Multi-dimensional decomposition and intelligent fusion power load prediction method and related equipment

The invention provides a multi-dimensional decomposition and intelligent fusion power load prediction method and related equipment, and the method comprises the steps: carrying out the processing of historical power load data and historical weather data of a target region, and obtaining a periodic l...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: MAO HAOCHUN, WANG JUAN, CHEN LU, YUAN XIAODI, TAN HUANZHEN, CHEN SHUNFEI, LIU HAO, WANG WENHONG, ZOU WEIBIN, LUO WENFENG, HU JIEQIANG
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 MAO HAOCHUN
WANG JUAN
CHEN LU
YUAN XIAODI
TAN HUANZHEN
CHEN SHUNFEI
LIU HAO
WANG WENHONG
ZOU WEIBIN
LUO WENFENG
HU JIEQIANG
description The invention provides a multi-dimensional decomposition and intelligent fusion power load prediction method and related equipment, and the method comprises the steps: carrying out the processing of historical power load data and historical weather data of a target region, and obtaining a periodic load component, a non-periodic load component, a weather load component and first feature data; sequentially inputting the aperiodic load components into the trained long-short-term memory network and the time domain convolutional network for prediction, and performing weighted fusion on prediction results to obtain a total prediction result of the aperiodic load components; fusing the weather load component and the first feature data, then inputting the fused weather load component and the first feature data into the trained long-short-term memory network and the time domain convolutional network in sequence for prediction, and carrying out weighted fusion on prediction results to obtain a total prediction result o
format Patent
fullrecord <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN118395384A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN118395384A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN118395384A3</originalsourceid><addsrcrecordid>eNqNzLEKwkAQBNA0FqL-w_oBKUIUYilBsdHKPhzZiS5cbs_cBn_fGPwAq2HgzSwzuY7eJGfpEZJocJ4YrfZRk9jUyQUmCQbv5YFg1I1fRlHfGMirY4oDWNoZ97Cn8rwZ4J2BCa9R4nRu62zROZ-w-eUq255P9_qSI2qDFF2LAGvqW1FU5WFfVrtj-Y_5AO_2Qd0</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Multi-dimensional decomposition and intelligent fusion power load prediction method and related equipment</title><source>esp@cenet</source><creator>MAO HAOCHUN ; WANG JUAN ; CHEN LU ; YUAN XIAODI ; TAN HUANZHEN ; CHEN SHUNFEI ; LIU HAO ; WANG WENHONG ; ZOU WEIBIN ; LUO WENFENG ; HU JIEQIANG</creator><creatorcontrib>MAO HAOCHUN ; WANG JUAN ; CHEN LU ; YUAN XIAODI ; TAN HUANZHEN ; CHEN SHUNFEI ; LIU HAO ; WANG WENHONG ; ZOU WEIBIN ; LUO WENFENG ; HU JIEQIANG</creatorcontrib><description>The invention provides a multi-dimensional decomposition and intelligent fusion power load prediction method and related equipment, and the method comprises the steps: carrying out the processing of historical power load data and historical weather data of a target region, and obtaining a periodic load component, a non-periodic load component, a weather load component and first feature data; sequentially inputting the aperiodic load components into the trained long-short-term memory network and the time domain convolutional network for prediction, and performing weighted fusion on prediction results to obtain a total prediction result of the aperiodic load components; fusing the weather load component and the first feature data, then inputting the fused weather load component and the first feature data into the trained long-short-term memory network and the time domain convolutional network in sequence for prediction, and carrying out weighted fusion on prediction results to obtain a total prediction result o</description><language>chi ; eng</language><subject>CALCULATING ; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER ; COUNTING ; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ; ELECTRIC DIGITAL DATA PROCESSING ; ELECTRICITY ; GENERATION ; PHYSICS ; SYSTEMS FOR STORING ELECTRIC ENERGY ; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><creationdate>2024</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&amp;date=20240726&amp;DB=EPODOC&amp;CC=CN&amp;NR=118395384A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25563,76318</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20240726&amp;DB=EPODOC&amp;CC=CN&amp;NR=118395384A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>MAO HAOCHUN</creatorcontrib><creatorcontrib>WANG JUAN</creatorcontrib><creatorcontrib>CHEN LU</creatorcontrib><creatorcontrib>YUAN XIAODI</creatorcontrib><creatorcontrib>TAN HUANZHEN</creatorcontrib><creatorcontrib>CHEN SHUNFEI</creatorcontrib><creatorcontrib>LIU HAO</creatorcontrib><creatorcontrib>WANG WENHONG</creatorcontrib><creatorcontrib>ZOU WEIBIN</creatorcontrib><creatorcontrib>LUO WENFENG</creatorcontrib><creatorcontrib>HU JIEQIANG</creatorcontrib><title>Multi-dimensional decomposition and intelligent fusion power load prediction method and related equipment</title><description>The invention provides a multi-dimensional decomposition and intelligent fusion power load prediction method and related equipment, and the method comprises the steps: carrying out the processing of historical power load data and historical weather data of a target region, and