Bad data detection method for smart grid based on adaptive partition state estimation

Abstract

The invention discloses a bad data detection method of a smart power grid based on self-adaptive partition state estimation. The bad data detection method comprises the following steps of: generating a corresponding graph model according to known physical structure parameters of the smart power grid; dividing the graph model into a plurality of sub-graphs by using a clustering algorithm, wherein each sub-graph corresponds to a subsystem in the smart power grid; carrying out bad data detection on each subsystem, and updating the graph model according to detection results; and executing new partitioning and detecting, so as to position bad data within a smaller section. The bad data detection method provided by the invention can be used for detecting bad data injection attacks aiming at the design of the smart power grid; with the adoption of a partitioning technology, the detection precision of the bad data is improved, and the time complexity in the detection can be reduced; and meanwhile, through a multi-partitioning strategy, the bad data is positioned within the smaller range in an effective time period.

Description

Technical field: [0001] The invention relates to the field of smart grid data security, in particular to a detection and positioning method for bad data injection in the smart grid. Background technique: [0002] Smart grid uses information network technology to monitor and optimize the power generation, power distribution and power consumption equipment in the power network in real time, so as to achieve energy saving, emission reduction and other goals. The control center estimates the current operating status of the power grid by collecting the meter measurement data of terminals and transmission lines, and makes corresponding scheduling decisions. How to ensure timely discovery of errors in the measured values ​​of smart meters and prevent malicious data injection by hackers is the basis for the stable operation of smart grids. At present, relatively mature bad data detection data technology has been provided in the power system, but for the special nature of the smart ...

AI Technical Summary

Problems solved by technology

[0004] (2) The number of smart grid communication nodes is huge and the working environment is complex. Traditional bad data detection technology consumes a lot of computing time for large-scale network detection, which puts forward higher requirements on the computing power and storage space of the upper-level control center.

[0005] In the existing research, some solutions have been proposed theoretically for the DC transmission model of the smart grid. However, for the complex AC transmission problems in practice, there is no effective method that can essentially solve the above problems.

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