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

Intelligent building microgrid power utilization behavior identification method

A recognition method and building technology, applied in the direction of character and pattern recognition, data processing applications, complex mathematical operations, etc., can solve the problem of calculating the probability of user electricity consumption behavior, the inability to achieve high-precision identification and classification, and the lack of accuracy of user electricity consumption behavior and other issues to achieve the effect of improving accuracy, improving accuracy and rapidity

Active Publication Date: 2017-10-03
XIANGTAN UNIV
View PDF5 Cites 31 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, some researchers decompose the user's electricity load into basic load and seasonal load, and use the adaptive fuzzy C-means clustering algorithm to cluster the user's basic load and seasonal load. However, in practical applications, some users The total load of electricity consumption is the same, but the basic load and the equipment used are also different, and the user's electricity consumption behavior cannot be identified and classified with high precision; in addition, other scholars use the entropy weight method to calculate the entropy and weight of the user's electricity consumption characteristic information, and then in Cluster analysis is performed on users by clustering algorithm, but this method cannot calculate the probability of users' electricity consumption behavior as a whole, and there is a deficiency in judging the accuracy of users' electricity consumption behavior

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
  • Intelligent building microgrid power utilization behavior identification method
  • Intelligent building microgrid power utilization behavior identification method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0038] The present invention will be further described below in conjunction with the drawings and specific implementation process.

[0039] Such as figure 1 As shown, the big data of electricity consumption is obtained through the monitoring of the intelligent building micro-grid electricity data collection terminal and environmental sensors; then the obtained data is preprocessed (data integration, data filling, feature normalization); the preprocessing is performed by using the kernel principal component analysis The final data sample extracts the load characteristic parameters of each electrical equipment. Different electrical equipment uses different power, voltage, current, etc. and shows different characteristics, and then it can be distinguished from the extracted electricity data characteristics. equipment; then use the multi-variable multi-scale sample entropy weight method to determine the environmental factors of the user's electricity consumption behavior characte...

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 an intelligent building microgrid power utilization behavior identification method. The intelligent building microgrid power utilization behavior identification method is characterized in that power utilization big data is obtained through an intelligent building microgrid power utilization data acquisition terminal and monitoring of each environment sensor; then the obtained data is subjected to pretreatments (data integration, data filling and feature normalization); the load feature parameter of each powered device is extracted from a pretreated data sample by means of a kernel principal component analysis method; the environment factor of each power utilization behavior feature of the user and the contribution rates of different powered devices, i.e., the feature weight of each influence factor of fuzzy C-mean value clustering are determined by means of a multi-variable multi-scale sample entropy weight method; finally the obtained feature data set is subjected to cluster analysis through the fuzzy C-mean value clustering method and the user power utilization behavior identification accuracy and rapidity can be improved. According to the invention, the building microgrid user power utilization behavior can be effectively identified, and a basis and reference can be provided for scheduling of the building microgrid power utilization load by the power grid, and furthermore the fact that the user saves power in life, and power wasting behaviors are reduced is promoted.

Description

technical field [0001] The invention belongs to the technical field of power consumption of smart building microgrids, and relates to a method for identifying power consumption behaviors of smart building microgrids. Background technique [0002] With the continuous construction and development of the smart grid, user electricity consumption data has gradually accumulated into big data. Although these large electricity consumption data seem to be very chaotic, they hide the user's electricity consumption behavior, and there are certain gaps between the data. connect. Mining scattered massive data and identifying the types of user electricity consumption behavior can help the power grid understand the user's personalized and differentiated service needs, and provide a basis and reference for the power grid to schedule the power load of the smart building microgrid, thereby improving residents' lives. Save electricity and reduce electricity consumption. [0003] At present, ...

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 Applications(China)
IPC IPC(8): G06F17/18G06K9/62G06Q50/06
CPCG06F17/18G06Q50/06G06F18/2321
Inventor 易灵芝张成董贾艳芳
Owner XIANGTAN 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