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Decentralized Energy Marketplace via NFTs and AI-based Agents

Authors: Nikbakht R.; Javed F.; Rezazadeh F.; Bartzoudis N.; Mangues-Bafalluy J.;

Decentralized Energy Marketplace via NFTs and AI-based Agents

Abstract

The paper introduces an advanced Decentralized Energy Marketplace (DEM) integrating blockchain technology and artificial intelligence to manage energy exchanges among smart homes with energy storage systems. The proposed framework uses Non-Fungible Tokens (NFTs) to represent unique energy profiles in a transparent and secure trading environment. Leveraging Federated Deep Reinforcement Learning (FDRL), the system promotes collaborative and adaptive energy management strategies, maintaining user privacy. A notable innovation is the use of smart contracts, ensuring high efficiency and integrity in energy transactions. Extensive evaluations demonstrate the system's scalability and the effectiveness of the FDRL method in optimizing energy distribution. This research significantly contributes to developing sophisticated decentralized smart grid infrastructures. Our approach broadens potential blockchain and AI applications in sustainable energy systems and addresses incentive alignment and transparency challenges in traditional energy trading mechanisms. The implementation of this paper is publicly accessible at \url{https://github.com/RasoulNik/DEM}.

6 pages

Keywords

FOS: Computer and information sciences, Computer Science - Machine Learning, Smart contract, Reinforcement learnings, Machine Learning (cs.LG), Computer Science - Networking and Internet Architecture, Automation, Intelligent buildings, Blockchain, Smart power grids, Reinforcement learning, Energy profile, Management strategies, Networking and Internet Architecture (cs.NI), Energy exchanges, Smart homes, Energy management, Deep learning, Block-chain, Energy efficiency, Energy management systems, Power markets, User privacy, Decentralized energy, Trading environments, Storage systems

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
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Energy Research