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Substation Auxiliary Monitoring Based On Internet Of Things Technology

Posted on:2016-02-03Degree:MasterType:Thesis
Country:ChinaCandidate:L J KangFull Text:PDF
GTID:2322330485955256Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
Substation equipment operation monitoring as an important part of intelligent substation management has been more and more extensive attention in the electric power industry at home and abroad. The degree of degradation and technology condition can be timely grasped to prevent and control gradually developed faults and sudden accident by the effective equipment running status monitoring.Based on the analysis of the Internet of things technology, the substation equipment operation monitoring system of the Internet of things in the perception layer, network layer, and application layer is discussed. On the comparison to the characteristics of several kinds of wireless communication technology, the advantages of ZigBee technology in substation equipment operation data acquisition is illuminated, and the corresponding building networked sensing layer is built. The sensor node, the coordinator node, intelligent access gateway, SDH optical transceiver, information exchange and communication network transmission equipment are discussed, and a complete communication network is established. Based on the actual observation records of hot point temperature in substation equipment, observation records used by chaotic time series theory are cleared up, the chaotic characteristics of device hot spot temperature time series data is proved, and equipment temperature is forecasted and analyzed by using the RBF network.Using Internet technology to monitor hot point temperature of transformer substation equipment, not only can improve the power grid operation efficiency, and improve the efficiency of the control personnel, but also have played an important role to ensure the safe operation of the actual grid.
Keywords/Search Tags:Substation equipment monitoring, Internet of Things technology, ZigBee technology, Chaotic time series, RBF neural network, Temperature forecasting
PDF Full Text Request
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