Gravity energy storage power distribution method based on load prediction model

The invention discloses a gravity energy storage power distribution method based on a load prediction model, relates to a gravity energy storage power distribution technology, and aims to solve the problem of unreasonable gravity energy storage power distribution caused by low load prediction accura...

Full description

Saved in:
Bibliographic Details
Main Authors ZHANG RUI, HAO WENBEI, LIU ZHIYANG, YIN JIALIN, SONG HANGXUAN, XU MINGYU, MU XINGHUA
Format Patent
LanguageChinese
English
Published 15.07.2022
Subjects
Online AccessGet full text

Cover

Loading…
Abstract The invention discloses a gravity energy storage power distribution method based on a load prediction model, relates to a gravity energy storage power distribution technology, and aims to solve the problem of unreasonable gravity energy storage power distribution caused by low load prediction accuracy in the prior art. According to the invention, a load prediction model based on a GAN network is established; the load of the gravity energy storage system is predicted by using the load prediction model, and a prediction result is output; calculating a peak regulation demand value and a frequency modulation demand value based on the prediction result; obtaining the value of a peak regulation participation factor and the value of a frequency modulation participation factor by combining the constraint condition of the gravity energy storage system and adopting a particle swarm algorithm; a peak regulation participation factor and a frequency modulation participation factor are adopted to jointly construct a power
AbstractList The invention discloses a gravity energy storage power distribution method based on a load prediction model, relates to a gravity energy storage power distribution technology, and aims to solve the problem of unreasonable gravity energy storage power distribution caused by low load prediction accuracy in the prior art. According to the invention, a load prediction model based on a GAN network is established; the load of the gravity energy storage system is predicted by using the load prediction model, and a prediction result is output; calculating a peak regulation demand value and a frequency modulation demand value based on the prediction result; obtaining the value of a peak regulation participation factor and the value of a frequency modulation participation factor by combining the constraint condition of the gravity energy storage system and adopting a particle swarm algorithm; a peak regulation participation factor and a frequency modulation participation factor are adopted to jointly construct a power
Author HAO WENBEI
LIU ZHIYANG
YIN JIALIN
ZHANG RUI
SONG HANGXUAN
MU XINGHUA
XU MINGYU
Author_xml – fullname: ZHANG RUI
– fullname: HAO WENBEI
– fullname: LIU ZHIYANG
– fullname: YIN JIALIN
– fullname: SONG HANGXUAN
– fullname: XU MINGYU
– fullname: MU XINGHUA
BookMark eNrjYmDJy89L5WTwdy9KLMssqVRIzUstSq9UKC7JL0pMT1UoyC9PLVJIySwuKcpMKi3JzM9TyE0tychPUUhKLE5NUQDyc_ITUxQKilJTMpMh8vkpqTk8DKxpiTnFqbxQmptB0c01xNlDN7UgPz61uCAxGWhRSbyzn6GhibmpuaGBuaMxMWoAzJk5Jw
ContentType Patent
DBID EVB
DatabaseName esp@cenet
DatabaseTitleList
Database_xml – sequence: 1
