Power load clustering analysis method based on correlation coefficient improved K-means
The invention discloses a power load clustering analysis method based on correlation coefficient improved K-means in the technical field of power load clustering analysis, and the method comprises thesteps: preprocessing load data through wavelet transformation under the condition that the power loa...
Gespeichert in:
Hauptverfasser: | , , , , , , , , , , , , , , , , , , , |
---|---|
Format: | Patent |
Sprache: | chi ; eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | |
container_start_page | |
container_title | |
container_volume | |
creator | LIU DINGHAO ZHOU JINGJING DAI HAORENG WANG SIWEI LI JIAO XIANG FEI ZHONG JIAYONG WU GAOXIANG LYU XIAOHONG TIAN PENG PENG WENXIN LI ZHE CHEN TAO LAI XIANGPING LI WEI CUI HONGBO LIU AI LI JUNJIE XIE TAO ZHANG LIN |
description | The invention discloses a power load clustering analysis method based on correlation coefficient improved K-means in the technical field of power load clustering analysis, and the method comprises thesteps: preprocessing load data through wavelet transformation under the condition that the power load data often contains an abnormal value; therefore, obviously wrong values and smooth data in the load data are eliminated, and meanwhile, dimensionality reduction is performed on the data by adopting a principal component analysis method, so that the calculation complexity during clustering is reduced, and the clustering efficiency is improved; clustering analysis on the power load data is facilitated, information such as power consumption and power utilization rules of users can be accuratelyobtained through analysis, and convenience is brought to a power distribution department to reasonably distribute electric energy in the future, so that the purposes of improving the working efficiency of enterprises and savi |
format | Patent |
fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN112215490A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN112215490A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN112215490A3</originalsourceid><addsrcrecordid>eNqNyjEKAjEQRuFtLES9w3iABbNqYSmLIghiIVguY_aPBrKZJRMVb6-IB7B6r_iGxfkoTyQKwi3ZcNeM5OOVOHJ4qVfqkG_S0oUVLUkkKykhcPbfh3PeesRMvuuTPD5mX3bgqONi4DgoJr-Oiul2c6p3JXppoD1bROSmPhhTVWa5WM3W83_MG42KOjE</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Power load clustering analysis method based on correlation coefficient improved K-means</title><source>esp@cenet</source><creator>LIU DINGHAO ; ZHOU JINGJING ; DAI HAORENG ; WANG SIWEI ; LI JIAO ; XIANG FEI ; ZHONG JIAYONG ; WU GAOXIANG ; LYU XIAOHONG ; TIAN PENG ; PENG WENXIN ; LI ZHE ; CHEN TAO ; LAI XIANGPING ; LI WEI ; CUI HONGBO ; LIU AI ; LI JUNJIE ; XIE TAO ; ZHANG LIN</creator><creatorcontrib>LIU DINGHAO ; ZHOU JINGJING ; DAI HAORENG ; WANG SIWEI ; LI JIAO ; XIANG FEI ; ZHONG JIAYONG ; WU GAOXIANG ; LYU XIAOHONG ; TIAN PENG ; PENG WENXIN ; LI ZHE ; CHEN TAO ; LAI XIANGPING ; LI WEI ; CUI HONGBO ; LIU AI ; LI JUNJIE ; XIE TAO ; ZHANG LIN</creatorcontrib><description>The invention discloses a power load clustering analysis method based on correlation coefficient improved K-means in the technical field of power load clustering analysis, and the method comprises thesteps: preprocessing load data through wavelet transformation under the condition that the power load data often contains an abnormal value; therefore, obviously wrong values and smooth data in the load data are eliminated, and meanwhile, dimensionality reduction is performed on the data by adopting a principal component analysis method, so that the calculation complexity during clustering is reduced, and the clustering efficiency is improved; clustering analysis on the power load data is facilitated, information such as power consumption and power utilization rules of users can be accuratelyobtained through analysis, and convenience is brought to a power distribution department to reasonably distribute