A New Criterion for Transformer Excitation Inrush Current Identification Based on the Wasserstein Distance Algorithm
To circumvent the computational bottlenecks associated with the intermediate steps (e.g., least squares fitting) in conventional sine wave similarity principles and directly acquire the energy metrics required for stabilized sinusoidal waveform characterization, this study leverages time domain prob...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-07-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/14/3872 |
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| author | Shanshan Zhou Jingguang Huang Yuanning Zhang Yulong Li |
| author_facet | Shanshan Zhou Jingguang Huang Yuanning Zhang Yulong Li |
| author_sort | Shanshan Zhou |
| collection | DOAJ |
| description | To circumvent the computational bottlenecks associated with the intermediate steps (e.g., least squares fitting) in conventional sine wave similarity principles and directly acquire the energy metrics required for stabilized sinusoidal waveform characterization, this study leverages time domain probability distribution theory. From a complementary advantage perspective, a novel transformer inrush current identification criterion is developed using the Wasserstein distance metric. The methodology employs feature discretization to extract target/template signals, transforming them into state vectors for sample labelling. By quantifying inter-signal energy distribution disparities through this framework, it achieves a precise waveform similarity assessment in sinusoidal regimes. The theoretical analysis and simulations demonstrate that the approach eliminates frequency domain computations while maintaining implementation simplicity. Compared with conventional sine wave similarity methods, the solution streamlines protection logic and significantly enhances practical applicability with accelerated response times. Furthermore, tests conducted on field-recorded circuit breaker closing waveforms using MATLAB R2022a confirm the effectiveness of the proposed method in improving transformer protection performance. |
| format | Article |
| id | doaj-art-6edcc652f4634da6b2e76155f50e4e8e |
| institution | Kabale University |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-6edcc652f4634da6b2e76155f50e4e8e2025-08-20T03:35:37ZengMDPI AGEnergies1996-10732025-07-011814387210.3390/en18143872A New Criterion for Transformer Excitation Inrush Current Identification Based on the Wasserstein Distance AlgorithmShanshan Zhou0Jingguang Huang1Yuanning Zhang2Yulong Li3National Virtual Simulation Experiment Centre for Electrical Engineering, China Three Gorges University, Yichang 443002, ChinaNational Virtual Simulation Experiment Centre for Electrical Engineering, China Three Gorges University, Yichang 443002, ChinaSuper High Voltage Company of State Grid Hubei Electric Power Co., Ltd., Wuhan 430050, ChinaNational Virtual Simulation Experiment Centre for Electrical Engineering, China Three Gorges University, Yichang 443002, ChinaTo circumvent the computational bottlenecks associated with the intermediate steps (e.g., least squares fitting) in conventional sine wave similarity principles and directly acquire the energy metrics required for stabilized sinusoidal waveform characterization, this study leverages time domain probability distribution theory. From a complementary advantage perspective, a novel transformer inrush current identification criterion is developed using the Wasserstein distance metric. The methodology employs feature discretization to extract target/template signals, transforming them into state vectors for sample labelling. By quantifying inter-signal energy distribution disparities through this framework, it achieves a precise waveform similarity assessment in sinusoidal regimes. The theoretical analysis and simulations demonstrate that the approach eliminates frequency domain computations while maintaining implementation simplicity. Compared with conventional sine wave similarity methods, the solution streamlines protection logic and significantly enhances practical applicability with accelerated response times. Furthermore, tests conducted on field-recorded circuit breaker closing waveforms using MATLAB R2022a confirm the effectiveness of the proposed method in improving transformer protection performance.https://www.mdpi.com/1996-1073/18/14/3872Wasserstein distancefault currentinrush currentenergy distribution |
| spellingShingle | Shanshan Zhou Jingguang Huang Yuanning Zhang Yulong Li A New Criterion for Transformer Excitation Inrush Current Identification Based on the Wasserstein Distance Algorithm Energies Wasserstein distance fault current inrush current energy distribution |
| title | A New Criterion for Transformer Excitation Inrush Current Identification Based on the Wasserstein Distance Algorithm |
| title_full | A New Criterion for Transformer Excitation Inrush Current Identification Based on the Wasserstein Distance Algorithm |
| title_fullStr | A New Criterion for Transformer Excitation Inrush Current Identification Based on the Wasserstein Distance Algorithm |
| title_full_unstemmed | A New Criterion for Transformer Excitation Inrush Current Identification Based on the Wasserstein Distance Algorithm |
| title_short | A New Criterion for Transformer Excitation Inrush Current Identification Based on the Wasserstein Distance Algorithm |
| title_sort | new criterion for transformer excitation inrush current identification based on the wasserstein distance algorithm |
| topic | Wasserstein distance fault current inrush current energy distribution |
| url | https://www.mdpi.com/1996-1073/18/14/3872 |
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