Abnormality monitoring system for applying big data to smart power grid

Abstract

The invention relates to an anomaly monitoring system for applying big data to a smart power grid. The anomaly monitoring system comprises a sensing node, a base station node, a control node and a management terminal, and the nodes are in communication connection; the control node is in communication connection with the management terminal; the base station node comprises a data analysis module and an anomaly detection module, and the data analysis module is in communication connection with the anomaly detection module; and the control node comprises a cross node module and a fault detection module, and the cross node module is in communication connection with the fault detection module. The sensing nodes collect power transmission line data of the power transmission line in real time. The base station node obtains a space-time state curve of the base station node according to the power transmission line data so as to perform anomaly identification on the power transmission line of the base station node. The control node performs cross verification on the abnormal base station node and the cross base station node according to the base station detection data and the cross detection data so as to perform abnormity monitoring judgment.

Description

technical field [0001] The invention relates to the fields of big data and smart grids, in particular to an abnormality monitoring system applying big data to smart grids. Background technique [0002] With the development of smart distribution network technology and the continuous advancement of power system automation construction, the structure and operation mode of the power network have become more and more complex. requirements. How to effectively monitor the abnormality of the power lines in the distribution network has become a new demand point and a hot research direction for the power production department. [0003] The line parameters of the distribution network are of great significance to the medium and long-term planning of the distribution network, the economic and stable operation of the distribution network, the topology of the distribution network, and fault judgment. Obviously wrong line parameters with small bad data will affect the dispatcher to make wr...

AI Technical Summary

Problems solved by technology

[0004] However, the existing distribution network power line safety monitoring technology only monitors the single-node fault status of the power line, and cannot perform cross-validation based on multi-node data. The detection accuracy is low

At the same time, the existing technology mainly finds the fault point of the power line in the distribution network manually, which leads to a decrease in the troubleshooting efficiency of the distribution network, which affects the safe power supply guarantee of the distribution network and increases the power outage in the area covered by the distribution network. Time, and thus unable to meet people's electricity demand

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