FederatedGrids: Federated Learning and Blockchain-assisted P2P Energy Sharing

Document Type


Source of Publication

IEEE Transactions on Green Communications and Networking

Publication Date



Peer-to-Peer (P2P) energy trading platforms envisioned energy sectors to satisfy the increasing demand for energy. The vision of this paper is not only to trade energy but also to have part of it being shared. Therefore, this paper presents FederatedGrids which is a P2P energy trading and sharing platform inside and across microgrids. Energy sharing allows exchanging energy between the categories of consumers and prosumers in return for future benefits. FederatedGrids platform uses blockchain and federated learning to enable autonomous activities while providing trust and privacy among all participants. Indeed, based on various smart contracts using federated learning, FederatedGrids calculates a prediction of the future energy production and demand allowing the system to autonomously switch between trading and sharing, and enabling the prosumers to make decisions related to their participation in the energy sharing process. Up to our knowledge, this work is the first attempt to create a hybrid energy trading and sharing platform, with the real sharing meaning, and that uses federated learning over the smart contract for energy demand prediction. The experimental results showed a 17.8% decrease in energy cost for consumers and a 76.4% decrease in load over utility grids.




Institute of Electrical and Electronics Engineers (IEEE)


Computer Sciences


Blockchain, Collaborative work, Costs, Federated Learning, Load modeling, Microgrids, Microgrids., P2P Energy Sharing, Privacy, Production, Smart contracts, Smart Contracts

Scopus ID


Indexed in Scopus


Open Access