Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Power load data dimension reduction reconstruction processing method based on VMD and OMP

A power load and data dimension reduction technology, applied in data processing applications, instruments, calculations, etc., can solve the problems of poor reconstruction accuracy, long time consumption, and low complexity

Pending Publication Date: 2020-11-10
SHENYANG POLYTECHNIC UNIV +1
View PDF0 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This type of algorithm has low complexity and simple algorithm operation, but its reconstruction accuracy is not as good as that of convex optimization algorithms.
The traditional greedy iterative algorithm of the essence of the MP algorithm, as the number of iterations increases, the time complexity of the MP algorithm increases, and the time it takes is longer

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
  • Power load data dimension reduction reconstruction processing method based on VMD and OMP
  • Power load data dimension reduction reconstruction processing method based on VMD and OMP
  • Power load data dimension reduction reconstruction processing method based on VMD and OMP

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0094] Such as figure 1 As shown, the operation method based on VMD and OMP power load data dimensionality reduction algorithm is characterized in that: the method includes:

[0095] Step 1, collecting power load data;

[0096] Step 2. Perform data decomposition filtering and dimension reduction processing on the collected power load data through the variational mode decomposition method;

[0097] Step 3. After obtaining the natural mode components with frequencies ranging from low to high, the orthogonal matching tracking algorithm is used to reconstruct and optimize the decomposed and filtered data.

[0098] After the power load data to be tested is processed through the above three steps, complex, massive and high-dimensional data can be processed into simple, low-dimensional and easy-to-handle and analyze data; finally, in-depth research on the processed data, for Users, power companies and the government provide the basis for easy analysis of electricity consumption beh...

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 relates to power load data processing, in particular to a power load data dimension reduction reconstruction processing method based on VMD and OMP. The method comprises the following steps: acquiring power load data; carrying out data decomposition filtering and dimension reduction processing on the acquired power load data through a variational mode decomposition method; and then,after obtaining intrinsic mode components of which the frequencies are from low to high, performing reconstruction optimization processing on the decomposed and filtered data by using an orthogonal matching tracking algorithm. According to the method, a VMD operation method and an OMP operation method are combined for the first time, the dimension reduction reconstruction processing method which is high in operation efficiency and universality is obtained, and the method is suitable for a data set of an existing dimension, not prone to being affected by noise, high in stability and more suitable for power load big data processing derived in the increasingly flourishing development information age.

Description

technical field [0001] The invention relates to the processing of electric load data, in particular to a dimension reduction and reconstruction processing method of electric load data based on VMD and OMP. Background technique [0002] In the era of big data, data is widely used in power automation systems. The power operation monitoring system in the era of big data realizes the integration of information technology, power grid production and enterprise management, and improves the timeliness of power grid business data. At the same time, the planning and operation of smart grids require a good data foundation, so the extraction and dimensionality reduction of big data loads based on demand-side response needs to be studied urgently. The demand-side big data includes high-dimensional and massive user daily / monthly load curves. Accurate analysis and research on these power consumption information data and obtaining corresponding load patterns can provide an important basis f...

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
IPC IPC(8): G06Q50/06
CPCG06Q50/06
Inventor 崔嘉董金武杨俊友雷振江田小蕾杨超李伟王丽霞李桐
Owner SHENYANG POLYTECHNIC UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
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