous Wavelet Transform (CWT) shows potential ability of the proposed method.

Time frequency response-based current differential protection of wide area compensated power system networks

This paper presents a time-frequency response approach suitable for current differential protection of transmission lines in an interconnected power system network. The current differential protection scheme efficiently discriminates between the internal and external faults in the protected zone of a transmission network and exhibits stability and robustness. For detecting the occurrence of a fault on the transmission line a cumulative sum average (CUSUM) technique is used and the fault classification and location are determined using the spectral energy of the average and differential currents based on a recent matrix version of the fast discrete S-transform (FST). This new formulation uses intelligent frequency scaling, bandpass filtering, and suitable interpolation techniques to reduce the computational overhead of the algorithm by almost 30 times in comparison to the earlier conventional S-transform. Further, the new protection scheme will be a viable and competing one with the advent synchrophasors technology and wide area high speed communication and GPS systems. Also, its viability is tested for the wide area network with a STATCOM placed at the middle of one of the transmission lines injecting reactive currents which requires the detection of the occurrence of the fault before or after the compensating device.

Time frequency response-based current differential protection of wide area compensated power system networks

This paper presents a time-frequency response approach suitable for current differential protection of transmission lines in an interconnected power system network. The current differential protection scheme efficiently discriminates between the internal and external faults in the protected zone of a transmission network and exhibits stability and robustness. For detecting the occurrence of a fault on the transmission line a cumulative sum average (CUSUM) technique is used and the fault classification and location are determined using the spectral energy of the average and differential currents based on a recent matrix version of the fast discrete S-transform (FST). This new formulation uses intelligent frequency scaling, bandpass filtering, and suitable interpolation techniques to reduce the computational overhead of the algorithm by almost 30 times in comparison to the earlier conventional S-transform. Further, the new protection scheme will be a viable and competing one with the advent synchrophasors technology and wide area high speed communication and GPS systems. Also, its viability is tested for the wide area network with a STATCOM placed at the middle of one of the transmission lines injecting reactive currents which requires the detection of the occurrence of the fault before or after the compensating device.

A fast time–frequency transform based differential relaying scheme for UPFC based double-circuit transmission line

Abstract This paper presents a new differential relaying scheme for a mutually coupled, double circuit transmission line in presence of Unified Power Flow Controller (UPFC) in the line. The process starts at retrieving the three phase current signals at both ends of the transmission line synchronously and processing it though the time–frequency transform such as Fast Discrete S-Transform to derive the spectral energy content of the current signals. The differential spectral energy of current signals (difference between the spectral energy of the current signal at the sending and receiving ends, respectively) of the respective phases of transmission line is used to register the fault pattern. The proposed approach includes fault detection and classification along with identification of the fault section with respect to UPFC location in one of the double-circuit transmission line. The extensive test results indicate that the proposed differential relaying scheme is highly reliable in registering fault patterns in UPFC based transmission line including wide variations in operating parameters of the power network.

Detection, classification, and location of faults in power transmission lines

Abstract This paper presents a pattern recognition approach for current differential relaying of power transmission lines. The current differential method uses spectral energy information provided through a new Fast Discrete S-Transform (FDST). Unlike the conventional S-Transform (ST) technique the new one uses different types of frequency scaling, band pass filtering, and interpolation techniques to reduce the computational cost and remove redundant information. Further due to its low computational complexity, the new algorithm is suitable for real-time implementation. The proposed scheme is evaluated for current differential protection of a transmission line fed from both ends for a variety of faults, fault resistance, inception angles, and significant noise in the signal using computer simulation studies. Also the fundamental amplitude and phase angle of the two end currents and one end voltage are computed with the help of the new formulation to provide fault location with significant accuracy. The results obtained from the exhaustive computation show the feasibility of the new approach.

A new time–frequency approach for distance protection in parallel transmission lines operating with STATCOM

The paper presents a new cross-differential and impedance protection scheme for a parallel transmission system, in the presence of STATCOM. A cumulative sum (CUSUM) approach is used for fault detection by obtaining the measured values of currents in the two lines. Spectral energies of the current signals are then computed by using a new fast discrete S-Transform (FDST) approach for classification of the nature of faults on the lines. The modified transform is based on new scaling, band pass filtering, and interpolation techniques that makes the new variant computationally much faster than the earlier S-Transform and can be implemented in real time. Further the FDST is used to accurately identify the occurrence of the fault before or after the STATCOM and compute the location of the fault using one half cycle data prior to the occurrence of the fault and one half cycle data after the fault has occurred.

