Typical load curve identification method based on normal cloud model and density clustering algorithm

A density clustering algorithm and load curve technology, applied in character and pattern recognition, calculation, complex mathematical operations, etc., can solve the problems of inaccurate cluster division and inaccurate calculation of curve similarity. The effect of avoiding clustering errors

Pending Publication Date: 2022-07-08
ZHEJIANG UNIV
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Problems solved by technology

[0003] The method problem mainly solved by the present invention is to overcome the problems of inaccurate calculation of curve similarity and inaccurate division of cluster clusters by the existing typical load curve extraction method, and provide a typical load curve based on normal cloud model and density clustering algorithm The identification method accurately represents and calculates the feature similarity between different curves, and accurately determines the center of each cluster through the density peak fast clustering algorithm

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  • Typical load curve identification method based on normal cloud model and density clustering algorithm
  • Typical load curve identification method based on normal cloud model and density clustering algorithm
  • Typical load curve identification method based on normal cloud model and density clustering algorithm

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[0058] The solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, but not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0059] Please see attached figure 1 , with figure 1 It is a calculation flow chart of a typical load curve identification method based on a normal cloud model and a density clustering algorithm of the present invention, and the method includes the following steps:

[0060] Step 1. Determine the research industry for the identification of typical load curves, collect metering load data of users in the industry and preprocess the collected data;

[0061] Step 2. Use the segmented cloud approximation algorithm to ...

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Abstract

The invention discloses a typical load curve identification method based on a normal cloud model and a density clustering algorithm. The method comprises the following steps: firstly, considering the electricity consumption uncertainty of different moments or users, and establishing a segmented feature model of a load curve by adopting a segmented cloud approximation algorithm; secondly, mining local dynamic features of the curves based on feature similarity between approximate area measurement curves among clouds; thirdly, clustering the load curve by adopting a density peak value fast clustering algorithm, and determining a clustering center of each cluster and a curve sample of each cluster; and finally, extracting a typical load curve from each cluster. According to the method, the feature similarity between different curves can be accurately represented, the electricity consumption types of the industry are finally divided by reasonably selecting the clustering center and the abnormal curve, and the typical load curve of the industry user is identified.

Description

technical field [0001] The invention belongs to the research field of power consumption pattern recognition, and particularly relates to a typical load curve identification method based on a normal cloud model and a density clustering algorithm. Background technique [0002] At present, mining the typical electricity consumption patterns of industries and users based on the massive historical electricity consumption data collected and stored in smart meters and electricity consumption information collection systems is an important guarantee for the planning and operation of power systems and refined management of distribution networks. Among them, the identification of typical daily load curves of industries and users is an important means of mining electricity consumption patterns, which can not only improve the accuracy of load forecasting, but also provide strong support for user-side demand response, electricity price design and load management. Therefore, how to mine an...

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Application Information

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Patent Type & AuthorityApplications(China)
IPC IPC(8): G06F16/2458G06F17/18G06K9/62G06Q50/06
CPCG06F16/2465G06F16/2462G06F17/18G06Q50/06G06F18/2321Y04S10/50
Inventor卢峰崔雪原王韵楚刘晟源林振智杨莉马愿谦章天晗陈昌铭张智邱伟强
OwnerZHEJIANG UNIV