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Power grid resource deployment analysis method based on Bayesian back propagation

A technology of backpropagation and analysis method, which is applied in the field of grid resource deployment analysis based on Bayesian backpropagation, can solve the problems of frequent changes, difficulty in grid resource deployment planning, and high real-time response, so as to improve efficiency and real-time performance and eliminate the complicated effect of massive data

Pending Publication Date: 2021-09-17
GUANGZHOU POWER SUPPLY BUREAU GUANGDONG POWER GRID CO LTD
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] At present, the deployment and construction of high-performance platforms that meet the requirements of the Energy Internet need to face the problems of a huge number of management elements, frequent changes, many users, and high real-time response. Data and spatial data are index-managed power grid resource data) have the characteristics of multiple sources, huge data volume, and complex processing and analysis, which is extremely difficult for the current power grid resource deployment planning

Method used

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  • Power grid resource deployment analysis method based on Bayesian back propagation
  • Power grid resource deployment analysis method based on Bayesian back propagation
  • Power grid resource deployment analysis method based on Bayesian back propagation

Examples

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Embodiment 1

[0025] refer to figure 1 , which is the first embodiment of the present invention, provides a Bayesian backpropagation-based power grid resource deployment analysis method, specifically including:

[0026] S1 acquires grid resource data. What needs to be explained is:

[0027] Use the cloud database to retrieve the grid resource data stored in the Internet;

[0028] Clean, screen, filter and standardize the power grid resource data to form a data sample set;

[0029] The data sample set includes a test data set, a verification data set and a comparison data set.

[0030] S2 constructs a network label according to the location information corresponding to the power grid resource data. What needs to be explained in this step is:

[0031] Network labels include network codes, identification symbols and elevation codes;

[0032] The network code includes the grid code determined by the equipment location information of the power grid resource data;

[0033] Identification s...

Embodiment 2

[0045] refer to figure 2 , is the second embodiment of the present invention. This embodiment is different from the first embodiment in that it provides a verification process of a Bayesian backpropagation-based power grid resource deployment analysis method, which specifically includes:

[0046] In order to better verify and explain the technical effect adopted in the method of the present invention, in this embodiment, the traditional power grid resource analysis method is selected for comparative testing with the method of the present invention, and the test results are compared by means of scientific demonstration to verify the results of the method of the present invention. have real effects.

[0047] The traditional power grid resource analysis method cannot handle massive data information, and the analysis of huge amounts of information from unknown sources is complicated, with low efficiency and large errors. In order to verify that the method of the present invention...

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Abstract

The invention discloses a power grid resource deployment analysis method based on Bayesian back propagation; the method comprises the steps: obtaining power grid resource data; constructing a network label according to the position information corresponding to the power grid resource data; and importing the network tag into a simulation analysis platform to read key information, and outputting an analysis report. According to the method, the problems of complicated mass data, complicated analysis and untimely processing can be solved, and the efficiency and the real-time performance are greatly improved.

Description

technical field [0001] The invention relates to the technical field of grid resource analysis, in particular to a grid resource deployment analysis method based on Bayesian backpropagation. Background technique [0002] At present, the deployment and construction of a high-performance platform that meets the requirements of the Energy Internet needs to face the problems of a huge number of management elements, frequent changes, many users, and high real-time response. Data and spatial data are index-managed power grid resource data), which has the characteristics of multiple sources, huge data volume, and complex processing and analysis, which is extremely difficult for the current power grid resource deployment planning. Contents of the invention [0003] The purpose of this section is to outline some aspects of embodiments of the invention and briefly describe some preferred embodiments. Some simplifications or omissions may be made in this section, as well as in the ab...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/27G06N20/10G06F113/04
CPCG06F30/27G06N20/10G06F2113/04
Inventor 方健杨帆童锐郝方舟晏小卉张敏田妍
Owner GUANGZHOU POWER SUPPLY BUREAU GUANGDONG POWER GRID CO LTD
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