Wavelet-alienation based protection scheme for multi-terminal transmission line
TL;DR: The proposed algorithm makes use of wavelet transform based approximate coefficients of three-phase voltage and current signals, obtained over a quarter cycle to detect, classify and locate various faults in multi-terminal transmission system.
About: This article is published in Electric Power Systems Research.The article was published on 2018-08-01. It has received 27 citations till now. The article focuses on the topics: Wavelet transform & Wavelet.
Citations
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TL;DR: The algorithm is found to be effective for providing protection to transmission line against various faults and makes the protection scheme less complex, fast and more economic due to the elimination of the requirement of communication channel and global positioning system synchronisation.
Abstract: This study presents an algorithm for detection, classification, and location of transmission line faults. A fault index based on features extracted from current signals using the alienation coefficient and Wigner distribution function has been proposed for the detection and classification of faults. Double line and double line to ground faults have been classified from each other using ground fault index based on negative sequence current. Statistical relations are proposed for the estimation of fault location using peak values of the proposed fault index. The results of different case studies established the effectiveness of the algorithm. The algorithm is found to be effective for providing protection to transmission line against various faults. This is achieved using current signals recorded on one terminal of the line. This makes the protection scheme less complex, fast and more economic due to the elimination of the requirement of communication channel and global positioning system synchronisation. The proposed protection scheme is also validated on a real-time network of transmission utility. The effectiveness of the algorithm is established by comparing performance with reported algorithms.
51 citations
TL;DR: An algorithm for providing protection to the hybrid grid with high RE penetration level is introduced and performance is effectively established by comparing with the discrete wavelet transform (DWT) and Stockwell transform based protection schemes.
Abstract: The rapid growth of grid integrated renewable energy (RE) sources resulted in development of the hybrid grids. Variable nature of RE generation resulted in problems related to the power quality (PQ), power system reliability, and adversely affects the protection relay operation. High penetration of RE to the utility grid is achieved using multi-tapped lines for integrating the wind and solar energy and also to supply loads. This created considerable challenges for power system protection. To overcome these challenges, an algorithm is introduced in this paper for providing protection to the hybrid grid with high RE penetration level. All types of fault were identified using a fault index (FI), which is based on both the voltage and current features. This FI is computed using element to element multiplication of current-based Wigner distribution index (WD-index) and voltage-based alienation index (ALN-index). Application of the algorithm is generalized by testing the algorithm for the recognition of faults during different scenarios such as fault at different locations on hybrid grid, different fault incident angles, fault impedances, sampling frequency, hybrid line consisting of overhead (OH) line and underground (UG) cable sections, and presence of noise. The algorithm is successfully tested for discriminating the switching events from the faulty events. Faults were classified using the number of faulty phases recognized using FI. A ground fault index (GFI) computed using the zero sequence current-based WD-index is also introduced for differentiating double phase and double phase to ground faults. The algorithm is validated using IEEE-13 nodes test network modelled as hybrid grid by integrating wind and solar energy plants. Performance of algorithm is effectively established by comparing with the discrete wavelet transform (DWT) and Stockwell transform based protection schemes.
41 citations
TL;DR: An algorithm for the recognition of faults in the grid to which a solar photovoltaic (PV) system is integrated and the performance was effectively established by comparing it with the discrete Wavelet transform (DWT), Wavelet packet transform (WPT) and Stockwell transform-based methods.
Abstract: As renewable energy (RE) penetration has a continuously increasing trend, the protection of RE integrated power systems is a critical issue. Recently, power networks developed for grid integration of solar energy (SE) have been designed with the help of multi-tapped lines to integrate small- and medium-sized SE plants and simultaneously supplying power to the loads. These tapped lines create protection challenges. This paper introduces an algorithm for the recognition of faults in the grid to which a solar photovoltaic (PV) system is integrated. A fault index (FI) was introduced to identify faults. This FI was calculated by multiplying the Wigner distribution (WD) index and Alienation (ALN) index. The WD-index was based on the energy density of the current signal evaluated using Wigner distribution function. The ALN-index was evaluated using sample-based alienation coefficients of the current signal. The performance of the algorithm was validated for various scenarios with different fault types at various locations, different fault incident angles, fault impedances, sampling frequencies, hybrid line consisting of overhead (OH) line and underground (UG) cable sections, different types of transformer windings and the presence of noise. Two phase faults with and without the involvement of ground were differentiated using the ground fault index based on the zero sequence current. This study was performed on the IEEE-13 nodes test network to which a solar PV plant with a capacity of 1 MW was integrated. The performance of the algorithm was also tested on the western part of utility grid in the Rajasthan State in India where solar PV energy integration is high. The performance of the algorithm was effectively established by comparing it with the discrete Wavelet transform (DWT), Wavelet packet transform (WPT) and Stockwell transform-based methods.
36 citations
TL;DR: The proposed scheme for a multi-terminal transmission line protection scheme based on wavelet packet transform is efficient and shows high speed and accuracy of fault detection compared to other methods in the literature.
36 citations
Cites methods from "Wavelet-alienation based protection..."
