A self-diagnosis method for network sampling and control links of smart substations

Abstract

The present invention provides an intelligent substation network sampling and control link self-diagnosis method, comprising the following steps: IEC61850 communications protocol analysis; independent diagnosis and test of a control link, to find a network fault; SNMP-based network fault diagnosis; and network fault management. The present invention provides an intelligent substation network sampling and control link self-diagnosis method. The present invention can timely find various network faults during network operation, position and troubleshoot the faults, and further manage and record network fault information, thereby further ensuring application reliability and security of network sampling and network control in a substation, and improving intelligence of the substation.

Description

technical field [0001] The invention belongs to the technical field of electric power automation, and in particular relates to a self-diagnosis method for network sampling and control links of intelligent substations. Background technique [0002] The use of the IEC61850 standard promotes the development of process-level bus technology, and promotes the development of substation network communication from serial port connection and field bus to Ethernet transmission, which greatly improves the overall level of substation automation, because sampling and control information can be transmitted through the network. Effectively reducing complex cable connections in substations not only helps to simplify the structure of the whole substation, but also effectively reduces the construction cost of substations. More importantly, it can promote the development of advanced application functions of substations and further improve the overall level of substations. [0003] In May 2009, ...

AI Technical Summary

Problems solved by technology

[0004] The reliable operation of the substation network is the key to the application of network transmission in substations. Although the network sampling and network tripping technologies were piloted in the early digital substations, due to the lack of detection and fault diagnosis technologies for the operation status of the substation network, it is difficult for those who adopt the process layer network. The operation of substations has brought potential safety hazards. In order to further improve the operation and maintenance level of smart substations and improve the reliability of substation network operation, it is urgent to diagnose and monitor the operation status of multi-substation networks in real time, find faults, locate faults and eliminate faults in time.

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