A new algorithm for busbar protection based on the comparison of initial traveling wave power

Wu, Hao; Dong, Xingxing; Ye, Ruikai

doi:10.1002/tee.22835

Cited by 7 publications

(3 citation statements)

References 12 publications

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“…The wave impedances of lines named OA, OB, OC, AD, BE, CF are Z C1 ~ZC6 respectively. According to the fact that the line wave impedance is approximately a real constant [27], and the equivalent capacitance impedance of bus C to ground is Z CC .…”

Section: Initial Traveling Wave Power Distribution Of Fault In the Pr...mentioning

confidence: 99%

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A new method for fault identification of T-connection transmission line based on multi-scale traveling wave reactive power and random forest

Zhong,

Yang,

Wang

et al. 2023

PLoS ONE

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Though the traditional fault diagnosis method of T-connected transmission lines can identify the faults inside and outside the area, it can not identify the specific branches. To improve the accuracy and reliability of fault diagnosis of T-connection transmission lines, a new method is proposed to identify specific faulty branches of T-connection transmission lines based on multi-scale traveling wave reactive power and random forest. Based on the S-transform, the mean and sum ratios of the corresponding short-time series traveling wave reactive powers of each two traveling wave protection units at multiple frequencies are calculated respectively to form the fault feature vector sample set of the T-connection transmission line. A random forest fault branch identification model is established, and it is trained and tested by the fault feature sample set of T-connection transmission line to identify the fault branch. The simulation results show that the proposed algorithm can identify the branch where the fault is located inside and outside the protection zone of T-connection transmission line quickly and accurately under various working conditions. This method also shows good performance to identify faults even under the situation of CT saturation, noise influence and data loss.

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Section: Initial Traveling Wave Power Distribution Of Fault In the Pr...mentioning

confidence: 99%

“…In this paper, Clark phase mode transformation is used to decouple the voltage and current of each phase. And then the combined modulus method is used to reflect various fault types of T-connection transmission line [24,27],…”

Section: Plos Onementioning

confidence: 99%

A new method for fault identification of T-connection transmission line based on multi-scale traveling wave reactive power and random forest

Zhong,

Yang,

Wang

et al. 2023

PLoS ONE

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“…Bus fault will cause damage to related electrical equipment, and may cause regional power failure [11]. Reference [12] introduces the ratio of comprehensive active driving quantity to active braking quantity to specify the protection criterion. Single-ended traveling wave protection does not need communication channel and time synchronization.…”

Section: Introductionmentioning

confidence: 99%

Boundary Protection Based on S-Transform Considering Fault Factors

Guo,

Huang,

Deng

et al. 2024

Electronics

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Boundary protection is a protection that takes advantage of the characteristic that signals will be attenuated when passing through the “line boundary”. The location of the traps and current transformers in the structure of extra-high voltage (EHV) transmission lines makes it difficult to apply current-based travelling wave protection in engineering practice. If the protection is put into use, it is necessary to carry out a large number of engineering modifications to the existing transmission lines, which greatly increases the economic cost. And after simulation, the protection will be misjudged under weak fault conditions, and it has low reliability. After analyzing the influence of fault factors, a boundary protection method using high-frequency voltage component energy is proposed. The fault signal is processed by S-transform, and the transient voltage energy is normalized with the initial fault phase and transition resistance. The reduced characteristic quantity is used to construct a criterion to judge the fault condition of the protection line. This protection eliminates the influence of fault factors on transient protection. The ATP-Draw 6.0 simulation results based on the proposed protection scheme show that the protection scheme can distinguish internal and external faults, and can work normally under weak faults with high reliability.

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A hybrid intelligent busbar protection strategy using hyperbolic S‐transforms and extreme learning machines

Rahimnejad

Gil

Abdoos

et al. 2021

Engineering Reports

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In power systems, busbars connect important components such as generators, transmission lines, and loads. A typical fault occurrence on the busbar may result in the isolation of faulty sections from other normally operating parts of the system resulting from differential protection operation. Although the main busbars' protection scheme is differential protection, its operation is significantly affected by magnetic saturation of the current transformer (CT), particularly during external fault occurrence or energizing power transformers. Saturation of the CT may generate a spurious differential current and is the main reason for the differential scheme malfunctioning. Previous research presented different methods to modify and improve busbars' differential protection scheme. However, there has been lack of a comprehensive study to assess the efficiency of the busbar protection scheme regarding all involved, and influencing aspects including various fault types, energizing power transformer, (high) fault resistance, fault angle (changing from 0 • to 360 • ), and the angle of the sources. Thus, in this study, a hybrid intelligent busbar protection scheme is proposed and the effects of all these factors are investigated. The proposed strategy utilizes the hyperbolic S-transform as a signal processing technique to extract an efficient feature that is able to discriminate internal faults from other abnormal modes, that is, external faults and inrush current under CT saturation. To obtain this goal, a learning-based classification method known as extreme learning machines is used to classify the system conditions based on the selected features. The proposed protection scheme was found to have low sensitivity to CT saturation and noise and was able to accurately detect internal faults from half a cycle to one cycle of the power system depending on the fault resistance.

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A new algorithm for busbar protection based on the comparison of initial traveling wave power

Cited by 7 publications

References 12 publications

A new method for fault identification of T-connection transmission line based on multi-scale traveling wave reactive power and random forest

A new method for fault identification of T-connection transmission line based on multi-scale traveling wave reactive power and random forest

Boundary Protection Based on S-Transform Considering Fault Factors

A hybrid intelligent busbar protection strategy using hyperbolic S‐transforms and extreme learning machines

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