Multi-Agent Systems for Decentralized Control and Management of Active Power Grid Peripheries: A Systematic Review
Source abstract
Abstract
The transition from centralized fossil fuel-based power systems toward decentralized smart grids with a high penetration of renewable energy sources (RES) introduces substantial challenges in monitoring, control, coordination, and management. These challenges are particularly evident at the active power grid periphery, defined in this work as the decentralized edge layer of modern power systems comprising low-voltage distribution networks, distributed energy resources (DERs), prosumers, energy storage systems, electric vehicles (EVs), and localized intelligent control entities operating near the consumer side of the grid. This review systematically examines the role of multi-agent systems (MASs) in addressing these emerging challenges. A total of 160 articles, drawn predominantly from top-tier Q1 journals and published up to March 2026, were systematically analyzed to evaluate recent methodological advances, identify persistent research gaps, and compare existing problem formulations and mathematical techniques. The review covers MAS-based applications including distributed energy management, voltage and frequency regulation, demand-side management, microgrid coordination, EV charging coordination, resilience enhancement, and cyber-physical supervisory control. The findings indicate that although MASs offer enhanced scalability, flexibility, resilience, and decentralized decision-making capabilities, existing approaches continue to face significant limitations associated with communication latency, cybersecurity vulnerabilities, interoperability constraints, heterogeneous agent dynamics, and limited real-time experimental validation. Furthermore, this review proposes six emerging research hypotheses targeting underexplored domains, presents a methodological decision flowchart for MAS implementation and selection, and discusses future research directions involving the integration of digital twins, blockchain technologies, edge intelligence, and advanced communication architectures with MAS frameworks.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Smart Grid Energy Management · Smart Grid Security and Resilience · Microgrid Control and Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mechanical Engineering, Yangzhou University, Yangzhou 225009, China
School of Sciences, University of Lancashire (UCLan), Larnaka 7080, Cyprus
Interdisciplinary Science Promotion & Innovative Research Exploration (INSPIRE) Research Centre, Larnaka 7080, Cyprus
Department of Electrical Engineering, Computer Engineering and Informatics, Frederick University, Nicosia 1036, Cyprus
Power Electronics and Systems, Department of Electronic and Computer Engineering, College of Engineering, Design and Physical Sciences, Brunel University London, London UB8 3PH, UK
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