Impedance differential plane for fault detection and faulty phase identification of FACTS compensated transmission line

Kumar, B. Suresh; Yadav, Anamika; Pazoki, Mohammad

doi:10.1002/etep.2804

Cited by 13 publications

(6 citation statements)

References 25 publications

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“…Over the years, distance relay-based transmission line protection schemes were adapted for secure and reliable operation of power systems [12][13][14]. But the presence of series/shunt FACTS devices leads to mal-operation of this conventional relay to detect and locate the fault [15,16]. Moreover, the fault signal is non-stationary in nature, and the analysis of such a signal is a cumbersome process.…”

Section: Introductionmentioning

confidence: 99%

Fault Detection and Classification of Shunt Compensated Transmission Line Using Discrete Wavelet Transform and Naive Bayes Classifier

et al. 2020

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This paper presents the methodology to detect and identify the type of fault that occurs in the shunt compensated static synchronous compensator (STATCOM) transmission line using a combination of Discrete Wavelet Transform (DWT) and Naive Bayes (NB) classifiers. To study this, the network model is designed using Matlab/Simulink. Different types of faults, such as Line to Ground (LG), Line to Line (LL), Double Line to Ground (LLG) and the three-phase (LLLG) fault, are applied at disparate zones of the system, with and without STATCOM, considering the effect of varying fault resistance. The three-phase fault current waveforms obtained are decomposed into several levels using Daubechies (db) mother wavelet of db4 to extract the features, such as the standard deviation (SD) and energy values. Then, the extracted features are used to train the classifiers, such as Multi-Layer Perceptron Neural Network (MLP), Bayes and the Naive Bayes (NB) classifier to classify the type of fault that occurs in the system. The results obtained reveal that the proposed NB classifier outperforms in terms of accuracy rate, misclassification rate, kappa statistics, mean absolute error (MAE), root mean square error (RMSE), percentage relative absolute error (% RAE) and percentage root relative square error (% RRSE) than both MLP and the Bayes classifier.

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Section: Introductionmentioning

confidence: 99%

Fault Detection and Classification of Shunt Compensated Transmission Line Using Discrete Wavelet Transform and Naive Bayes Classifier

et al. 2020

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“…The presence of UPFC in a transmission system significantly control the power flow and improves the dynamic stability of the system by controlling three major parameters like voltage magnitude, its phase angle and impedance of the line. But, the inclusion of FACTS devices in the system affects the existing transmission line protection system 3,4 . The presence of FACTS device in the fault loop can influence the magnitude and phase angle of the fundamental voltage and current signals at the relaying point and thereby affecting the performance of the existing protection schemes.…”

Section: Introductionmentioning

confidence: 99%

Intrinsic time decomposition based fault location scheme for unified power flow controller compensated transmission line

Mishra

Gupta

Yadav

2020

Int Trans Electr Energ Syst

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The transmission line fault location algorithms are affected in presence of FACTS device like unified power flow controller (UPFC) due to changed voltage and currents signals at the relaying point after occurrence of fault. Additionally, these algorithms involve high computation burden associated with signal processing techniques and are proven to be in‐efficient during severe power system conditions. To eliminate the limitations stated above, a novel travelling wave aided intrinsic time‐decomposition (ITD) based fault location algorithm is presented in this paper for estimation of fault location in UPFC employed transmission lines. ITD offers several advantages over other time‐frequency‐energy (TFE) analysis tools such as presenting precise temporal information and involving less computation burden. ITD decomposes a given signal into a sum of proper rotation components (PRCs) followed by a monotonic trend. The proposed ITD based fault location algorithm estimates the arrival times of travelling waves from first PRC of modal voltage signals of the terminals to which the transmission line is connected. From the estimated arrival times, the fault location is calculated. For simulation, a 100 MVA UPFC controlling the power flows in a 500 kV transmission system is used. Different cases of faults with diverse power system conditions are applied to examine the robustness and efficacy of ITD based fault location algorithm. Further, ITD base method is compared to existing methods available in literature and found to be a better performer in the context of fault localization.

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“…Implementation of such scheme requires perfect elimination of channel delays and fine tuning of channel data at both ends which can be also affected by worst weather conditions. Further, Kumar et al, 22 has presented impedance differential plane based fault detection and fault phase identification for FACTS compensated transmission line. The protection scheme is again based on synchronized phasor measurement at both ends.…”

Section: Introductionmentioning

confidence: 99%

Supervised relevance vector machine based dynamic disturbance classifier for series compensated transmission line

Patel

Chothani

Bhatt

2020

Int Trans Electr Energ Syst

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Background: Nowadays, numerical relays configured through power swing blocking function are vulnerable to faults with high impedance owing to nonlinearities present in the faulty path. Identification of symmetrical high impedance faults incepting during the power swing scenario is of prime importance for protection engineers to avoid cascade tripping. It is analyzed that the classical approaches for symmetrical fault detection during power swing can maloperate owing to high level of uncertainty arise during validation of high impedance fault, symmetrical faults and cross country faults during power swing with varied level of compensation which has been explored in this research.Aims: This paper presents an innovative scheme for series compensated line by utilizing the capability of Relevance Vector Machine (RVM) as a disturbance classifier taking into consideration of cross country faults, CT saturation; power swings prone to symmetrical faults along with high impedance faults in comparison with prevailing methods. Materials & Methods:In order to validate the proposed RVM based disturbance classifier algorithm, different kinds of faults and power swing situations have been applied in IEEE 9 bus test system using PSCAD/EMTDC software followed by validation in MATLAB. The features of sequence components of currents are estimated using Modified Full Cycle Discrete Fourier Transform (MFCDFT). The extracted features are used as control inputs to RVM for discernment among power swing and fault under the influence of wide range of system and fault dynamics.

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Impedance differential plane for fault detection and faulty phase identification of FACTS compensated transmission line

Cited by 13 publications

References 25 publications

Fault Detection and Classification of Shunt Compensated Transmission Line Using Discrete Wavelet Transform and Naive Bayes Classifier

Fault Detection and Classification of Shunt Compensated Transmission Line Using Discrete Wavelet Transform and Naive Bayes Classifier

Intrinsic time decomposition based fault location scheme for unified power flow controller compensated transmission line

Supervised relevance vector machine based dynamic disturbance classifier for series compensated transmission line

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