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

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.

Authors

Institutions

Publication Details

Journal
Energies
Published
2026-05-18
DOI
https://doi.org/10.3390/en19102420
Primary Topic
Smart Grid Security and Resilience
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Yue Wang, Xiyu Lu, GuoHua Gao, DingYu Yan
Energies
Smart Grid Security and Resilience
article

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

Yue Wang, Xiyu Lu, GuoHua Gao, DingYu Yan
article en

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.

EnergiesVol. 19(10)
Beijing University of Technology (CN), National Computer Network Emergency Response Technical Team/Coordination Center of Chinar (CN)
Ministry of Science and Technology of the People's Republic of China
Industry, innovation and infrastructure
Openalex Percentile: Top 6%
Smart Grid Security and Resilience
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.