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Natural gas load fluctuation asymmetry analysis method and system based on TARCH model

An asymmetric and analytical technology, applied in the field of data analysis, can solve the problems of lack of natural gas load analysis, inaccurate natural gas load forecast, etc., to avoid pseudo-regression phenomenon and improve forecast accuracy.

Pending Publication Date: 2022-06-28
XI'AN UNIVERSITY OF ARCHITECTURE AND TECHNOLOGY
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Problems solved by technology

[0003] The existing natural gas load prediction methods often lack the analysis of natural gas load characteristics, resulting in inaccurate natural gas load forecasting. However, natural gas load has significant nonlinear characteristics such as periodicity, uncertainty, and volatility. Therefore, it is necessary to analyze the characteristics and laws of natural gas load to provide accurate reference data for the prediction of natural gas load.

Method used

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  • Natural gas load fluctuation asymmetry analysis method and system based on TARCH model
  • Natural gas load fluctuation asymmetry analysis method and system based on TARCH model
  • Natural gas load fluctuation asymmetry analysis method and system based on TARCH model

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Effect test

Embodiment 1

[0070] A TARCH model-based asymmetric analysis method for natural gas load fluctuations, including the following steps:

[0071] 1) Use the K-means algorithm to detect and eliminate outliers in the acquired natural gas load data set, and use the mean interpolation method to fill in the missing values ​​in the natural gas load data set.

[0072] 2) According to the size of the natural gas load data set, the data set is segmented according to the division method of every other year, and multiple natural gas data subsets are obtained to form a comparative analysis on the time span;

[0073] 3) Use the ADF unit root test method to test whether the natural gas load sequence is stable, so as to avoid false regression in the regression process.

[0074] The verification results are shown in Table 1:

[0075] Table 1 ADF unit root verification results

[0076]

[0077] The P values ​​were all less than 0.01, indicating that the null hypothesis was rejected at the 1% check level, ...

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Abstract

The invention discloses a natural gas consumption load fluctuation asymmetry analysis method and system based on a TARCH model, and the method comprises the steps: carrying out the preprocessing of an obtained natural gas data set, and dividing the natural gas data set according to years, so as to form the comparative analysis of a time span; checking whether the natural gas load sequence is stable or not by using an ADF unit root checking method so as to avoid a pseudo-regression phenomenon in a regression process; the method comprises the following steps of: verifying a natural gas consumption load data set, performing ARCH effect verification on the verified data set, judging whether the data set has the ARCH effect, finally performing fluctuation asymmetry analysis based on a TARCH model on the data set judged through the ARCH effect, and performing fluctuation asymmetry analysis on the natural gas consumption load data set by using the TARCH model to obtain a final analysis result. Natural gas negative pressure prediction is carried out according to the analysis result, and prediction accuracy can be improved.

Description

technical field [0001] The invention belongs to the field of data analysis, and in particular relates to a TARCH model-based asymmetric analysis method and system for natural gas load fluctuations. Background technique [0002] As a clean and efficient energy, natural gas can effectively make up for the shortcomings of wind and solar energy that are not easy to store and supply is unstable. The general trend of natural gas replacing high-carbon and high-polluting coal is irreversible. Therefore, the development of natural gas will definitely drive the rapid development of urban natural gas. . Followed by a series of problems such as: urban gas source replacement, urban gas pipeline network planning, construction of gas storage facilities and so on. In view of these problems, the research work of gas load forecasting method is particularly important. [0003] The existing natural gas load prediction methods often lack the analysis of the characteristics of the natural gas l...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06F17/18G06K9/62G06Q50/06
CPCG06Q10/0639G06F17/18G06Q50/06G06F18/23213
Inventor 边根庆孙世冲
Owner XI'AN UNIVERSITY OF ARCHITECTURE AND TECHNOLOGY
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