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Prediction Model of Elastic Load Resource Regulation Potential under Hierarchical and Partitioned Dynamic Control Architecture

Journal of physics. Conference series, 2022-08, Vol.2331 (1), p.12014 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;Published under licence by IOP Publishing Ltd. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1742-6588 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/2331/1/012014

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  • Title:
    Prediction Model of Elastic Load Resource Regulation Potential under Hierarchical and Partitioned Dynamic Control Architecture
  • Author: Zhou, Ying ; Chen, Songsong ; Shi, Kun ; Gong, Taorong ; Yuan, Jindou ; Li, Bo ; Yang, Shihai
  • Subjects: Dynamic control ; Prediction models
  • Is Part Of: Journal of physics. Conference series, 2022-08, Vol.2331 (1), p.12014
  • Description: Abstract In order to deal with the problem of energy shortage, demand side management has attracted more and more attention. Taking demand side resources as an example to understand the regulation potential of demand side resources, this paper designs a hierarchical and partitioned dynamic regulation architecture for demand side adjustable resources, which can carry out the interconnection between multi-level subjects and efficient information interaction. The regulation potential prediction model of elastic load is established through the hierarchical and partitioned architecture, and the credible and adjustable potential of resident users under two regulation scenarios is obtained through calculation: participating in emergency load reduction and peak valley difference, which proves the effectiveness of the architecture.
  • Publisher: Bristol: IOP Publishing
  • Language: English
  • Identifier: ISSN: 1742-6588
    EISSN: 1742-6596
    DOI: 10.1088/1742-6596/2331/1/012014
  • Source: Geneva Foundation Free Medical Journals at publisher websites
    IOP Publishing (Open access)
    IOPscience (Open Access)
    ProQuest Central
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