AI-Driven Decentralized Energy Systems: A Review of
Peer-to-Peer Renewable Energy Networks

M. El-Said^1,*, Marwa M. Eid²

¹Electrical Engineering Department, Faculty of Engineering, Mansoura University, Mansoura 35516, Egypt

²Faculty of Artificial Intelligence, Delta University for Science and Technology, Mansoura 11152, Egypt

Emails: Melsaid@mans.edu.eg; mmm@ieee.org

Abstract

This work examines the transformational potential of AI-based decentralized energy systems: P2P renewable energy networks interconnect AI, blockchain technology, and multi-agent systems, thus circumventing the barriers of traditional centralized grids. This paper will trace how their latest trends in real-time energy optimization, secure smart contracts, and autonomous coordination of distributed resources can enhance grid resilience, minimize transmission losses, and democratize energy markets. However, it becomes evident that to enable mass adoption; significant challenges must be addressed regarding renewable energy intermittency, scalability limitations, regulatory loopholes, and cybersecurity threats. Through synthesizing current research and the analytical case of Brooklyn Microgrid, this paper discusses some of the barriers and potential future directions that must be emphasized, such as hybrid optimization models, standardized frameworks, and inclusive design for accelerating transitions towards sustainable and equitable energy systems.

Keywords: Decentralized energy systems; Peer-to-peer energy trading; Artificial Intelligence; Blockchain; Multi-agent systems; Renewable energy; Smart grids