Academic Journal
SDecPP-DC: State Decomposition Privacy-Preserving Optimization Algorithm for Incentive-Based Demand Response in Smart Grid.
| Τίτλος: | SDecPP-DC: State Decomposition Privacy-Preserving Optimization Algorithm for Incentive-Based Demand Response in Smart Grid. |
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| Συγγραφείς: | Bi, Yang, Dong, Tao |
| Πηγή: | Mathematics (2227-7390); May2026, Vol. 14 Issue 9, p1511, 15p |
| Θεματικοί όροι: | Energy demand management, Data privacy, Mathematical optimization, Electronic data processing, Smart power grids, Iterative methods (Mathematics), Synchronization |
| Περίληψη: | This paper considers the incentive-based demand response (IDR) economic dispatch problem (EDP) in smart grid while preserving the privacy of sensitive information, where the sensitive information is the consumers' electricity consumption. The incentive-based demand response (IDR) optimization objective function as an EDP is established. A novel state decomposition-based privacy-preserving distributed consensus algorithm (SDecPP-DC) is designed to address this EDP, where the state decomposition mechanism is proposed to preserve the privacy of sensitive information. The feedback gains in the SDecPP-DC algorithm for the mismatch variables are non-coordinated and constant. The convergence of the proposed SDecPP-DC algorithm is theoretically proved by using multi-parameter perturbation theory. It is shown that the SDecPP-DC algorithm can deal with the directed network topology with a row-stochastic matrix, and the convergence point is the optimal solution of EDP. Finally, the correctness and effectiveness of SDecPP-DC are confirmed by the experiments. [ABSTRACT FROM AUTHOR] |
| Copyright of Mathematics (2227-7390) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://resolver.ebsco.com/c/fiv2js/result?sid=EBSCO:edb&genre=article&issn=22277390&ISBN=&volume=14&issue=9&date=20260501&spage=1511&pages=1511-1525&title=Mathematics (2227-7390)&atitle=SDecPP-DC%3A%20State%20Decomposition%20Privacy-Preserving%20Optimization%20Algorithm%20for%20Incentive-Based%20Demand%20Response%20in%20Smart%20Grid.&aulast=Bi%2C%20Yang&id=DOI:10.3390/math14091511 Name: Full Text Finder (for New FTF UI) (ns324271) Category: fullText Text: Full Text Finder MouseOverText: Full Text Finder |
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| Items | – Name: Title Label: Title Group: Ti Data: SDecPP-DC: State Decomposition Privacy-Preserving Optimization Algorithm for Incentive-Based Demand Response in Smart Grid. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Bi%2C+Yang%22">Bi, Yang</searchLink><br /><searchLink fieldCode="AR" term="%22Dong%2C+Tao%22">Dong, Tao</searchLink> – Name: TitleSource Label: Source Group: Src Data: Mathematics (2227-7390); May2026, Vol. 14 Issue 9, p1511, 15p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Energy+demand+management%22">Energy demand management</searchLink><br /><searchLink fieldCode="DE" term="%22Data+privacy%22">Data privacy</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+data+processing%22">Electronic data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Smart+power+grids%22">Smart power grids</searchLink><br /><searchLink fieldCode="DE" term="%22Iterative+methods+%28Mathematics%29%22">Iterative methods (Mathematics)</searchLink><br /><searchLink fieldCode="DE" term="%22Synchronization%22">Synchronization</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This paper considers the incentive-based demand response (IDR) economic dispatch problem (EDP) in smart grid while preserving the privacy of sensitive information, where the sensitive information is the consumers' electricity consumption. The incentive-based demand response (IDR) optimization objective function as an EDP is established. A novel state decomposition-based privacy-preserving distributed consensus algorithm (SDecPP-DC) is designed to address this EDP, where the state decomposition mechanism is proposed to preserve the privacy of sensitive information. The feedback gains in the SDecPP-DC algorithm for the mismatch variables are non-coordinated and constant. The convergence of the proposed SDecPP-DC algorithm is theoretically proved by using multi-parameter perturbation theory. It is shown that the SDecPP-DC algorithm can deal with the directed network topology with a row-stochastic matrix, and the convergence point is the optimal solution of EDP. Finally, the correctness and effectiveness of SDecPP-DC are confirmed by the experiments. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Mathematics (2227-7390) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/math14091511 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 15 StartPage: 1511 Subjects: – SubjectFull: Energy demand management Type: general – SubjectFull: Data privacy Type: general – SubjectFull: Mathematical optimization Type: general – SubjectFull: Electronic data processing Type: general – SubjectFull: Smart power grids Type: general – SubjectFull: Iterative methods (Mathematics) Type: general – SubjectFull: Synchronization Type: general Titles: – TitleFull: SDecPP-DC: State Decomposition Privacy-Preserving Optimization Algorithm for Incentive-Based Demand Response in Smart Grid. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Bi, Yang – PersonEntity: Name: NameFull: Dong, Tao IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 22277390 Numbering: – Type: volume Value: 14 – Type: issue Value: 9 Titles: – TitleFull: Mathematics (2227-7390) Type: main |
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