Power system abnormal data identifying and correcting method based on time series analysis

A time series analysis and abnormal data technology, applied in data processing applications, instruments, calculations, etc., can solve data errors and other problems, achieve the effect of improving accuracy and promoting safe and high-quality operation

Inactive Publication Date: 2015-07-08
SOUTHEAST UNIV +3
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Problems solved by technology

During the operation of the power system, due to channel errors, remote terminal unit failures,

Method used

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  • Power system abnormal data identifying and correcting method based on time series analysis
  • Power system abnormal data identifying and correcting method based on time series analysis
  • Power system abnormal data identifying and correcting method based on time series analysis

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Embodiment Construction

[0011] The present invention will be further described below in conjunction with the accompanying drawings.

[0012] Such as figure 1 Shown, method of the present invention specifically comprises the following steps:

[0013] 1) Preprocess the data to be detected, identify the missing data and the data that have mutated to zero in the data to be detected, and use the Lagrange interpolation method to fill in the identified missing and mutated to zero data and fixes.

[0014] The method of Lagrange interpolation is to give n interpolation nodes x 1 ,x 2 ,...x n , and the corresponding function value y 1 ,y 2 ,...y n , using the n-degree Lagrange interpolation polynomial, the function value y of any x in the interpolation interval can be solved by Ln(x), and the expression of Ln(x) is:

[0015] Ln ( x ) = Σ i = 0 n ...

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Abstract

The invention discloses a power system abnormal data identifying and correcting method based on time series analysis. The power system abnormal data identifying and correcting method includes data preprocessing, time series modeling, abnormal data identifying and abnormal data correcting. Data preprocessing includes the step of identifying and correcting missing data in data to be detected and data suddenly changing to be zero. Time series modeling comprises the steps of conducting time series analyzing on the preprocessed data to be detected and establishing a model according to the time series, and a difference autoregression moving average model is used for modeling the data to be detected. According to abnormal data identifying, the fitting residual series of the established difference autoregression moving average model is analyzed, an error confidence interval is set, and abnormal data are identified. According to abnormal data correcting, a neural network method is used for establishing a prediction model for correcting the abnormal data, the data value of the moment when the abnormal data exist is predicted, and the abnormal data are corrected. The power system abnormal data identifying and correcting method is easy to implement and high in accuracy.

Description

technical field [0001] The invention relates to the technical field of identification and correction of abnormal data in power systems, in particular to a method for identifying and correcting abnormal data based on time series analysis. Background technique [0002] With the rapid development of the social economy and the continuous improvement of the level of science and technology, the modern power system is developing faster and faster, and the society's requirements for the intelligence of the power grid are also increasing. Due to the continuous expansion of the grid scale and the increasingly complex structure and operation mode of the power system, a large amount of real-time data in the power system has an increasing impact on the security, stability and reliability of the system. [0003] The so-called abnormal data refers to the quantity measurement with a large measurement error in the actual power system operation. During the operation of the power system, due ...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q50/06
Inventor 蒋浩王珂苏大威徐春雷余璟杨志强袁丁
Owner SOUTHEAST UNIV
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