Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A two-layer spectral clustering method for power load curves considering wavelet entropy dimensionality reduction

A power load and spectral clustering algorithm technology, applied in computing, computer components, instruments, etc., can solve problems such as excessive data dimension and the inability of algorithms to adapt to different demand responses, so as to improve operating speed, improve stability, reduce The effect of data volume

Active Publication Date: 2021-11-23
SHANDONG UNIV
View PDF0 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In order to solve the deficiencies of the prior art, the present invention provides a two-layer spectrum clustering method for power load curves that takes into account wavelet entropy dimensionality reduction. The present invention overcomes the problems that existing algorithms cannot adapt to the requirements of different demand responses and the data dimension is too high. Realize effective clustering of demand response-oriented user load data, with fast calculation speed, high clustering effectiveness and good algorithm stability

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A two-layer spectral clustering method for power load curves considering wavelet entropy dimensionality reduction
  • A two-layer spectral clustering method for power load curves considering wavelet entropy dimensionality reduction
  • A two-layer spectral clustering method for power load curves considering wavelet entropy dimensionality reduction

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0039] It should be pointed out that the following detailed description is exemplary and intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0040] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinations thereof.

[0041] Among the specific implementation examples disclosed by the present invention, a double-layer spectrum cl...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a double-layer spectrum clustering method for electric load curves considering wavelet entropy dimensionality reduction, comprising: obtaining daily load data of electric loads and forming a data set; segmenting the electric load data in the data set into q intervals And calculate the wavelet entropy S of the original data set in the interval q q , according to the calculated wavelet entropy value and the threshold value of wavelet entropy to measure the degree of fluctuation of the data, the degree of fluctuation is greater than the specified threshold; on the contrary, the degree of fluctuation is relatively small; the number of loads whose wavelet entropy value is greater than the threshold value of wavelet entropy in the statistical interval q And calculate the proportion of the load data in the total load of the electric load; divide the interval with a proportion greater than the threshold into two sections, calculate the wavelet entropy value in the interval again and compare the fluctuation degree of the measurement data until the load with a large fluctuation degree in the interval accounts for The proportion of all loads is less than the threshold or the number of points in the interval cannot be equally divided, and the load curve data with variable time resolution is obtained; the double-layer spectral clustering obtains similar and refined load clusters.

Description

technical field [0001] The invention relates to the technical field of power systems, in particular to a double-layer spectrum clustering method for power load curves considering wavelet entropy dimension reduction. Background technique [0002] The construction of the Energy Internet has promoted the development of big data on power distribution and consumption. The continuous accumulation of these energy-consuming data has brought certain difficulties to the implementation of demand response. The massive data of the power grid makes simple statistical analysis of load characteristics meaningless. , it is more unrealistic to adopt different control strategies for each load. It is necessary to classify the loads participating in demand response. The traditional classification method is to divide according to typical industries. However, the load curves of power users in the same industry may vary greatly , the load curves of power loads in different industries may also be ve...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62
CPCG06F18/22G06F18/23213
Inventor 王振树吴晨
Owner SHANDONG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com