An Enhanced Impedance Trajectory-Based Adaptive Distance Protection for Renewable Energy Systems

Considering the significant risk of malfunction or non-operation in single-phase faults with fault resistance occurring in renewable energy transmission lines, this paper proposes a novel distance protection scheme based on modified impedance trajectory, using transient component. Firstly, multiple fault characteristics of the entire frequency band are extracted utilizing synchronous squeezing S-transform (SST) and S-transform (ST)methods. On this basis, a classifier based on artificial neural networks (ANN) for identifying low-resistance and high-resistance grounding faults is constructed. Then, attenuation coefficients and delayed coefficients are derived by utilizing ST coefficient matrix, and the expression for the fault resistance is deduced. Finally, the impedance trajectory is modified that compensates for additional impedance. The proposed protection is validated on the RTDS platform, the results show that it is unaffected by the weak infeed and strongly withstand the fault resistance, operates rapidly and reliably without communication and delay, and has anti-interference performance.

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Publication Details

Published
2024-11-29
DOI
https://doi.org/10.1109/ei264398.2024.10991537
Citations
1
Primary Topic
Smart Grid Security and Resilience
Type
article
Field-Weighted Citation Impact
0.33
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An Enhanced Impedance Trajectory-Based Adaptive Distance Protection for Renewable Energy Systems

Zebang Yang, Lanlan Qu, Lei Xia, Hui Li et al.
1 citations
Smart Grid Security and Resilience
0.33
article

An Enhanced Impedance Trajectory-Based Adaptive Distance Protection for Renewable Energy Systems

Zebang Yang, Lanlan Qu, Lei Xia, Hui Li, Yifan Li, Bing Hou
article en
1 citations

Abstract

Considering the significant risk of malfunction or non-operation in single-phase faults with fault resistance occurring in renewable energy transmission lines, this paper proposes a novel distance protection scheme based on modified impedance trajectory, using transient component. Firstly, multiple fault characteristics of the entire frequency band are extracted utilizing synchronous squeezing S-transform (SST) and S-transform (ST)methods. On this basis, a classifier based on artificial neural networks (ANN) for identifying low-resistance and high-resistance grounding faults is constructed. Then, attenuation coefficients and delayed coefficients are derived by utilizing ST coefficient matrix, and the expression for the fault resistance is deduced. Finally, the impedance trajectory is modified that compensates for additional impedance. The proposed protection is validated on the RTDS platform, the results show that it is unaffected by the weak infeed and strongly withstand the fault resistance, operates rapidly and reliably without communication and delay, and has anti-interference performance.

North China Electric Power University (CN), State Grid Corporation of China (China) (CN), State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources
Affordable and clean energy
Openalex Percentile: Top 35%
Smart Grid Security and Resilience
0.33
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