Design of Intelligent Information Monitoring System for Distribution Network and Adjustment of Alarm Threshold

Xiang Ma; Jianye Cui; Zhongming Xiang; Haoliang Du; Jianfeng Huang

doi:10.5626/JCSE.2022.16.2.97

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자료유형: 학술저널

저자정보: Xiang Ma (State Grid Jinhua Power Supply Company) Jianye Cui (State Grid Jinhua Power Supply Company) Zhongming Xiang (State Grid Jinhua Power Supply Company) Haoliang Du (State Grid Jinhua Power Supply Company) Jianfeng Huang (State Grid Jinhua Power Supply Company)

저널정보: Korean Institute of Information Scientists and Engineers Journal of Computing Science and Engineering Journal of Computing Science and Engineering Vol.16 No.2

발행연도: 2022.6

수록면: 97 - 104 (8page)

DOI: 10.5626/JCSE.2022.16.2.97

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In the current distribution network information monitoring system, there are many false alarm information, which forms redundant interference to the fault alarm threshold, and it is difficult to ensure the alarm accuracy of the monitoring system. The distribution network intelligent information monitoring system and the alarm threshold adjustment method based on machine learning are designed, with the physical layer of the system designed to collect the operation status information of each line and equipment of the distribution network according to various sensors, and transfer it to the data layer. The data layer extracts, processes, and classifies the received information, stores it in the database, obtains the abnormal information in the information base, and adjusts the alarm threshold based on the fuzzy clustering method in machine learning, realizing intelligent monitoring of distribution network. The test results show that the detection performance of abnormal information is good, that the abnormal information in the data can be obtained accurately, and that the clustering of the target category of abnormal information can be completed according to the eigenvalue, and has a good threshold adaptive adjustment ability, to maximize the balance between human, machine, and power grid operation state in the process of distribution network monitoring information, ensure real-time and reliable monitoring and alarm results.

#Machine learning #Distribution network #Intelligent monitoring #Information system #Alarm threshold #Fuzzy clustering

참고문헌 (15)

참고문헌 신청

J. Yang, B. Fu, L. Ruan, W. Qiu, and B. Luo, “Intelligent monitoring method for ship distribution network standardization patrol based on two-dimensional code label,” Ship Science and Technology, vol. 41, no. 10, pp. 98-100, 2019.

Z. W. Wang, J. Q. Li, and B. Y. Huang, “Communication bandwidth prediction based on hybrid queue model for condition monitoring service in distribution network,” Electric Power Construction, vol. 40, no. 11, pp. 1-7, 2019.

H. Wang, H. Li, K. Yu, W. Guo, and K. Huang, “Identification of distribution network operation topology based on DSCADA and μPMU telemetry data fusion,” Electric Power Construction, vol. 40, no. 6, pp. 123-131, 2019.

N. J. Wang, S. Han, and Y. G. Luo, “Method for determining the permitted capacity of photovoltaic generation using daily minimum load with confidence interval,” Proceedings of the CSU-EPSA, vol. 32, no. 2, pp. 54-60, 2020.

M. Zhang, M. L. Ding, and B. Cai, “Intelligent monitoring system for wind-solar hybrid power station based on Internet of Things,” Proceedings of the CSU-EPSA, vol. 31, no. 2, pp. 9-13, 2019.

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