Design of Intelligent Information Monitoring System for Distribution Network and Adjustment of Alarm Threshold
Authors: Ma, X., Cui, J., Xiang, Z., Du, H., Huang, J.
Journal: Journal of Computer Science Review and Engineering (JCSRE), ISSN 1694-4488
Citation: JCSRE 4(2), 2022-08-12.
DOI: 10.5626/jcse.2022.16.2.97
Type: Original Research
Abstract
The safe and reliable operation of the distribution network is particularly important. In order to monitor the operation status of the distribution network more accurately, find hidden dangers in time, and improve the intelligent operation level of the distribution network, this paper designs a set of intelligent monitoring system for the distribution network. The system builds a basic data layer, a historical data layer, a real‐time operation layer, and an application layer. The basic data layer stores various basic data of the distribution network such as equipment parameters and network structure; the historical data layer stores a large amount of historical operational data such as load, voltage, and current; the real‐time operation layer collects real‐time operational data of the distribution network through sensors and communication networks; the application layer provides various intelligent applications such as fault diagnosis, load forecasting, and alarm processing. In response to the problem that it is difficult for the traditional distribution network monitoring system to adjust the alarm threshold based on the actual operation situation, this paper proposes an adaptive adjustment method for the alarm threshold. This method uses the CUSUM algorithm to monitor the change trend of the operating parameters of the distribution network in real time and automatically adjusts the alarm threshold based on the historical data and actual operating conditions. The simulation results show that the intelligent monitoring system and the adaptive adjustment method of the alarm threshold for the distribution network can effectively improve the accuracy and timeliness of distribution network monitoring, and provide strong support for the safe and stable operation of the distribution network.
Keywords
distribution network, intelligent monitoring system, CUSUM algorithm, alarm threshold adjustment, fault diagnosis
Full Text
The safe and reliable operation of the distribution network is particularly important. In order to monitor the operation status of the distribution network more accurately, find hidden dangers in time, and improve the intelligent operation level of the distribution network, this paper designs a set of intelligent monitoring system for the distribution network. The system builds a basic data layer, a historical data layer, a real‐time operation layer, and an application layer. The basic data layer stores various basic data of the distribution network such as equipment parameters and network structure; the historical data layer stores a large amount of historical operational data such as load, voltage, and current; the real‐time operation layer collects real‐time operational data of the distribution network through sensors and communication networks; the application layer provides various intelligent applications such as fault diagnosis, load forecasting, and alarm processing. In response to the problem that it is difficult for the traditional distribution network monitoring system to adjust the alarm threshold based on the actual operation situation, this paper proposes an adaptive adjustment method for the alarm threshold. This method uses the CUSUM algorithm to monitor the change trend of the operating parameters of the distribution network in real time and automatically adjusts the alarm threshold based on the historical data and actual operating conditions. The simulation results show that the intelligent monitoring system and the adaptive adjustment method of the alarm threshold for the distribution network can effectively improve the accuracy and timeliness of distribution network monitoring, and provide strong support for the safe and stable operation of the distribution network.