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User load classification method based on optimal clustering number and apparatus thereof

A load classification and clustering technology, applied in the field of smart grid, can solve the problems of low precision and complex calculation of high-dimensional data processing

Inactive Publication Date: 2016-06-22
STATE GRID CORP OF CHINA +3
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Problems solved by technology

Existing methods are more complicated to calculate, and there is a problem of low processing accuracy for high-dimensional data

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  • User load classification method based on optimal clustering number and apparatus thereof
  • User load classification method based on optimal clustering number and apparatus thereof
  • User load classification method based on optimal clustering number and apparatus thereof

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Embodiment Construction

[0040] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0041] An embodiment of the present invention provides a flow chart of a user load classification method based on an optimal cluster number in an embodiment of the present invention. refer to figure 1 , is a flowchart of a user load classification method based on the optimal number of clusters according to an embodiment of the present invention.

[0042] The user load classification method based on the optimal number of clusters comprises the following steps:

[0043] Step 101. Obtain time series curve data of user load and perform normalization processing.

[0044] In this step, the data set to be clustered is obtained by collecting a large number of residential users by the electricity collection system. Due to the li...

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Abstract

The invention discloses a user load classification method based on an optimal clustering number and an apparatus thereof. The method comprises the following steps of acquiring time sequence curve data of a user load and carrying out normalization processing; extracting a user electricity usage behavior characteristic; using an Renyi entropy gradient descent method to carry out optimal clustering number training; and using the optimal clustering number to carry out hierarchical clustering. In the invention, a similarity and relevance among different users are comprehensively considered; a problem that precision of a traditional Euclidean distance similarity during high dimension data processing is not high is overcome; the different clustering numbers of Renyi entropy values are calculated so that the optimal clustering number can be found; a disadvantage that the clustering number needs to be set in advance in a traditional algorithm is overcome; operation efficiency is increased and operation cost is reduced.

Description

technical field [0001] The invention relates to the technical field of smart grids, in particular to a user load classification method and device based on the optimal number of clusters. Background technique [0002] Today, as the electricity market is increasingly open, the importance of user load classification is becoming more and more significant. With the rapid development of my country's economy and the improvement of people's living standards, the electricity consumption of residents shows a growth trend, and the demand for electricity tends to be diversified. With the society's increasing requirements for environmental protection, energy conservation and emission reduction, and sustainable development, the future power grid must be able to provide safer, more reliable, clean, and high-quality power supply and provide better services. [0003] With the construction of a unified and strong smart grid featuring informatization, digitization, automation, and interaction...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q50/06G06K9/62
CPCG06Q50/06G06F18/23
Inventor 刘庆时赵贺姚国风唐新忠李天杰郑凤柱赵大明周建华贾孟扬
Owner STATE GRID CORP OF CHINA
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