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    A dedicated consensus algorithm for improving performance of futuristic energy blockchain

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    Authors
    Yapa, Charithri
    De Alwis, Chamitha
    Wijewardhana, Uditha Lakmal
    Liyanage, Madhusanka
    Issue Date
    2024-02-28
    Subjects
    power line monitoring
    power quality
    consensus mechanism
    blockchain
    Smart Grid 2.0
    
    Metadata
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    Abstract
    Integrating renewable energy generation in the consumer end has transformed users acting as both buyers and sellers. Uncoordinated interconnections lead to degraded power quality, which demands for continuous network monitoring. This study evaluates the applicability of the network monitoring process to develop a novel consensus protocol, customized for blockchain platforms integrated with smart grids. The motivation for integrating grid monitoring with the blockchain consensus mechanism lies in the significance of decentralized architectures such as distributed ledger technologies for future energy grids. Existing blockchain consensus mechanisms have exhibited excessive energy usage and low scalability due to the additional workload associated. Hence, the study proposes a customised solution, which has the advantage of combining grid monitoring with the blockchain consensus protocol. This eliminates the additional computation burden, reduces the cost of execution, and improves the transaction throughput of the blockchain consensus mechanism.
    Citation
    Yapa C, De Alwis C, Wijewardhana U, Liyanage M (2024) 'A dedicated consensus algorithm for improving performance of futuristic energy blockchain', 2024 IEEE International Conference on Consumer Electronics (ICCE) - Las Vegas,, Institute of Electrical and Electronics Engineers Inc..
    Publisher
    Institute of Electrical and Electronics Engineers Inc.
    URI
    http://hdl.handle.net/10547/626869
    DOI
    10.1109/ICCE59016.2024.10444184
    Additional Links
    https://ieeexplore.ieee.org/document/10444184
    Type
    Conference papers, meetings and proceedings
    Language
    en
    ISBN
    9798350324136
    ae974a485f413a2113503eed53cd6c53
    10.1109/ICCE59016.2024.10444184
    Scopus Count
    Collections
    Computing

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