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Smart grid big data-based electricity price execution checking method

A smart grid and big data technology, applied in data processing applications, instruments, resources, etc., to achieve the effects of high inspection accuracy, high stability, and simple and clear principles

Inactive Publication Date: 2016-05-11
GUANGDONG UNIV OF TECH
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Problems solved by technology

However, the research on implementing online inspection of electricity price execution by using data mining technology and intelligent algorithm is still blank.

Method used

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  • Smart grid big data-based electricity price execution checking method
  • Smart grid big data-based electricity price execution checking method
  • Smart grid big data-based electricity price execution checking method

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Embodiment Construction

[0063] Such as figure 2 Shown is a flow chart of the application of the MDKC operator in a power grid based on the smart grid big data electricity price execution inspection method of the present invention, including the following steps:

[0064] Step 1, combined with the characteristics of the data set, initialize the maximum number of clusters kmax = 15, the maximum and minimum density parameter adjustment coefficient α max = 0.8, α min =0.5, convergence criterion ξ=0.0001, initial iteration flag Iter=1;

[0065] Step 2, determine the initial cluster center according to the density parameter value, the specific steps are as follows:

[0066] ⑴ According to the formula

[0067] Density (P i ,ε)=|Neighbor(P i ,ε)|, where, P i is the sample point, i∈[1,n], ε is the radius;

[0068] Find the density parameter values ​​of all points, form the density parameter set Den and sort by descending power, use the high density threshold D_th, take out some of the high density para...

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Abstract

The invention discloses a smart grid big data-based electricity price execution checking method. The method comprises the following steps: 1) processing the power consumer power consumption data by utilizing a data pre-processing module; 2) constructing a power consumer typical power consumption track expert library by utilizing a clustering algorithm; and 3) realizing the electricity process execution checking of the power consumers by utilizing a distance discriminant analysis algorithm. According to the clustering algorithm, an initial clustering center can be determined through the density parameters of sample points; by utilizing a method of combining the cluster evaluation index and the score evaluation index, the optimum number of clusters can be determined, so that a power consumer typical power consumption track curve is formed; according to the distance discriminant analysis algorithm, electricity price execution checking discrimination is carried out on new power consumers, and through calculating the electricity price abnormal suspected coefficient, a list of the final the electricity price execution abnormal consumers is determined. According to the method, the intelligent analysis and identification of the power consumption behavior tracks can be realized, the remote online diagnosis of the consumer electricity price execution can be realized, and the pertinence, correctness and timeliness of the marketing checking can be improved.

Description

technical field [0001] The present invention relates to an electricity price execution inspection method based on smart grid big data, in particular to an electricity price based on a density-based improved k-means clustering (ModifiedDensityK-meansClustering, MDKC) and Fréchet Distance Discriminant Analysis (FDDA) algorithm The execution inspection method belongs to the innovative technology of the electricity price execution inspection method. Background technique [0002] Electricity fee income is the most important source of operating income for power supply companies, and the recovery of electricity fees on schedule and in volume is one of the important economic indicators for power supply companies. With the development of smart grid big data, the data generated in the power distribution link is large, multi-dimensional, complex processing logic, long storage period, high calculation frequency and other big data characteristics. analysis needs. [0003] The current e...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q50/06
CPCG06Q10/063G06Q50/06
Inventor 彭显刚郑伟钦林利祥刘艺
Owner GUANGDONG UNIV OF TECH
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