| Issue |
E3S Web Conf.
Volume 252, 2021
2021 International Conference on Power Grid System and Green Energy (PGSGE 2021)
|
|
|---|---|---|
| Article Number | 01006 | |
| Number of page(s) | 6 | |
| Section | Power Control Technology and Smart Grid Application | |
| DOI | https://doi.org/10.1051/e3sconf/202125201006 | |
| Published online | 23 April 2021 | |
Dynamic Monitoring of Low Voltage Distribution Network Leakage Detection Device Based on Internet of Things Technology
1 State Grid Liaoning Electric Power Co., LTD., Shenyang, Liaoning 110000, China
2 Electric Power Research Institute, State Grid Liaoning Electric Power Co., LTD., Shenyang, Liaoning 110000, China
* E-mail: yidaiyaorao@163.com
The existing dynamic monitoring methods of low-voltage distribution network leakage detection device have been unable to meet the needs of the distribution network in China. Therefore, a dynamic monitoring method of low-voltage distribution network leakage detection device based on Internet of Things technology is proposed. Based on the introduction of the Internet of Things technology sensor sensing technology, the sensor is installed on the leakage detection device to obtain the operation data of the leakage detection device and preprocess it with noise reduction and normalization. At the same time, the statistical analysis of partial discharge signal is carried out to extract the characteristics of fast waveform signal (energy parameters, sample entropy and modal components). Based on the operation data features of the leakage detection device extracted above, the state diagnosis framework of the leakage detection device is built to diagnose the state of the leakage detection device, and the dynamic monitoring of the leakage detection device in low-voltage distribution network is realized. The experimental results show that: compared with the existing methods, the proposed method has stronger anti-interference ability and smaller monitoring error, which fully proves that the proposed method has better application effect.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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