A novel non-unit transient based boundary protection for HVDC transmission lines using synchrosqueezing wavelet transform

Duan, Jiandong; Li, Hao; Yang, Libo; Lihao, Tuo

doi:10.1016/j.ijepes.2019.105478

Cited by 35 publications

(21 citation statements)

References 24 publications

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“…The maximum detectable fault resistance of the proposed algorithm is also higher compared to the methods in [8–11, 17, 18, 24–26]. The sampling frequency of the proposed algorithm is higher than the methods in [17, 18, 25], is equal to [22] and is less than [8–11, 14–16, 19–21, 23, 24, 26]. Compared to the methods in [22, 26], the proposed algorithm needs a shorter data window.…”

Section: Comparison With the Other Workmentioning

confidence: 96%

“…Compared to the methods in [22, 26], the proposed algorithm needs a shorter data window. The proposed protection and the protections in [8–10, 20–26] do not need GPS and communication link so they are more reliable since there is no risk of loss of synchronism or communication link failure.…”

Section: Comparison With the Other Workmentioning

confidence: 99%

“…In the work of Duan et al . [20], a single‐end protection method is proposed based on the transmission differences between tuning and low‐frequency voltages. The method uses synchrosqueezing wavelet transform and the ratio of the positive and negative voltage micro‐increment to select the faulted line.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Single‐end protection algorithm for HVDC transmission lines based on the current difference

Mehrabi‐Kooshki

Mirhosseini

Jamali

2020

IET Generation, Transmission & Distribution

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Section: Comparison With the Other Workmentioning

confidence: 96%

Section: Comparison With the Other Workmentioning

confidence: 99%

See 1 more Smart Citation

Single‐end protection algorithm for HVDC transmission lines based on the current difference

Mehrabi‐Kooshki

Mirhosseini

Jamali

2020

IET Generation, Transmission & Distribution

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“…It can be seen from the above formulas that the wavelet transform W 1 f (s, t) can be obtained by the first order differential and the W 2 f (s, t) can be obtained by the second order differential. e discontinuous point of f(t) corresponds to the modulus maximum point of W 1 f (s, t) and the zero point of W 2 f (s, t) [18,19]. However, the electrical quantity of the nonfault point will be disturbed during the signal transmission, which will affect the accuracy of the Complexity 3 zero-crossing detection, so the result of the zero-crossing detection is usually not a discontinuity point, but an inflection point of the signal, and the modulus maximum detection is more reliable than zero-crossing detection [20,21].…”

Section: Modulus Maximum Detectionmentioning

confidence: 99%

Fault Detection of the Power System Based on the Chaotic Neural Network and Wavelet Transform

Wang

2020

Complexity

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The safety and stability of the power supply system are affected by some faults that often occur in power system. To solve this problem, a criterion algorithm based on the chaotic neural network (CNN) and a fault detection algorithm based on discrete wavelet transform (DWT) are proposed in this paper. MATLAB/Simulink is used to establish the system model to output fault signals and travelling wave signals. Db4 wavelet decomposes the travelling wave signals into detail signals and approximate signals, and these signals are combined with the two-terminal travelling wave location method to achieve fault location. And the wavelet detail coefficients are extracted to input to the proposed chaotic neural network. The results show that the criterion algorithm can effectively determine whether there are faults in the power system, the fault detection algorithm has the capabilities of locating the system faults accurately, and both algorithms are not affected by fault type, fault location, fault initial angle, and transition resistance.

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“…The summation of the absolute values of level 2 detail coefficients was calculated, and the absolute value of the differentiation of this summation was proposed as a new index for detecting fault clearance to determine the reclosing instant. In DC systems, the WT was applied in high-voltage DC systems [29][30][31][32]. Therefore, the WT can be applied to protection in an LVDC microgrid.…”

Section: Introductionmentioning

confidence: 99%

Development of New Protection Scheme in DC Microgrid Using Wavelet Transform

Seo¹

2022

Energies

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The demand for a low voltage direct current (LVDC) microgrid is increasing by the increase of DC-based digital loads and renewable resources and the rapid development of power electronics technology. For the stable operation of an LVDC microgrid, it is necessary to develop a protection method. In this paper, the new protection scheme considering the fault section is proposed using wavelet transform (WT) in an LVDC microgrid. The fault sections are classified into DC side of the alternating current (AC)/DC converter, DC/DC converter connected to photovoltaic (PV) system, DC line, and DC bus. The characteristics of fault current at each fault section are analyzed. Based on these analyses, the new protection scheme including the fault section estimation is proposed using WT. The proposed scheme estimates the fault section using the detail component after performing WT and sends the trip signal to each circuit breaker according to the fault section. The proposed protection scheme is verified through various simulations according to the fault region and fault current using electromagnetic transient program (EMTP)/ATPDraw and MATLAB. The simulation results show that the fault section is accurately determined, and the corresponding circuit breaker (CB) operations are performed.

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A novel non-unit transient based boundary protection for HVDC transmission lines using synchrosqueezing wavelet transform

Cited by 35 publications

References 24 publications

Single‐end protection algorithm for HVDC transmission lines based on the current difference

Single‐end protection algorithm for HVDC transmission lines based on the current difference

Fault Detection of the Power System Based on the Chaotic Neural Network and Wavelet Transform

Development of New Protection Scheme in DC Microgrid Using Wavelet Transform

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