A new fast discrete S-transform and decision tree for the classification and monitoring of power quality disturbance waveforms

SUMMARY In this paper, a new fast discrete S-transform (ST)-based time-frequency signal analyzer has been proposed for the detection, classification, and monitoring of power quality (PQ) disturbances varying in an electric power system. The proposed algorithm is based on the generalized Fourier algorithm that is used to obtain the time-localized spectral characteristics of the time-varying voltage and current signals belonging to PQ events. The fast ST algorithm is realized with different types of frequency scaling, band pass filtering, and interpolation techniques based on Heisenberg's uncertainty principle resulting in a reduced computation cost. In the conventional ST, the window width decreases at higher frequencies with a reduction in frequency resolution and conversely at low frequencies with wider windows. Therefore, the time-varying PQ disturbance signal is down sampled at low frequencies and cropped at high frequencies resulting in the evaluation of a fewer samples. From the time–frequency matrix output, important features are extracted and used with a binary decision tree for an accurate classification of single and simultaneous PQ events. Further, a unified approach is presented to track the time-varying PQ disturbance waveforms like voltage sag, swell, harmonics, and oscillatory transients and produce estimation of their amplitudes and phase angles. Copyright © 2013 John Wiley & Sons, Ltd.

A new fast discrete S-transform for power quality disturbance monitoring

AbstractIn this paper a new fast discrete S-transform (ST) has been proposed for the estimation of power quality (PQ) disturbance signal parameters in an electric power system. The proliferation of non-stationary non-linear loads and various PQ disturbances such as voltage dips, swells, transients, interruptions, voltage flicker, and spikes, etc., necessitate high PQ level in micro and smart grids. The proposed algorithm is based on the generalised Fourier algorithm that combines down sampling and signal cropping to produce a fast discrete ST. The technique is based on Heisenberg’s uncertainty principle, which limits the time-frequency resolution of ST and employs a trade-off between the time resolution and frequency resolution. In ST the window width decreases at higher frequencies with a reduction in frequency resolution and conversely at low frequencies with wider windows. Hence the signal can be down sampled at low frequencies and cropped at high frequencies to result in fewer samples to be evaluated....

A New Real-Time Fast Discrete S-Transform for Cross-Differential Protection of Shunt-Compensated Power Systems

This paper presents a cross-differential protection scheme for power transmission systems inclusive of a STATCOM. The measurement of the energy of the prominent frequency components of the current signals is done using a computationally fast version of the discrete S Transform suitable for power system signal analysis. The energy thus obtained is used for cross-differential purposes. The practical implementation of the new fast discrete S-transform is performed on the TMS320C6713 digital signal processor for verification of real-time operation of the relaying scheme. The computational load of the processor to perform the transform in online mode is reduced by a cross-differential check using a cumulative difference technique. The results obtained from the extensive experimentations show the feasibility and speed of the new approach.

A New Fast Discrete S-Transform for Power Quality Disturbance Monitoring

In this paper a new fast discrete S-transform (ST) has been proposed for the estimation of power quality (PQ) disturbance signal parameters in an electric power system. The proliferation of non-stationary non-linear loads and various PQ disturbances such as voltage dips, swells, transients, interruptions, voltage flicker, and spikes, etc., necessitate high PQ level in micro and smart grids. The proposed algorithm is based on the generalised Fourier algorithm that combines down sampling and signal cropping to produce a fast discrete ST. The technique is based on Heisenberg’s uncertainty principle, which limits the time-frequency resolution of ST and employs a trade-off between the time resolution and frequency resolution. In ST the window width decreases at higher frequencies with a reduction in frequency resolution and conversely at low frequencies with wider windows. Hence the signal can be down sampled at low frequencies and cropped at high frequencies to result in fewer samples to be evaluated. The algorithm models the typical time-varying signal and the accompanied distortions due to harmonics and random noise in a manner that will be suitable for real-time PQ indices estimation. Various PQ disturbance waveforms like voltage sag, swell, harmonics and interharmonics, and oscillatory transients are considered for tracking and estimation of PQ indices.

Fault Trajectories and Location Estimations for Distance Protection using two New Simplified Phasor Analysers

The paper presents two new computationally simple algorithms for the protection of power transmission lines during fault conditions. The first method is based on the minimisation of a weighted forgetting factor based error cost function by the use of a fast Gauss-Newton method approach. Further a Hessian matrix approximation is used to produce a fast recursive algorithm, which is immune to random noise, waveform distortion due to DC offsets and increases the speed of convergence and accuracy. The algorithm models the typical time-varying signal and the accompanied distortions due to harmonics and random noise in a manner that will be suitable for real-time apparent impedance estimation. The second approach is based on a phase corrected wavelet transform known as fast discrete S-transform, which unlike the conventional one, uses frequency selection and frequency localised band pass filtering techniques to reduce the computational overhead and makes it suitable for on-line implementation in computing the fault location on an overhead transmission line. Both the proposed schemes are evaluated for the protection of a transmission line in a meshed power system network for a variety of fault types, fault locations, fault resistances, and significant noise in the signal using computer simulation studies.