Real‐time digital filtering algorithm for elimination of the decaying DC component using mathematical morphology

Godse, Revati; Bhat, Sunil

doi:10.1049/iet-gtd.2018.5476

Cited by 10 publications

(6 citation statements)

References 34 publications

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“…The development of edge computing corroborates the intellectual development of power grids. Fig 5 shows an edge computing-based relay protection system for the delayed and real-time traditional power grid relay protection [ 26 , 27 ]. In this system, the critical data are transmitted to the edge device by the relay protection equipment and its intelligent terminals.…”

Section: Methodsmentioning

confidence: 99%

A security technology of power relay using edge computing

2021

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The purposes are to find the techniques suitable for the safety relay protection of intelligent substations and discuss the applicability of edge computing in relay protection. Regarding relay protection in intelligent substations, edge computing and optimized simulated annealing algorithm (OSAA) are combined innovatively to form an edge computing strategy. On this basis, an edge computing model is proposed based on relay fault traveling waves. Under different computing shunt tasks, OSAA can converge after about 1,100 iterations, and its computing time is relatively short. As the global optimal time delay reaches 0.5295, the corresponding computing time is 456.27s, apparently better than the linear search method. The proposed model can reduce the computing time significantly, playing an active role in the safe shunting of power relays. The simulation also finds that the voltage and current waveforms corresponding to the fault state of Phase A are consistent with the actual situations. To sum up, this model provides a reference for improving and optimizing intelligent substation relay protection.

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Section: Methodsmentioning

confidence: 99%

A security technology of power relay using edge computing

2021

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“…In the absence of optimal hyper-plane, the aim of SVM is to maximize the margin and to minimize the number of errors. This hyper-plane is obtained by solving the optimization problem [25] as:…”

Section: Basics Of Support Vector Machine (Svm)mentioning

confidence: 99%

“…Hence, SVM is further modified to address the multiclassification problems. For this, two types of tactics are defined as: 1) to amend the designed SVM model to include the multiclass learning in the quadratic solving algorithm and 2) to blend numerous binary classifiers [25]. The later one involves the techniques like one-versus-all (OVA) and one-versus-one (OVO).…”

Section: Basics Of Support Vector Machine (Svm)mentioning

confidence: 99%

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Combined morphology and SVM-based fault feature extraction technique for detection and classification of transmission line faults

Godse¹,

Bhat²

2020

Turk J Elec Eng & Comp Sci

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A transmission line is the main commodity of power transmission network through which power is transmitted to the utility. These lines are often swayed by accidental breakdowns owing to different random origins. Hence, researchers try to detect and track down these failures at the earliest to avoid financial prejudice. This paper offers a new realtime mathematical morphology based approach for fault feature extraction. The morphological open-close-median filter is exploited to wrest unique fault features which are then fed as an input to support vector machine to detect and classify the short circuit faults. The acquired graphical and numerical results of the extracted fault features affirm the potency of the offered scheme. The proposed scheme has been verified for different fault cases simulated on high-voltage transmission line modelled using ATP/EMTP with varying system constraints. The performance of the stated technique is also validated for fault detection and classification in real-field transmission lines. The results state that the proposed method is capable of detecting and classifying the faults with adequate precision and reduced computational complexity, in less than quarter of a cycle.

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“…Another auxiliary filter is proposed in [22], Characteristic Harmonic Digital Filter (CharmDF), attenuating the DDC component prior to applying the DFT filter. In [23], a morphological median filter (MMF) is proposed to filter out the DDC component from fault current prior to applying the DFT filter. A method is reported in [24] that estimates the DDC component by two auxiliary filters of Hilbert transform and full‐cycle integration of fault current signal.…”

Section: Introductionmentioning

confidence: 99%

Two modified DFT‐based algorithms for fundamental phasor estimation

Afrandideh

Arabshahi

Fazeli

2022

IET Generation Trans & Dist

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The discrete Fourier transform (DFT) is a powerful phasor estimation algorithm conventionally used in digital relaying applications. The DFT-based phasor estimation is usually accompanied by oscillatory error due to the presence of the decaying DC (DDC) components in fault current signals. Accordingly, two modified DFT-based phasor estimation algorithms are proposed in this paper. The proposed algorithms accurately estimate the exact fundamental phasor by extracting the DDC components using successive outputs of the conventional DFT algorithm. The performance of the proposed algorithms is validated by the mathematically generated and PSCAD-simulated signals and is compared with previous algorithms. The results demonstrate that the proposed algorithms in this paper are more robust than other ones. Moreover, they are applicable in the DFT algorithm with different data windows. INTRODUCTIONThe fundamental phasor estimation plays an important role in detecting, locating, and discriminating faults in power systems. There are a number of conventional phasor estimation algorithms, that include: discrete Fourier transform (DFT), least-square error (LSE), discrete wavelet transform (DWT), Kalman filters, discrete Hartley transform (DHT), and artificial neural networks (ANNs) [1][2][3][4]. The discrete Fourier transform (DFT) is a powerful phasor estimation algorithm, widely used in digital relaying applications due to its simplicity, accuracy, and speed. The DFT algorithm has a high capability to estimate the fundamental phasor of periodic sinusoidal signals. However, its performance is extremely influenced by non-periodic signals such as decaying DC components (DDCs), which are created in the current and voltage signals during fault conditions. This issue causes an undesired oscillating error in the estimated phasor, especially phase angle. Although this error decays after a certain period of time (depending on the time constant of the DDC component), it extremely reduces the speed and accuracy of decision-making in relays. The DDC component has two parameters, the initial value and time constant, which depend on fault inception angle and the value of pathway X ∕R ratio, respectively. Because the source impedance and line X ∕R ratio are so close to each other, the initial value ofThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Real‐time digital filtering algorithm for elimination of the decaying DC component using mathematical morphology

Cited by 10 publications

References 34 publications

A security technology of power relay using edge computing

A security technology of power relay using edge computing

Combined morphology and SVM-based fault feature extraction technique for detection and classification of transmission line faults

Two modified DFT‐based algorithms for fundamental phasor estimation

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