Energy Routing Protocols for Energy Internet: A Review on Multi-Agent Systems, Metaheuristics, and Artificial Intelligence Approaches
The Energy Internet (EI) is transforming power networks by integrating Smart Grids (SGs), Distributed Energy Sources (DESs), and advanced communication and data technologies. This transformation increases complexity, as energy transmission evolves into a multi-source, multi-path, and multi-load syst...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10908236/ |
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| author | Amani Fawaz Imad Mougharbel Kamal Al-Haddad Hadi Y. Kanaan |
| author_facet | Amani Fawaz Imad Mougharbel Kamal Al-Haddad Hadi Y. Kanaan |
| author_sort | Amani Fawaz |
| collection | DOAJ |
| description | The Energy Internet (EI) is transforming power networks by integrating Smart Grids (SGs), Distributed Energy Sources (DESs), and advanced communication and data technologies. This transformation increases complexity, as energy transmission evolves into a multi-source, multi-path, and multi-load system, with Peer-to-Peer (P2P) energy trading markets and Energy Routers as central drivers. As power networks grow and become more decentralized, the need for efficient and adaptive power routing protocols has become crucial to ensure their reliable and scalable management. This review focuses on energy routing strategies using multi-Agent architectures, Artificial Intelligence, and Metaheuristic optimization techniques. These approaches are well-suited to support the transformation of power networks into more distributed, dynamic, and complex systems. Spanning research from 2018 to 2024, this paper consolidates diverse studies, filling a critical gap by providing a comprehensive overview of power routing solutions for the evolving EI. It highlights key methodologies, limitations, and future research directions, offering a valuable reference for researchers. |
| format | Article |
| id | doaj-art-62a8023f90214c97bf227efc76d930df |
| institution | OA Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-62a8023f90214c97bf227efc76d930df2025-08-20T01:58:00ZengIEEEIEEE Access2169-35362025-01-0113416254164310.1109/ACCESS.2025.354662010908236Energy Routing Protocols for Energy Internet: A Review on Multi-Agent Systems, Metaheuristics, and Artificial Intelligence ApproachesAmani Fawaz0https://orcid.org/0009-0002-6532-9926Imad Mougharbel1Kamal Al-Haddad2https://orcid.org/0000-0003-0276-4277Hadi Y. Kanaan3https://orcid.org/0000-0003-4477-9477Department of Doctoral Studies, Faculty of Engineering, Saint Joseph University of Beirut, Beirut, LebanonDepartment of Electrical Engineering, École de Technologie Supérieure, Montreal, QC, CanadaDepartment of Electrical Engineering, École de Technologie Supérieure, Montreal, QC, CanadaDepartment of Doctoral Studies, Faculty of Engineering, Saint Joseph University of Beirut, Beirut, LebanonThe Energy Internet (EI) is transforming power networks by integrating Smart Grids (SGs), Distributed Energy Sources (DESs), and advanced communication and data technologies. This transformation increases complexity, as energy transmission evolves into a multi-source, multi-path, and multi-load system, with Peer-to-Peer (P2P) energy trading markets and Energy Routers as central drivers. As power networks grow and become more decentralized, the need for efficient and adaptive power routing protocols has become crucial to ensure their reliable and scalable management. This review focuses on energy routing strategies using multi-Agent architectures, Artificial Intelligence, and Metaheuristic optimization techniques. These approaches are well-suited to support the transformation of power networks into more distributed, dynamic, and complex systems. Spanning research from 2018 to 2024, this paper consolidates diverse studies, filling a critical gap by providing a comprehensive overview of power routing solutions for the evolving EI. It highlights key methodologies, limitations, and future research directions, offering a valuable reference for researchers.https://ieeexplore.ieee.org/document/10908236/Artificial intelligenceenergy internetenergy routing protocolsmetaheuristicmulti agent systemssmart grid |
| spellingShingle | Amani Fawaz Imad Mougharbel Kamal Al-Haddad Hadi Y. Kanaan Energy Routing Protocols for Energy Internet: A Review on Multi-Agent Systems, Metaheuristics, and Artificial Intelligence Approaches IEEE Access Artificial intelligence energy internet energy routing protocols metaheuristic multi agent systems smart grid |
| title | Energy Routing Protocols for Energy Internet: A Review on Multi-Agent Systems, Metaheuristics, and Artificial Intelligence Approaches |
| title_full | Energy Routing Protocols for Energy Internet: A Review on Multi-Agent Systems, Metaheuristics, and Artificial Intelligence Approaches |
| title_fullStr | Energy Routing Protocols for Energy Internet: A Review on Multi-Agent Systems, Metaheuristics, and Artificial Intelligence Approaches |
| title_full_unstemmed | Energy Routing Protocols for Energy Internet: A Review on Multi-Agent Systems, Metaheuristics, and Artificial Intelligence Approaches |
| title_short | Energy Routing Protocols for Energy Internet: A Review on Multi-Agent Systems, Metaheuristics, and Artificial Intelligence Approaches |
| title_sort | energy routing protocols for energy internet a review on multi agent systems metaheuristics and artificial intelligence approaches |
| topic | Artificial intelligence energy internet energy routing protocols metaheuristic multi agent systems smart grid |
| url | https://ieeexplore.ieee.org/document/10908236/ |
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