  dbid: EVB
  name: esp@cenet
  url: http://worldwide.espacenet.com/singleLineSearch?locale=en_EP
  sourceTypes: Open Access Repository
DeliveryMethod fulltext_linktorsrc
Discipline Medicine
Chemistry
Sciences
Physics
DocumentTitleAlternate 一种基于负荷预测模型的重力储能功率分配方法
ExternalDocumentID CN114757107A
GroupedDBID EVB
ID FETCH-epo_espacenet_CN114757107A3
IEDL.DBID EVB
IngestDate Fri Jul 19 14:58:31 EDT 2024
IsOpenAccess true
IsPeerReviewed false
IsScholarly false
Language Chinese
English
LinkModel DirectLink
MergedId FETCHMERGED-epo_espacenet_CN114757107A3
Notes Application Number: CN202210499867
OpenAccessLink https://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20220715&DB=EPODOC&CC=CN&NR=114757107A
ParticipantIDs epo_espacenet_CN114757107A
PublicationCentury 2000
PublicationDate 20220715
PublicationDateYYYYMMDD 2022-07-15
PublicationDate_xml – month: 07
  year: 2022
  text: 20220715
  day: 15
PublicationDecade 2020
PublicationYear 2022
RelatedCompanies STATE GRID CORPORATION OF CHINA
STATE GRID HEILONGJIANG ELECTRIC POWER COMPANY LIMITED ELECTRIC POWER RESEARCH INSTITUTE
RelatedCompanies_xml – name: STATE GRID HEILONGJIANG ELECTRIC POWER COMPANY LIMITED ELECTRIC POWER RESEARCH INSTITUTE
– name: STATE GRID CORPORATION OF CHINA
Score 3.5329983
Snippet The invention discloses a gravity energy storage power distribution method based on a load prediction model, relates to a gravity energy storage power...
SourceID epo
SourceType Open Access Repository
SubjectTerms CALCULATING
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
Title Gravity energy storage power distribution method based on load prediction model
URI https://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20220715&DB=EPODOC&locale=&CC=CN&NR=114757107A
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV1LS8NAEB5qfd60KlofrCC5BZvY7eMQxG5Si9C0SJXeSrq7oYo0IY0I_npntqn1osfdhWF3YPbbx8z3AVzXYs25dtt2HDddmxip7KiuazZXkYwV8Zc7VODcDxu95_rjmI9L8LaqhTE8oZ-GHBEjSmK852a_TtePWL7JrVzcTF-xK7nrjjzfKm7HrouIyS2_4wXDgT8QlhCeCK3wycNjf5MjmjbvN2CTaLeIZz946VBVSvobUrr7sDVEa_P8AEpfswrsipXyWgV2-sWHdwW2TYamXGBnEYWLQxg8ZBFJPjBtCvcYJTjitsBSUjxjiqwUKlZsKRDNCKsUw_Z7EimWZmR_OU5COEdw1Q1GomfjHCc_DpmIcL2c22Moz5O5PgE2bTXqXMk23tHw3N_SGIpSyZhLh8RonNopVP-2U_1v8Az2yLn0punwcyjn2Ye-QDDOp5fGi98kNY7r
link.rule.ids 230,308,780,885,25564,76547
linkProvider European Patent Office
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV3dT8IwEL8ofuCbokbxqyZmb4tsUgYPi5EORIVBDBreyGi7qDGwwIyJf713ZYgv-tg2ubSX3P2u7d39AC5KseZcuzU7jj3Xpo5UdlTWJZurSMaK-pc7VODcCSutp_L9gA9W4G1RC2P6hH6a5ohoURLtPTX-Olk-YgUmt3J2OXrFqcl1s-8HVnY7dl1ETG4Fdb_R6wZdYQnhi9AKH30M-z2OaOrdrMKaR4y7FDo916kqJfkNKc1tWO-htHG6AytfLwXIiwXzWgE2O9mHdwE2TIamnOFkZoWzXejeTiOifGDaFO4xSnBEt8ASYjxjiqRkLFZsThDNCKsUw_H7JFIsmZL8-ToR4ezBebPRFy0b9zj8UchQhMvjXO1DbjwZ6wNgo2qlzJWs4R0N4_6qRlOUSsZcOkRG45QOofi3nOJ_i2eQb_U77WH7Lnw4gi1SNL1vOvwYcun0Q58gMKejU6PRbwHIkdw
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Apatent&rft.title=Gravity+energy+storage+power+distribution+method+based+on+load+prediction+model&rft.inventor=ZHANG+RUI&rft.inventor=HAO+WENBEI&rft.inventor=LIU+ZHIYANG&rft.inventor=YIN+JIALIN&rft.inventor=SONG+HANGXUAN&rft.inventor=XU+MINGYU&rft.inventor=MU+XINGHUA&rft.date=2022-07-15&rft.externalDBID=A&rft.externalDocID=CN114757107A