A Novel Method of Ground Fault Phase Selection in Weak-Infeed Side

Huang, Shaofeng; Luo, Lan; Cao, Kai

doi:10.1109/tpwrd.2014.2322073

Cited by 33 publications

(20 citation statements)

References 8 publications

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“…In this technique, fault resistances are estimated for discrimination between single-line-to-ground and double-line-to-ground faults. Phase angle difference of superimposed sequence voltages are utilized in some of the relays along with current angle feature for fault type classification in weak-infeed situation [8], [11]. These techniques consider homogeneity in the system and work properly for power networks connecting synchronous generators (SGs).…”

Section: B Literature Reviewmentioning

confidence: 99%

Adaptive Fault Type Classification for Transmission Network Connecting Converter-Interfaced Renewable Plants

Paladhi

Pradhan

2021

IEEE Systems Journal

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Fault ride through compliance as imposed by the grid codes (GCs) prevents the inadvertent disconnection of the renewable plants from the network even during faults. Control algorithms applied in the converters associated with such plants modulate the fault characteristics significantly and result in malfunction of available fault type classifiers at times. In this article, an adaptive fault type classification technique is proposed for transmission network connecting converter-interfaced renewable plants. The method calculates sequence current angles in the faulted loop by determining pure-fault impedance of the plant at every instant during fault using local voltage and current data for fault type identification. The proposed method is tested for different fault situations on renewable integrated standard systems using PSCAD/EMTDC. The performance of the proposed method is found to be accurate in the presence of different types of renewable plants and complying different GC requirements. Comparative assessment reveals its superior performance.

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Section: B Literature Reviewmentioning

confidence: 99%

Adaptive Fault Type Classification for Transmission Network Connecting Converter-Interfaced Renewable Plants

Paladhi

Pradhan

2021

IEEE Systems Journal

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“…For example, θ V2 − θ V0 , the angle difference between the negative and zero sequence voltage, is selected since it captures the incremental of the unbalance level contributed from HIFs to distribution grids. The using of the angle difference between zero and negative sequence voltage is inspired by the work in [5], [29], and the practical engineering experience of the authors. To the best of our knowledge, this feature is utilized in some other fault detection application such as [29], but not in HIF detection before.…”

Section: Effective Feature Set (Efs)mentioning

confidence: 99%

A Feature Selection Method for High Impedance Fault Detection

Cui

El-Arroudi²,

Weng

2019

IEEE Trans. Power Delivery

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High impedance fault (HIF) has been a challenging task to detect in distribution networks. On one hand, although several types of HIF models are available for HIF study, they are still not exhibiting satisfactory fault waveforms. On the other hand, utilizing historical data has been a trend recently for using machine learning methods to improve HIF detection. Nonetheless, most proposed methodologies address the HIF issue starting with investigating a limited group of features and can hardly provide a practical and implementable solution. This paper, however, proposes a systematic design of feature extraction, based on an HIF detection and classification method. For example, features are extracted according to when, how long, and what magnitude the fault events create. Complementary power expert information is also integrated into the feature pools. Subsequently, we propose a ranking procedure in the feature pool for balancing the information gain and the complexity to avoid over-fitting. For implementing the framework, we create an HIF detection logic from a practical perspective. Numerical methods show the proposed HIF detector has very high dependability and security performance under multiple fault scenarios comparing with other traditional methods. Index TermsHigh impedance fault, distribution network, data mining, feature selection. arXiv:1808.04454v1 [eess.SP] 13 Aug 2018 S KF = {s 5 , s 6 , s 7 , s 8 , s 9 , s 10 } = {KF V a cos H3, KF V b cos H3, KF V c cos H3, KF V a sin H3, KF V b sin H3, KF V c sin H3}

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“…Among them, the passive line selection is based on the steady-state signal and transient signal of the power grid fault. A line selection method based on current reactive component is proposed in [6]- [7], 2 while negative-sequence and zero-sequence voltages are used in [8]. However, most distribution networks have their neutral points grounded through arc suppression coil.…”

Section: Introductionmentioning

confidence: 99%

Single-Phase Fault Line Selection in Distribution Network Based on Signal Injection Method

Niu

2021

IEEE Access

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The distribution network with small current grounding mode can ensure high power supply reliability, but it is difficult to locate single-phase grounding fault line. Most of the faults in distribution network are single-phase to ground fault. It is important to locate the fault line timely and accurately for the normal operation of the power grid. In this paper, a fault line selection method based on signal injection is proposed. The dynamic selection of parameters and injection frequency in real-time monitoring distribution network by injection method is analyzed. The accuracy of signal frequency domain conversion is improved by using all phase Fourier transform. Taking the active power consumption of injected signal after fault as the criterion, the accuracy of line selection is improved. Through theoretical analysis and simulation, as well as experiments in a 600V distribution system, the fault line can be accurately selected.

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A Novel Method of Ground Fault Phase Selection in Weak-Infeed Side

Cited by 33 publications

References 8 publications

Adaptive Fault Type Classification for Transmission Network Connecting Converter-Interfaced Renewable Plants

Adaptive Fault Type Classification for Transmission Network Connecting Converter-Interfaced Renewable Plants

A Feature Selection Method for High Impedance Fault Detection

Single-Phase Fault Line Selection in Distribution Network Based on Signal Injection Method

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