Low-carbon demand response method based on combined online learning
The invention discloses a low-carbon demand response method based on combined online learning, and belongs to the technical field of power load management, and the method comprises the steps: constructing a carbon emission model corresponding to a user power consumption behavior, and obtaining a lin...
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| creator | RUAN WENJUN ZHANG YUANSHI KIM, WUK ZHUANG ZHONG HU QINRAN CHEN XINYI HUANG GUAN |
| description | The invention discloses a low-carbon demand response method based on combined online learning, and belongs to the technical field of power load management, and the method comprises the steps: constructing a carbon emission model corresponding to a user power consumption behavior, and obtaining a linear quantitative relation-node carbon potential between a user power adjustment amount and a corresponding carbon reduction amount; dynamic node carbon potential is sent to a user through a carbon table to advocate the user to perform energy conservation and emission reduction; the method comprises the following steps: constructing a low carbon demand response problem under the influence of node carbon potential into a Multi-Armed Bands (MAB) model, introducing a Contextual Multi-Armed Bands (CMAB) theory, proposing a Linear User Confidence Bound LinUCB algorithm to solve the provided model, continuously updating a user selection strategy according to context information (node carbon potential) and a user carbon re |
| format | Patent |
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dynamic node carbon potential is sent to a user through a carbon table to advocate the user to perform energy conservation and emission reduction; the method comprises the following steps: constructing a low carbon demand response problem under the influence of node carbon potential into a Multi-Armed Bands (MAB) model, introducing a Contextual Multi-Armed Bands (CMAB) theory, proposing a Linear User Confidence Bound LinUCB algorithm to solve the provided model, continuously updating a user selection strategy according to context information (node carbon potential) and a user carbon re</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ; PHYSICS ; 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&date=20240227&DB=EPODOC&CC=CN&NR=117610812A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,777,882,25545,76296</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240227&DB=EPODOC&CC=CN&NR=117610812A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>RUAN WENJUN</creatorcontrib><creatorcontrib>ZHANG YUANSHI</creatorcontrib><creatorcontrib>KIM, WUK</creatorcontrib><creatorcontrib>ZHUANG ZHONG</creatorcontrib><creatorcontrib>HU QINRAN</creatorcontrib><creatorcontrib>CHEN XINYI</creatorcontrib><creatorcontrib>HUANG GUAN</creatorcontrib><title>Low-carbon demand response method based on combined online learning</title><description>The invention discloses a low-carbon demand response method based on combined online learning, and belongs to the technical field of power load management, and the method comprises the steps: constructing a carbon emission model corresponding to a user power consumption behavior, and obtaining a linear quantitative relation-node carbon potential between a user power adjustment amount and a corresponding carbon reduction amount; 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dynamic node carbon potential is sent to a user through a carbon table to advocate the user to perform energy conservation and emission reduction; the method comprises the following steps: constructing a low carbon demand response problem under the influence of node carbon potential into a Multi-Armed Bands (MAB) model, introducing a Contextual Multi-Armed Bands (CMAB) theory, proposing a Linear User Confidence Bound LinUCB algorithm to solve the provided model, continuously updating a user selection strategy according to context information (node carbon potential) and a user carbon re</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | Low-carbon demand response method based on combined online learning |
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