electric energy in the future, so that the purposes of improving the working efficiency of enterprises and savi</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ; HANDLING RECORD CARRIERS ; PHYSICS ; PRESENTATION OF DATA ; RECOGNITION OF DATA ; RECORD CARRIERS ; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><creationdate>2021</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20210112&DB=EPODOC&CC=CN&NR=112215490A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25563,76418</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20210112&DB=EPODOC&CC=CN&NR=112215490A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>LIU DINGHAO</creatorcontrib><creatorcontrib>ZHOU JINGJING</creatorcontrib><creatorcontrib>DAI HAORENG</creatorcontrib><creatorcontrib>WANG SIWEI</creatorcontrib><creatorcontrib>LI JIAO</creatorcontrib><creatorcontrib>XIANG FEI</creatorcontrib><creatorcontrib>ZHONG JIAYONG</creatorcontrib><creatorcontrib>WU GAOXIANG</creatorcontrib><creatorcontrib>LYU XIAOHONG</creatorcontrib><creatorcontrib>TIAN PENG</creatorcontrib><creatorcontrib>PENG WENXIN</creatorcontrib><creatorcontrib>LI ZHE</creatorcontrib><creatorcontrib>CHEN TAO</creatorcontrib><creatorcontrib>LAI XIANGPING</creatorcontrib><creatorcontrib>LI WEI</creatorcontrib><creatorcontrib>CUI HONGBO</creatorcontrib><creatorcontrib>LIU AI</creatorcontrib><creatorcontrib>LI JUNJIE</creatorcontrib><creatorcontrib>XIE TAO</creatorcontrib><creatorcontrib>ZHANG LIN</creatorcontrib><title>Power load clustering analysis method based on correlation coefficient improved K-means</title><description>The invention discloses a power load clustering analysis method based on correlation coefficient improved K-means in the technical field of power load clustering analysis, and the method comprises thesteps: preprocessing load data through wavelet transformation under the condition that the power load data often contains an abnormal value; therefore, obviously wrong values and smooth data in the load data are eliminated, and meanwhile, dimensionality reduction is performed on the data by adopting a principal component analysis method, so that the calculation complexity during clustering is reduced, and the clustering efficiency is improved; clustering analysis on the power load data is facilitated, information such as power consumption and power utilization rules of users can be accuratelyobtained through analysis, and convenience is brought to a power distribution department to reasonably distribute electric energy in the future, so that the purposes of improving the working efficiency of enterprises and savi</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</subject><subject>HANDLING RECORD CARRIERS</subject><subject>PHYSICS</subject><subject>PRESENTATION OF DATA</subject><subject>RECOGNITION OF DATA</subject><subject>RECORD CARRIERS</subject><subject>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2021</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNyjEKAjEQRuFtLES9w3iABbNqYSmLIghiIVguY_aPBrKZJRMVb6-IB7B6r_iGxfkoTyQKwi3ZcNeM5OOVOHJ4qVfqkG_S0oUVLUkkKykhcPbfh3PeesRMvuuTPD5mX3bgqONi4DgoJr-Oiul2c6p3JXppoD1bROSmPhhTVWa5WM3W83_MG42KOjE</recordid><startdate>20210112</startdate><enddate>20210112</enddate><creator>LIU DINGHAO</creator><creator>ZHOU JINGJING</creator><creator>DAI HAORENG</creator><creator>WANG SIWEI</creator><creator>LI JIAO</creator><creator>XIANG FEI</creator><creator>ZHONG JIAYONG</creator><creator>WU GAOXIANG</creator><creator>LYU XIAOHONG</creator><creator>TIAN PENG</creator><creator>PENG WENXIN</creator><creator>LI ZHE</creator><creator>CHEN TAO</creator><creator>LAI XIANGPING</creator><creator>LI WEI</creator><creator>CUI HONGBO</creator><creator>LIU AI</creator><creator>LI JUNJIE</creator><creator>XIE TAO</creator><creator>ZHANG LIN</creator><scope>EVB</scope></search><sort><creationdate>20210112</creationdate><title>Power load clustering analysis method based on correlation coefficient improved K-means</title><author>LIU