obtaining a periodic load component, a non-periodic load component, a weather load component and first feature data; sequentially inputting the aperiodic load components into the trained long-short-term memory network and the time domain convolutional network for prediction, and performing weighted fusion on prediction results to obtain a total prediction result of the aperiodic load components; fusing the weather load component and the first feature data, then inputting the fused weather load component and the first feature data into the trained long-short-term memory network and the time domain convolutional network in sequence for prediction, and carrying out weighted fusion on prediction results to obtain a total prediction result o</description><subject>CALCULATING</subject><subject>CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>CONVERSION OR DISTRIBUTION OF ELECTRIC POWER</subject><subject>COUNTING</subject><subject>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>ELECTRICITY</subject><subject>GENERATION</subject><subject>PHYSICS</subject><subject>SYSTEMS FOR STORING ELECTRIC ENERGY</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>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNzLEKwkAQBNA0FqL-w_oBKUIUYilBsdHKPhzZiS5cbs_cBn_fGPwAq2HgzSwzuY7eJGfpEZJocJ4YrfZRk9jUyQUmCQbv5YFg1I1fRlHfGMirY4oDWNoZ97Cn8rwZ4J2BCa9R4nRu62zROZ-w-eUq255P9_qSI2qDFF2LAGvqW1FU5WFfVrtj-Y_5AO_2Qd0</recordid><startdate>20240726</startdate><enddate>20240726</enddate><creator>MAO HAOCHUN</creator><creator>WANG JUAN</creator><creator>CHEN LU</creator><creator>YUAN XIAODI</creator><creator>TAN HUANZHEN</creator><creator>CHEN SHUNFEI</creator><creator>LIU HAO</creator><creator>WANG WENHONG</creator><creator>ZOU WEIBIN</creator><creator>LUO WENFENG</creator><creator>HU JIEQIANG</creator><scope>EVB</scope></search><sort><creationdate>20240726</creationdate><title>Multi-dimensional decomposition and intelligent fusion power load prediction method and related equipment</title><author>MAO HAOCHUN ; WANG JUAN ; CHEN LU ; YUAN XIAODI ; TAN HUANZHEN ; CHEN SHUNFEI ; LIU HAO ; WANG WENHONG ; ZOU WEIBIN ; LUO WENFENG ; HU JIEQIANG</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN118395384A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2024</creationdate><topic>CALCULATING</topic><topic>CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>CONVERSION OR DISTRIBUTION OF ELECTRIC POWER</topic><topic>COUNTING</topic><topic>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>ELECTRICITY</topic><topic>GENERATION</topic><topic>PHYSICS</topic><topic>SYSTEMS FOR STORING ELECTRIC ENERGY</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>MAO HAOCHUN</creatorcontrib><creatorcontrib>WANG JUAN</creatorcontrib><creatorcontrib>CHEN LU</creatorcontrib><creatorcontrib>YUAN XIAODI</creatorcontrib><creatorcontrib>TAN HUANZHEN</creatorcontrib><creatorcontrib>CHEN SHUNFEI</creatorcontrib><creatorcontrib>LIU HAO</creatorcontrib><creatorcontrib>WANG WENHONG</creatorcontrib><creatorcontrib>ZOU WEIBIN</creatorcontrib><creatorcontrib>LUO WENFENG</creatorcontrib><creatorcontrib>HU JIEQIANG</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>MAO HAOCHUN</au><au>WANG JUAN</au><au>CHEN LU</au><au>YUAN XIAODI</au><au>TAN HUANZHEN</au><au>CHEN SHUNFEI</au><au>LIU HAO</au><au>WANG WENHONG</au><au>ZOU WEIBIN</au><au>LUO WENFENG</au><au>HU JIEQIANG</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Multi-dimensional decomposition and intelligent fusion power load prediction method and related equipment</title><date>2024-07-26</date><risdate>2024</risdate><abstract>The invention provides a multi-dimensional decomposition and intelligent fusion power load prediction method and related equipment, and the method comprises the steps: carrying out the processing of historical power load data and historical weather data of a target region, and obtaining a periodic load component, a non-periodic load component, a weather load component and first feature data; sequentially inputting the aperiodic load components into the trained long-short-term memory network and the time domain convolutional network for prediction, and performing weighted fusion on prediction results to obtain a total prediction result of the aperiodic load components; fusing the weather load component and the first feature data, then inputting the fused weather load component and the first feature data into the trained long-short-term memory network and the time domain convolutional network in sequence for prediction, and carrying out weighted fusion on prediction results to obtain a total prediction result o</abstract><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier
ispartof
issn
language chi ; eng
recordid cdi_epo_espacenet_CN118395384A
source esp@cenet
subjects CALCULATING
CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
ELECTRIC DIGITAL DATA PROCESSING
ELECTRICITY
GENERATION
PHYSICS
SYSTEMS FOR STORING ELECTRIC ENERGY
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
title Multi-dimensional decomposition and intelligent fusion power load prediction method and related equipment
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-12T01%3A49%3A57IST&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=MAO%20HAOCHUN&rft.date=2024-07-26&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN118395384A%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