Research Article
Online Monitoring Method for Hazard Source of Power System Network Based on Mobile Internet
@INPROCEEDINGS{10.1007/978-3-030-67874-6_13, author={Jie-sheng Zheng and Bo-jian Wen and Wen-bin Liu and Guang-cai Wu and Gao Shang}, title={Online Monitoring Method for Hazard Source of Power System Network Based on Mobile Internet}, proceedings={Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part II}, proceedings_a={ADHIP PART 2}, year={2021}, month={1}, keywords={Mobile internet Power system Network hazard source On-line monitoring}, doi={10.1007/978-3-030-67874-6_13} }- Jie-sheng Zheng
Bo-jian Wen
Wen-bin Liu
Guang-cai Wu
Gao Shang
Year: 2021
Online Monitoring Method for Hazard Source of Power System Network Based on Mobile Internet
ADHIP PART 2
Springer
DOI: 10.1007/978-3-030-67874-6_13
Abstract
In the power system network, aiming at the low accuracy of traditional network hazard online monitoring method, an online monitoring method for hazard source of power system network based on mobile internet is proposed. Based on mobile internet, a power system network communication is constructed. The model uses this model to collect dangerous source data. After the hazard data is collected, the WAMS system is used to calculate the relative residuals of the hazard source data, and then the relative residuals are used to identify the hazard source parameters, and the branch with the hazard source parameters is present. The traveling wave positioning network is used to locate the dangerous source. After the hazard source is located, the hazard source is monitored online by the hazard source indicator. Under the condition that the experimental environment is the same, the method is compared with the online hazard source online monitoring method based on feature recognition technology and the online hazard source online monitoring method based on communication message parsing. The monitoring accuracy of these three methods is improved. The results are 41.1%, 68.8%, and 94.5%, respectively. The experimental results show that the monitoring accuracy of this method is higher than the traditional online hazard source online monitoring method, which proves the superiority of the method.