DINGHAO ; ZHOU JINGJING ; DAI HAORENG ; WANG SIWEI ; LI JIAO ; XIANG FEI ; ZHONG JIAYONG ; WU GAOXIANG ; LYU XIAOHONG ; TIAN PENG ; PENG WENXIN ; LI ZHE ; CHEN TAO ; LAI XIANGPING ; LI WEI ; CUI HONGBO ; LIU AI ; LI JUNJIE ; XIE TAO ; ZHANG LIN</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN112215490A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2021</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</topic><topic>HANDLING RECORD CARRIERS</topic><topic>PHYSICS</topic><topic>PRESENTATION OF DATA</topic><topic>RECOGNITION OF DATA</topic><topic>RECORD CARRIERS</topic><topic>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</topic><toplevel>online_resources</toplevel><creatorcontrib>LIU DINGHAO</creatorcontrib><creatorcontrib>ZHOU JINGJING</creatorcontrib><creatorcontrib>DAI HAORENG</creatorcontrib><creatorcontrib>WANG SIWEI</creatorcontrib><creatorcontrib>LI JIAO</creatorcontrib><creatorcontrib>XIANG FEI</creatorcontrib><creatorcontrib>ZHONG JIAYONG</creatorcontrib><creatorcontrib>WU GAOXIANG</creatorcontrib><creatorcontrib>LYU XIAOHONG</creatorcontrib><creatorcontrib>TIAN PENG</creatorcontrib><creatorcontrib>PENG WENXIN</creatorcontrib><creatorcontrib>LI ZHE</creatorcontrib><creatorcontrib>CHEN TAO</creatorcontrib><creatorcontrib>LAI XIANGPING</creatorcontrib><creatorcontrib>LI WEI</creatorcontrib><creatorcontrib>CUI HONGBO</creatorcontrib><creatorcontrib>LIU AI</creatorcontrib><creatorcontrib>LI JUNJIE</creatorcontrib><creatorcontrib>XIE TAO</creatorcontrib><creatorcontrib>ZHANG LIN</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>LIU DINGHAO</au><au>ZHOU JINGJING</au><au>DAI HAORENG</au><au>WANG SIWEI</au><au>LI JIAO</au><au>XIANG FEI</au><au>ZHONG JIAYONG</au><au>WU GAOXIANG</au><au>LYU XIAOHONG</au><au>TIAN PENG</au><au>PENG WENXIN</au><au>LI ZHE</au><au>CHEN TAO</au><au>LAI XIANGPING</au><au>LI WEI</au><au>CUI HONGBO</au><au>LIU AI</au><au>LI JUNJIE</au><au>XIE TAO</au><au>ZHANG LIN</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Power load clustering analysis method based on correlation coefficient improved K-means</title><date>2021-01-12</date><risdate>2021</risdate><abstract>The invention discloses a power load clustering analysis method based on correlation coefficient improved K-means in the technical field of power load clustering analysis, and the method comprises thesteps: preprocessing load data through wavelet transformation under the condition that the power load data often contains an abnormal value; therefore, obviously wrong values and smooth data in the load data are eliminated, and meanwhile, dimensionality reduction is performed on the data by adopting a principal component analysis method, so that the calculation complexity during clustering is reduced, and the clustering efficiency is improved; clustering analysis on the power load data is facilitated, information such as power consumption and power utilization rules of users can be accuratelyobtained through analysis, and convenience is brought to a power distribution department to reasonably distribute electric energy in the future, so that the purposes of improving the working efficiency of enterprises and savi</abstract><oa>free_for_read</oa></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | |
ispartof | |
issn | |
language | chi ; eng |
recordid | cdi_epo_espacenet_CN112215490A |
source | esp@cenet |
subjects | CALCULATING COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES HANDLING RECORD CARRIERS PHYSICS PRESENTATION OF DATA RECOGNITION OF DATA RECORD CARRIERS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
title | Power load clustering analysis method based on correlation coefficient improved K-means |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-08T12%3A35%3A50IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=LIU%20DINGHAO&rft.date=2021-01-12&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN112215490A%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |