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A traffic forecasting method for power integrated service network

A technology of integrated business and forecasting method, which is applied in the field of traffic forecasting of the integrated power business network, and can solve problems such as large forecast errors and hysteresis at turning points

Inactive Publication Date: 2018-08-10
STATE GRID CORP OF CHINA +3
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Problems solved by technology

This makes the obtained prediction model have a significant hysteresis phenomenon compared with the actual data flow curve when the prediction model encounters a turning point, so there is a large prediction error at the turning point.

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  • A traffic forecasting method for power integrated service network
  • A traffic forecasting method for power integrated service network
  • A traffic forecasting method for power integrated service network

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Embodiment Construction

[0055] The present application discloses a traffic forecasting method of an integrated electric power service network. Due to the obvious daily periodicity of the data flow curve of the integrated power service network, such as figure 1As shown, the present invention extracts the historical data into horizontal and vertical dimensions by making full use of the historical data. Since the horizontal data sequence has an obvious periodic trend, the present invention uses a neural network algorithm to predict the horizontal data. For the longitudinal data sequence, the trend is not obvious, mainly random fluctuations, so the present invention uses a linear prediction algorithm to predict the longitudinal data. A neural network prediction model, called lateral prediction, is built with lateral flow sequence training. A linear forecasting model, called longitudinal forecasting, is built with longitudinal flow series. Horizontal forecasting better captures the trend of data traffi...

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Abstract

The invention provides a power integrated service network flow prediction method. The power integrated service network flow prediction method comprises the steps of: step 1, extracting transverse flow data series and longitudinal flow data series from a power integrated service network flow database; step 2, establishing a two-dimensional prediction model; step 3, reading new data at a moment t, wherein the t is a current sampling moment; step 4, utilizing the two-dimensional prediction model for predicting flow data at a moment t+T, and outputting the prediction result, wherein the T is a sampling period; and step 5, waiting until a next sampling moment and returning to the step 3.

Description

technical field [0001] The present application relates to the technical field of smart grids, in particular to a traffic forecasting method for an integrated electric power service network. Background technique [0002] With the continuous deepening of smart grid construction, such as unattended substations, expansion of business halls, online office business, etc., the data flow of the integrated power business network has been greatly increased. Precisely predicting the data flow in the power integrated service network to realize traffic early warning has important theoretical guiding significance for the operation and maintenance of the integrated service network and the expansion of communication resources. [0003] The existing data flow forecasting algorithms of the integrated power service network can be divided into two categories. The first type of prediction algorithm is directly used in the data flow prediction of the power integrated service network after select...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L12/24
Inventor 冯伟东孙勇罗欢张天魁
Owner STATE GRID CORP OF CHINA
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