...As part of the generalization, the proposed protection scheme has been applied to the five-bus system shown in Figure 18 and the parameters given in Table 8 [43]....
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...[43] 345 WAAC Current approximate coefficients 1....
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...In [43], a novel scheme was presented for a multi-transmission line using the powerful analysis and decomposition features of WT....
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...The idea of the proposed scheme in [43] was based on wavelet-alienation approximate coefficients (WAAC) using the db2 mother wavelet....
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TL;DR: A novel, protection algorithm based on wavelet-alienation-neural technique for STATCOM-compensated transmission system, validated for various faults at different locations with varying fault impedances and angles of fault incidence is introduced.
Abstract: The custom power devices play important role for enhancing the power transfer capacity of transmission system. However, these devices introduce challenges of under reach or over reach, in the protection of transmission system. This article introduces a novel, protection algorithm based on wavelet-alienation-neural technique for STATCOM-compensated transmission system. For detecting and classifying faults, approximate coefficients are computed from the postfault quarter cycle current waveforms. Fault index, which is summation of alienation coefficients (computed by approximate coefficients) of both the buses, is computed and compared with the threshold magnitude for detecting and classifying the different faults. For the determination of fault location, artificial neural network is applied, with input as three-phase approximate coefficients, evaluated from the voltage and current signals over a time duration of a quarter cycle. Robustness of the developed scheme has been validated for various faults at different locations with varying fault impedances and angles of fault incidence.
30 citations
Cites methods from "Wavelet-alienation based protection..."
...where Aa represents alienation coefficient and ra represents correlation coefficient, which is computed as follows [24]:...
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...Approximate coefficients based alienation coefficients used in this study are computed as follows [24]:...
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References
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TL;DR: The proposed method converges very fast with fewer numbers of training samples compared to neural-network and neuro-fuzzy systems which indicates fastness and accuracy of the proposed method for protection of the transmission line with TCSC.
Abstract: Distance protection of flexible ac transmission lines, including the thyristor-controlled series compensator (TCSC), static synchronous compensator, and static var compensator has been a very challenging task. This paper presents a new approach for the protection of TCSC line using a support vector machine (SVM). The proposed method uses postfault current samples for half cycle (ten samples) from the inception of the fault and firing angle as inputs to the SVM. Three SVMs are trained to provide fault classification, ground detection, and section identification, respectively, for the line using TCSC. The SVMs are trained with polynomial kernel and Gaussian kernel with different parameter values to get the most optimized classifier. The proposed method converges very fast with fewer numbers of training samples compared to neural-network and neuro-fuzzy systems which indicates fastness and accuracy of the proposed method for protection of the transmission line with TCSC
295 citations
TL;DR: In this article, a new scheme to locate a fault on a multi-terminal transmission line is described, which can work for transposed as well as untransposed lines and is free of prefault conditions.
Abstract: This paper describes a new scheme to locate a fault on a multi-terminal transmission line. It describes a simple new algorithm to identify the faulted section first. Then, to exactly locate the fault on this section, a method is described that uses the synchronized voltage measurements at all terminals. The main advantage of this method is that the current-transformer errors in the current measurements can be avoided. Since these errors can be as high as 10%, the fault location is extremely accurate with this method. The scheme can work for transposed as well as untransposed lines and is free of prefault conditions. The paper, after describing the scheme, describes very promising results from an Electromagnetic Transients Program simulation of a multi-terminal transmission line.
155 citations
TL;DR: In this paper, a system is proposed to locate faults on transmission lines using the traveling wave phenomenon, where an ANN is used to estimate the fault location based on the modal information.
Abstract: A system is proposed to locate faults on transmission lines using the traveling wave phenomenon. Prony method is used to analyze the voltage or current signal at the local bus and extract its modal information. This information represents the traveling wave generated by the fault and can be used to estimate its location. Artificial neural networks (ANNs) are used to estimate the fault location based on the modal information. Two schemes are presented: the first with a voltage input signal; and the second with a current input signal. Training and testing data are obtained by ATP-EMTP simulations. Tests were done to study the effect of fault resistance variation and fault incidence angle on both schemes. The system has the advantages of utilizing single-end measurements, using either a voltage or current signal; no pre-fault data is required.
114 citations
TL;DR: A new approach of digital relays for transmission line protection is presented, consisting of a preprocessing module based on discrete wavelet transforms in combination with an artificial neural network for detecting and classifying fault events.
Abstract: A new approach of digital relays for transmission line protection is presented. The proposed technique consists of a preprocessing module based on discrete wavelet transforms (DWTs) in combination with an artificial neural network (ANN) for detecting and classifying fault events. The DWT acts as an extractor of distinctive features in the input signals at the relay location. This information is then fed into an ANN for classifying fault conditions. A DWT with quasioptimal performance for the preprocessing stage is also presented.
112 citations
TL;DR: In this paper, the application of wavelet transforms for the detection, classification, and location of faults on transmission lines is discussed, where a Global Positioning System clock is used to synchronize sampling of voltage and current signals at both the ends of the transmission line.
96 citations