【Author】
Bouachir, Ouns; Aloqaily, Moayad; Ozkasap, Oznur; Ali, Faizan
【Source】IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING
【Abstract】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.
【Keywords】Collaborative work; Costs; Production; Microgrids; Smart contracts; Load modeling; Privacy; P2P energy sharing; blockchain; federated learning; smart contracts; microgrids
【标题】FederatedGrids：联邦学习和区块链辅助的 P2P 能源共享
【摘要】点对点 (P2P) 能源交易平台设想能源部门来满足日益增长的能源需求。本文的愿景不仅是进行能源交易，还包括共享能源的一部分。因此，本文介绍了 FederatedGrids，它是一个在微电网内部和跨微电网的 P2P 能源交易和共享平台。能源共享允许在不同类别的消费者和产消者之间交换能源，以换取未来的利益。 FederatedGrids 平台使用区块链和联邦学习来实现自主活动，同时在所有参与者之间提供信任和隐私。事实上，基于使用联邦学习的各种智能合约，FederatedGrids 计算出对未来能源生产和需求的预测，从而使系统能够在交易和共享之间自主切换，并使产消者能够做出与其参与能源共享过程相关的决策。据我们所知，这项工作是首次尝试创建具有真正共享意义的混合能源交易和共享平台，并使用联邦学习而不是智能合约进行能源需求预测。实验结果表明，消费者的能源成本降低了 17.8%，公用电网的负载降低了 76.4%。
【关键词】协作工作；费用；生产;微电网；智能合约；负载建模；隐私; P2P能源共享；区块链；联邦学习；智能合约；微电网
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