Architectures and Intelligence at the Intersection of Smart Grid, Internet of Energy, and Industry 5.0 Manufacturing Systems
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Industrial Electronics".
Deadline for manuscript submissions: 15 February 2027 | Viewed by 40
Special Issue Editors
Interests: power system; power electronics; next-gen networks; micro/smart grid technologies; cyber–physical system; network softwarization (SDN-NFV); cybersecurity; Internet of Things (IoT); cloud computing
Interests: network monitoring and orchestration; software-defined networking; AI/ML; 5G/6G; blockchain; cyber–physical system; digital twin; edge computing
Special Issue Information
Dear Colleagues,
This Special Issue focuses on the convergence of smart grids, the Internet of Energy (IoE), and Industry 5.0 manufacturing systems. It seeks to explore how intelligent architectures, real-time communication, and resilient control mechanisms can enable the next generation of energy-aware, cyber–physical manufacturing infrastructures. The emphasis is on integrating energy distribution intelligence with digitalized production environments using technologies such as digital twins, edge–cloud computing, software-defined networking (SDN), AI, and blockchain.
We welcome the submission of original research articles, comprehensive reviews, system designs, and field applications that address technological solutions at the intersection of smart energy and manufacturing. Topics of interest for this Special Issue include, but are not limited to, the following:
- SDN/NFV-enabled architectures for programmable energy-manufacturing networks;
- Digital twins for synchronization and simulation of energy-aware manufacturing systems;
- Blockchain-based traceability and security in IoE-manufacturing ecosystems;
- Low-latency and hybrid communication infrastructures;
- Edge–cloud intelligence for MaaS and Industry 5.0 frameworks;
- Smart grid-driven optimization of manufacturing energy usage;
- Resilient microservice and multi-agent frameworks for Industry 5.0;
- Cybersecurity and quantum-resilient protocols in energy-aware production;
- Experimental deployments, simulations, and case studies.
The primary purpose of this Special Issue is to foster interdisciplinary research that bridges the traditionally separate domains of energy systems and manufacturing. As manufacturing evolves toward Industry 5.0, characterized by sustainability, resilience, and human–machine collaboration, there is a growing need to integrate intelligent energy management into the fabric of manufacturing infrastructures. This Special Issue aims to highlight how smart grid and IoE technologies can empower Manufacturing-as-a-Service (MaaS) models and enable context-aware, adaptive, and energy-efficient industrial processes.
While extensive literature exists separately in the domains of smart grid, IoE, and smart manufacturing, relatively little research has addressed the system-level integration of these fields in the context of Industry 5.0. Existing studies often focus on energy optimization in grid systems, or digital transformation in manufacturing, but fail to capture their interdependency in real-world, service-oriented, and energy-sensitive environments. This Special Issue fills that gap by presenting architectures, algorithms, and deployments that unite these domains under a cohesive, cyber–physical umbrella. Therefore, this Special Issue will serve as a valuable supplement to the existing literature by introducing cross-domain intelligence, programmable energy-manufacturing convergence, and practical deployment insights relevant to academia and industry alike.
Dr. Harsh Kumar
Dr. Petro Tshakwanda
Guest Editors
Manuscript Submission Information
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Keywords
- smart grid
- Internet of Energy (IoE)
- Industry 5.0
- smart manufacturing
- Manufacturing-as-a-Service (MaaS)
- Digital Twin (DT)
- edge–cloud architecture
- Software-Defined Networking (SDN)
- Cyber–Physical Systems (CPSs)
- energy-aware manufacturing
- distributed manufacturing systems
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