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Power consumer service demand prediction method based on big data analysis

A technology for power user and demand forecasting, applied in data processing applications, forecasting, instruments, etc., can solve the problems of low accuracy of forecast results and inability to predict big data, and achieve the effect of refined management and accurate forecasting.

Pending Publication Date: 2022-03-25
GUIZHOU POWER GRID CO LTD
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Most of the existing technologies solve the problem of demand forecasting by combining artificial intelligence to establish a demand forecasting model, but the factors considered by the existing power demand forecasting model are too subjective, resulting in low accuracy of forecasting results and the inability to predict big data

Method used

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  • Power consumer service demand prediction method based on big data analysis
  • Power consumer service demand prediction method based on big data analysis
  • Power consumer service demand prediction method based on big data analysis

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Experimental program
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Embodiment 1

[0028] refer to figure 1 , which is the first embodiment of the present invention, this embodiment provides a method for forecasting power user service demand based on big data analysis, including:

[0029] S1: Collect power user data and preprocess the power user data.

[0030] Electricity user data includes user personal information and enterprise information;

[0031] Among them, user personal information includes gender, age, place of residence, income, expenditure, provident fund and social security information; enterprise information includes enterprise name, type, registered capital and legal person information.

[0032] Further, preprocess the power user data:

[0033] (1) Using the K-nearest neighbor algorithm, select the R sample instances closest to the data with missing information as a class, remove the data with missing information, and count the number of occurrences of each sample;

[0034] (2) The one with the highest frequency of occurrence is used as the ...

Embodiment 2

[0063] In order to verify and explain the technical effect adopted in this method, this embodiment chooses the traditional technical scheme and adopts this method to conduct a comparative test, and compares the test results by means of scientific demonstration to verify the real effect of this method.

[0064] In order to verify that this method has a higher prediction accuracy than the traditional technical solution, in this embodiment, the traditional technical solution and this method will be used to predict the electricity consumption data (5 categories) in a certain area, and the prediction results are shown in Table 1 shown.

[0065] Table 1: Comparison of power forecasting results.

[0066]

[0067] It can be seen from the above table that, compared with the traditional technical solution, this method can accurately predict the power consumption.

[0068] It should be appreciated that embodiments of the invention may be realized or implemented by computer hardware, ...

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Abstract

The invention discloses a power consumer service demand prediction method based on big data analysis, and the method comprises the steps: collecting power consumer data, and carrying out the preprocessing of the power consumer data; analyzing the preprocessed data by using a wavelet transform clustering algorithm so as to divide power consumer categories; establishing a power demand prediction model in combination with the power consumer category and the historical power consumption data; predicting the service demand of the power consumer through the power demand prediction model, and visualizing the prediction result; according to the method, the clustering algorithm and the neural network are combined, mass data can be processed, accurate prediction of power consumer service requirements is achieved, meanwhile, the prediction result is visualized, and fine management of power consumers is achieved.

Description

technical field [0001] The invention relates to the technical field of power user service demand forecasting, in particular to a power user service demand forecasting method based on big data analysis. Background technique [0002] With the continuous improvement of the level of science and technology, people are increasingly inseparable from electricity. The automation development of many industries also relies on electric energy. The electricity consumption in various regions is increasing, and people's demand for electricity is also growing. As the external service window of power grid enterprises, the power grid customer service center needs to integrate various internal and external data resources, store and analyze massive customer service information. How to efficiently, reliably, and inexpensively store all kinds of data of power grid enterprises, and quickly analyze and predict them is an important research topic at present. [0003] Most of the existing technologi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06K9/62G06N3/04
CPCG06Q10/04G06Q50/06G06N3/047G06N3/045G06F18/23G06F18/24147
Inventor 范俊秋袁龙谢威邵倩文廖畅王聃宋达杨鹏王军谢才科杨瑞张华杜刃刃王师国
Owner GUIZHOU POWER GRID CO LTD
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