FederatedGrids: Federated Learning and Blockchain-Assisted P2P Energy Sharing

被引:30
作者
Bouachir, Ouns [1 ]
Aloqaily, Moayad [2 ]
Ozkasap, Oznur [3 ]
Ali, Faizan [3 ]
机构
[1] Zayed Univ, Coll Technol Innovat, Dubai, U Arab Emirates
[2] Mohamed Bin Zayed Univ Artificial Intelligence, Machine Learning Dept, Abu Dhabi, U Arab Emirates
[3] Koc Univ, Dept Comp Engn, TR-34550 Istanbul, Turkey
来源
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING | 2022年 / 6卷 / 01期
关键词
Collaborative work; Costs; Production; Microgrids; Smart contracts; Load modeling; Privacy; P2P energy sharing; blockchain; federated learning; smart contracts; microgrids;
D O I
10.1109/TGCN.2022.3140978
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
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.
引用
收藏
页码:424 / 436
页数:13
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    Ali, Faizan Safdar
    Bouachir, Ouns
    Ozkasap, Oznur
    Aloqaily, Moayad
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2021, 17 (08) : 5769 - 5778
  • [2] Blockchain-assisted Decentralized Virtual Prosumer Grouping for P2P Energy Trading
    Ali, Faizan Safdar
    Aloqaily, Moayad
    Ozkasap, Oznur
    Bouachir, Ouns
    [J]. 2020 21ST IEEE INTERNATIONAL SYMPOSIUM ON A WORLD OF WIRELESS, MOBILE AND MULTIMEDIA NETWORKS (IEEE WOWMOM 2020), 2020, : 385 - 390
  • [3] Cyberphysical Blockchain-Enabled Peer-to-Peer Energy Trading
    Ali, Faizan Safdar
    Aloqaily, Moayad
    Alfandi, Omar
    Ozkasap, Oznur
    [J]. COMPUTER, 2020, 53 (09) : 56 - 65
  • [4] SynergyGrids: blockchain-supported distributed microgrid energy trading
    Aloqaily, Moayad
    Bouachir, Ouns
    Ozkasap, Oznur
    Ali, Faizan Safdar
    [J]. PEER-TO-PEER NETWORKING AND APPLICATIONS, 2022, 15 (02) : 884 - 900
  • [5] An Energy Trade Framework Using Smart Contracts: Overview and Challenges
    Aloqaily, Moayad
    Boukerche, Azzedine
    Bouachir, Ouns
    Khalid, Fariea
    Jangsher, Sobia
    [J]. IEEE NETWORK, 2020, 34 (04): : 119 - 125
  • [6] Energy Trading in Local Electricity Market With Renewables-A Contract Theoretic Approach
    Amin, Uzma
    Hossain, M. Jahangir
    Tushar, Wayes
    Mahmud, Khizir
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2021, 17 (06) : 3717 - 3730
  • [7] Deep Reinforcement Learning for Demand Response in Distribution Networks
    Bahrami, Shahab
    Chen, Yu Christine
    Wong, Vincent W. S.
    [J]. IEEE TRANSACTIONS ON SMART GRID, 2021, 12 (02) : 1496 - 1506
  • [8] IFed: A novel federated learning framework for local differential privacy in Power Internet of Things
    Cao, Hui
    Liu, Shubo
    Zhao, Renfang
    Xiong, Xingxing
    [J]. INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, 2020, 16 (05)
  • [9] Smart Meter Data to Optimize Combined Roof-Top Solar and Battery Systems Using a Stochastic Mixed Integer Programming Model
    Chatterji, Emon
    Bazilian, Morgan D.
    [J]. IEEE ACCESS, 2020, 8 : 133843 - 133853
  • [10] Electricity Cost-Sharing in Energy Communities Under Dynamic Pricing and Uncertainty
    Grzanic, Mirna
    Morales, Juan M.
    Pineda, Salvador
    Capuder, Tomislav
    [J]. IEEE ACCESS, 2021, 9 : 30225 - 30241