Identification between internal and external faults of UHVDC transmission lines based on sequential overlapping derivative transform of voltage transient

Shu, Hongchun; Jiang, Xiaohan; Wang, Xuan; Cao, Ping; Yang, Bo

doi:10.1049/iet-gtd.2020.0395

Cited by 6 publications

(7 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Section: Experimental Results and Analysismentioning

confidence: 99%

“…In order to demonstrate the fault location performance of the proposed method, it is compared with the literature [6], literature [9], literature [10], and the results of the location error at different fault distances are shown in Figure 6. The proposed method Literature [10] Literature [6] Literature [11] Figure 5. Comparison of fault location error results of different methods As can be seen from Figure 5, compared with other methods, the proposed method has the smallest overall fault location error and the smallest error fluctuation, the maximum error is about 0.52 km, and the minimum is about -0.95 km.…”

Section: Experimental Results and Analysismentioning

confidence: 99%

“…There are subjective assumptions, and the fault location error is large, and the absolute value of the error is close to 1.5km. Reference [6] uses the time domain and frequency domain information of the current traveling wave at both ends of the line, and Reference [10] uses the sequential overlapping derivative transform method to locate the fault. Due to the lack of a powerful processing model, the fault location error is large.…”

Section: Experimental Results and Analysismentioning

confidence: 99%

“…For example, in literature [9], by using the shape similarity between voltage signals, the artificial neural network (ANN) is trained as a pattern recognizer to fit the mathematical model between the voltage signal and the fault distance in the line for fault location. In literature [10], the transient voltage signal of the fault line is processed by sequential overlapping derivative transformation to obtain the identification criteria of internal and external faults and realize fast fault identification. However, the traversal process is slow in monitoring long distance and multi fault transmission lines, which cannot give consideration to accuracy and efficiency.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

VSC-HVDC Fault Location Method Based on Effective Feature and Depth Belief Network

Zhai

Cui

et al. 2022

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

Aiming at the problems that most fault location methods are applied to the high voltage direct current (HVDC) transmission system, such as low location accuracy and vulnerability to noise, a voltage source converter (VSC)-HVDC fault location method based on effective feature and deep belief network is proposed. Firstly, the Karenbauer phase mode transform is used to decouple the original fault current data to eliminate the coupling effect between positive and negative lines. Then, Hilbert Huang (HH) transform is used to obtain six effective features of information from frequency domain and time domain analysis to fully characterize the system fault current signal. Finally, the extracted effective features are input into the depth belief network for learning, so as to estimate the fault location in the transmission line. VSC-HVDC system is built based on the MATLAB platform for experimental analysis. The results show that the fault location obtained by the proposed method has the smallest overall fault location error, and the maximum and minimum errors are divided into about 0.52 km and -0.95 km. Compared with other methods, it has certain advantages in fault location.

show abstract

Section: Experimental Results and Analysismentioning

confidence: 99%

Section: Experimental Results and Analysismentioning

confidence: 99%

Section: Experimental Results and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

VSC-HVDC Fault Location Method Based on Effective Feature and Depth Belief Network

Zhai

Cui

et al. 2022

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

show abstract

“…Its essence is high order difference. The higher the order of difference is, the more the result can reflect the characteristics and mutation direction of high frequency transient signal [25].…”

Section: Sequential Overlapping Derivative Transformmentioning

confidence: 99%

A novel transient directional pilot protection principle based on sequential overlapping derivative transform for AC transmission lines

Wang

et al. 2022

IET Generation Trans & Dist

View full text Add to dashboard Cite

The access of large‐scale renewable energy and power electronic equipment to the power grid makes the power source and short‐circuit paths possess time‐varying characteristics when faults occur, which has a serious impact on the traditional protection based on power frequency components. Besides, higher requirements are needed for relay protection in the power grid. The transient fault current contains a large amount of fault information. First, the bus capacitance has a strong reflection effect on the high frequency signal, and there are obvious differences in the high frequency component of the fault current of internal and external faults. Next, a transient quantity algorithm based on sequential overlapping derivative transform is introduced. The algorithm can effectively suppress the low frequency component and enhance the high frequency component in the current, which simply and effectively highlights the difference between the transient current of internal and external faults. Finally, through the ratio of high frequency energy of each outgoing line, the fault direction can be accurately determined, and the transient directional pilot protection can be formed. The accuracy of the protection scheme is verified by a large number of simulation experiments.

show abstract

An enhanced distance protection algorithm based on characteristics-travelling waves measured from the current for HVDC Lines

Mourad

2022

Electric Power Systems Research

View full text Add to dashboard Cite

Identification between internal and external faults of UHVDC transmission lines based on sequential overlapping derivative transform of voltage transient

Cited by 6 publications

References 34 publications

VSC-HVDC Fault Location Method Based on Effective Feature and Depth Belief Network

VSC-HVDC Fault Location Method Based on Effective Feature and Depth Belief Network

A novel transient directional pilot protection principle based on sequential overlapping derivative transform for AC transmission lines

An enhanced distance protection algorithm based on characteristics-travelling waves measured from the current for HVDC Lines

Contact Info

Product

Resources

About