Abstract
The advancement in renewable energy sources (RESs) technology have changed the role of traditional consumers to prosumers. In contrast to the traditional power grid, the Smart Grid (SG) network provides a platform for peer-to-peer (P2P) energy trading between prosumers to buy or sell energy according to their requirements. The potential benefits of P2P energy trading can be realized through an efficient service provider of the communication network infrastructure. However, the current communication network is a trustless environment and thereby is unable to fully support the P2P energy trading requirements. Existing techniques in P2P energy trading with blockchain suffers from large network delay due to large network size; this further affects the network performance for P2P trading. In this paper, we present a novel Blockchain-Based Smart Energy Trading (BSET) algorithm along with a Blockchain-Enabled Fog Computing Model (BFCM) for P2P energy trading in Smart Grid. The proposed BSET algorithm provides a fully trusted minimum latency communication network that enables the prosumers to trade energy within their local premises. The algorithm was implemented using iFogSim, Truffle, ATOM, Anaconda, and Geth and evaluated against state-of-the-art communication network models for P2P energy trading. The simulation results revealed the effectiveness in terms of secure trading and network latency.
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Acknowledgements
This publication has emanated from research supported in part by a research grant from Cooperative Energy Trading System (CENTS) under Grant Number REI1633, and by a research grant from Science Foundation Ireland (SFI) under Grant Number SFI 12/RC/2289_P2 (Insight), co-funded by the European Regional Development Fund.
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Shukla, S., Thakur, S., Hussain, S., Breslin, J.G. (2022). A Blockchain-Enabled Fog Computing Model for Peer-To-Peer Energy Trading in Smart Grid. In: Prieto, J., Partida, A., Leitão, P., Pinto, A. (eds) Blockchain and Applications. BLOCKCHAIN 2021. Lecture Notes in Networks and Systems, vol 320. Springer, Cham. https://doi.org/10.1007/978-3-030-86162-9_2
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DOI: https://doi.org/10.1007/978-3-030-86162-9_2
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