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A Novel MBSE-Driven Multi-Agent Framework for Enhancing Cyber-Physical Security in Smart Grids.

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Title: A Novel MBSE-Driven Multi-Agent Framework for Enhancing Cyber-Physical Security in Smart Grids.
Authors: Wang, Yuantao1 (AUTHOR), Yan, Dingyu2 (AUTHOR), Lu, Xiyu1,2 (AUTHOR), Gao, Guohua1,2 (AUTHOR) gaoguohua@bjut.edu.cn
Source: Energies (19961073). May2026, Vol. 19 Issue 10, p2420. 18p.
Subject Terms: *Multiagent systems, *Smart power grids, *Distributed power generation, *Model-driven software architecture, *Digital twin, *Internet security, *Decentralized control systems, *Cyber physical systems
Abstract: The paradigm shift towards highly distributed renewable energy integration has exponentially increased the topological complexity of Smart Grids. Consequently, the tight coupling between operational and information networks exposes these systems to severe cyber threats, including data breaches and malicious intrusions. Conventional centralized dispatch paradigms struggle with delayed responses, suboptimal coordination, and opaque design lifecycles. To overcome these limitations, this study introduces an innovative Multi-Agent System architecture engineered via Model-Based Systems Engineering methodologies. By employing SysML, we established a comprehensive digital twin encompassing system requirements, functional layouts, and logical boundaries. The proposed framework deploys a decentralized hierarchy of four specialized agents—perception, decision making, execution, and collaboration—to execute collaborative defense protocols strictly bounded by electrical safety constraints. Validation through IEEE 33-node distribution network simulations confirms that the framework rapidly identifies and mitigates Denial of Service, data falsification, and unauthorized device access. This MBSE-MAS paradigm demonstrates exceptional scalability and resilience, offering a highly practical blueprint for safeguarding next-generation power infrastructure. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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Header DbId: enr
DbLabel: Energy & Power Source
An: 194141535
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PubTypeId: academicJournal
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  Label: Title
  Group: Ti
  Data: A Novel MBSE-Driven Multi-Agent Framework for Enhancing Cyber-Physical Security in Smart Grids.
– Name: Author
  Label: Authors
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  Data: <searchLink fieldCode="AR" term="%22Wang%2C+Yuantao%22">Wang, Yuantao</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yan%2C+Dingyu%22">Yan, Dingyu</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lu%2C+Xiyu%22">Lu, Xiyu</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Gao%2C+Guohua%22">Gao, Guohua</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> gaoguohua@bjut.edu.cn</i>
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  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. May2026, Vol. 19 Issue 10, p2420. 18p.
– Name: Subject
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  Data: *<searchLink fieldCode="DE" term="%22Multiagent+systems%22">Multiagent systems</searchLink><br />*<searchLink fieldCode="DE" term="%22Smart+power+grids%22">Smart power grids</searchLink><br />*<searchLink fieldCode="DE" term="%22Distributed+power+generation%22">Distributed power generation</searchLink><br />*<searchLink fieldCode="DE" term="%22Model-driven+software+architecture%22">Model-driven software architecture</searchLink><br />*<searchLink fieldCode="DE" term="%22Digital+twin%22">Digital twin</searchLink><br />*<searchLink fieldCode="DE" term="%22Internet+security%22">Internet security</searchLink><br />*<searchLink fieldCode="DE" term="%22Decentralized+control+systems%22">Decentralized control systems</searchLink><br />*<searchLink fieldCode="DE" term="%22Cyber+physical+systems%22">Cyber physical systems</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The paradigm shift towards highly distributed renewable energy integration has exponentially increased the topological complexity of Smart Grids. Consequently, the tight coupling between operational and information networks exposes these systems to severe cyber threats, including data breaches and malicious intrusions. Conventional centralized dispatch paradigms struggle with delayed responses, suboptimal coordination, and opaque design lifecycles. To overcome these limitations, this study introduces an innovative Multi-Agent System architecture engineered via Model-Based Systems Engineering methodologies. By employing SysML, we established a comprehensive digital twin encompassing system requirements, functional layouts, and logical boundaries. The proposed framework deploys a decentralized hierarchy of four specialized agents—perception, decision making, execution, and collaboration—to execute collaborative defense protocols strictly bounded by electrical safety constraints. Validation through IEEE 33-node distribution network simulations confirms that the framework rapidly identifies and mitigates Denial of Service, data falsification, and unauthorized device access. This MBSE-MAS paradigm demonstrates exceptional scalability and resilience, offering a highly practical blueprint for safeguarding next-generation power infrastructure. [ABSTRACT FROM AUTHOR]
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.3390/en19102420
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
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        PageCount: 18
        StartPage: 2420
    Subjects:
      – SubjectFull: Multiagent systems
        Type: general
      – SubjectFull: Smart power grids
        Type: general
      – SubjectFull: Distributed power generation
        Type: general
      – SubjectFull: Model-driven software architecture
        Type: general
      – SubjectFull: Digital twin
        Type: general
      – SubjectFull: Internet security
        Type: general
      – SubjectFull: Decentralized control systems
        Type: general
      – SubjectFull: Cyber physical systems
        Type: general
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      – TitleFull: A Novel MBSE-Driven Multi-Agent Framework for Enhancing Cyber-Physical Security in Smart Grids.
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            NameFull: Wang, Yuantao
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            NameFull: Yan, Dingyu
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            NameFull: Lu, Xiyu
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            NameFull: Gao, Guohua
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            – D: 15
              M: 05
              Text: May2026
              Type: published
              Y: 2026
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              Value: 19
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              Value: 10
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            – TitleFull: Energies (19961073)
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