Construction method for communication traffic threshold model of intelligent substation based on FARIMA

A smart substation, communication flow technology, applied in the direction of electrical components, digital transmission systems, transmission systems, etc.

Active Publication Date: 2018-01-05
ZHEJIANG UNIV
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Problems solved by technology

[0005] The purpose of the present invention is to solve the problem of modeling and prediction of intelligent substation communication traffic with sudden and long-term correlation, and propose a perfect analysis method for the existing re...

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  • Construction method for communication traffic threshold model of intelligent substation based on FARIMA
  • Construction method for communication traffic threshold model of intelligent substation based on FARIMA
  • Construction method for communication traffic threshold model of intelligent substation based on FARIMA

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Embodiment Construction

[0073] The purpose and effects of the present invention will become more apparent by referring to the accompanying drawings in detail of the present invention.

[0074] By collecting the actual data flow of a 110kV substation in Tianjin, a flow model with appropriate parameters is established. In the actual substation, a total of 56 IEDs and 3 monitoring machines are connected to the double-ring network structure through LAN (Local Area Network). The sampling point is obtained by the probe mechanism by collecting the port data of the SCADA servo server (IBMX3650). Measured aggregated traffic at the station control level of the smart substation; these traffics enable remote control and advanced management services. The original statistical time step of the probe measurement data stream is 1ms, which means that the data is refreshed and stored every millisecond. 8.64×107 pieces of data were recorded in the entire SCN operation cycle (that is, 24 hours); by analyzing the charac...

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Abstract

The invention discloses a construction method for a communication traffic threshold model of an intelligent substation based on FARIMA. The method comprises the following steps: analyzing the stability and autocorrelation of a traffic sequence; designing an FIR filter according to Hurst parameters of the sequence, and filtering data; performing order determination for an ARMA (p, q) model by usingAIC information criteria, and then performing residual test for a predicted value of an FARIMA (p, d, q) model; and simulating the FARIMA model for multiple times, performing short-term prediction, and designing an algorithm to generate traffic threshold models with different confidence levels. According to the construction method disclosed by the invention, a detailed algorithm description is provided by taking the traffic actually acquired by a station control layer of a certain substation in Tianjin as test data, and the communication traffic threshold model of the station control layer ofthe intelligent substation is also obtained through a series of experiments.

Description

technical field [0001] The invention relates to power communication network flow prediction, in particular to a method for constructing a communication flow threshold model of an intelligent substation based on FARIMA. Background technique [0002] With the construction of national intelligent substations and the advancement of power transmission and distribution automation transformation, the issue of power grid industrial control information security has become increasingly prominent. How to grasp the behavioral nature, protocol characteristics and traffic anomalies of the power information network has undoubtedly become a key issue in the research of power communication in my country. At present, China is making every effort to build an intelligent communication network. The access of a large number of secondary equipment and the update requirements of real-time data have caused a large increase and complex changes in the power communication network traffic. How to plan ...

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Application Information

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IPC IPC(8): H04L12/24H04L12/801
Inventor 杨强郝唯杰
Owner ZHEJIANG UNIV
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