Network analysis in a peer-to-peer energy trading model using blockchain and machine learning

Existing technology like smart grid (SG) and smart meters play a significant role in meeting the everlasting demand of energy consumption, supply, and generation for peer-to-peer (P2P) energy trading between different distributed prosumers. Whereas blockchain when used with P2P energy trading plays...

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Main Authors: Shukla, S., Hussain, S., Irshad, R.R., Alattab, A.A., Thakur, S., Breslin, J.G., Hassan, M.F., Abimannan, S., Husain, S., Jameel, S.M.
Format: Article
Published: 2024
Online Access:http://scholars.utp.edu.my/id/eprint/38084/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175193267&doi=10.1016%2fj.csi.2023.103799&partnerID=40&md5=a357b85aa2d5df62df1aa640bcf1302f
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Institution: Universiti Teknologi Petronas
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spelling oai:scholars.utp.edu.my:380842023-12-11T03:17:08Z http://scholars.utp.edu.my/id/eprint/38084/ Network analysis in a peer-to-peer energy trading model using blockchain and machine learning Shukla, S. Hussain, S. Irshad, R.R. Alattab, A.A. Thakur, S. Breslin, J.G. Hassan, M.F. Abimannan, S. Husain, S. Jameel, S.M. Existing technology like smart grid (SG) and smart meters play a significant role in meeting the everlasting demand of energy consumption, supply, and generation for peer-to-peer (P2P) energy trading between different distributed prosumers. Whereas blockchain when used with P2P energy trading plays a major role in cost and security by eliminating any involvement of outsiders and third parties. However, existing works related to the blockchain with P2P energy trading are engaged in increasing the cost related to resource allocation, latency, computational processing, and large network setup. The objective of this paper is to design and develop a three-tier architecture, an analytical model, and a hybrid algorithm for network analysis in a blockchain-based P2P energy trading system using reinforcement learning (RL) and feed forward neural network (FFNN) techniques. In this model, we will examine the various parameters and tradeoffs which affect the delay, throughput, and security in P2P energy trading. This will lead to profitable P2P energy trading between different distributed prosumers. By analyzing the simulation results of the proposed model and algorithm by benchmarking with the existing state-of-the-art techniques it's clear that the proposed algorithm shows marked improvement over network latency generated results. The simulation of the model is conducted using the iFogSim simulator, Ganache with Ethereum platform, Truffle, Python editor tool, and ATOM IDE with solidity. © 2023 Elsevier B.V. 2024 Article NonPeerReviewed Shukla, S. and Hussain, S. and Irshad, R.R. and Alattab, A.A. and Thakur, S. and Breslin, J.G. and Hassan, M.F. and Abimannan, S. and Husain, S. and Jameel, S.M. (2024) Network analysis in a peer-to-peer energy trading model using blockchain and machine learning. Computer Standards and Interfaces, 88. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175193267&doi=10.1016%2fj.csi.2023.103799&partnerID=40&md5=a357b85aa2d5df62df1aa640bcf1302f 10.1016/j.csi.2023.103799 10.1016/j.csi.2023.103799 10.1016/j.csi.2023.103799
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description Existing technology like smart grid (SG) and smart meters play a significant role in meeting the everlasting demand of energy consumption, supply, and generation for peer-to-peer (P2P) energy trading between different distributed prosumers. Whereas blockchain when used with P2P energy trading plays a major role in cost and security by eliminating any involvement of outsiders and third parties. However, existing works related to the blockchain with P2P energy trading are engaged in increasing the cost related to resource allocation, latency, computational processing, and large network setup. The objective of this paper is to design and develop a three-tier architecture, an analytical model, and a hybrid algorithm for network analysis in a blockchain-based P2P energy trading system using reinforcement learning (RL) and feed forward neural network (FFNN) techniques. In this model, we will examine the various parameters and tradeoffs which affect the delay, throughput, and security in P2P energy trading. This will lead to profitable P2P energy trading between different distributed prosumers. By analyzing the simulation results of the proposed model and algorithm by benchmarking with the existing state-of-the-art techniques it's clear that the proposed algorithm shows marked improvement over network latency generated results. The simulation of the model is conducted using the iFogSim simulator, Ganache with Ethereum platform, Truffle, Python editor tool, and ATOM IDE with solidity. © 2023 Elsevier B.V.
format Article
author Shukla, S.
Hussain, S.
Irshad, R.R.
Alattab, A.A.
Thakur, S.
Breslin, J.G.
Hassan, M.F.
Abimannan, S.
Husain, S.
Jameel, S.M.
spellingShingle Shukla, S.
Hussain, S.
Irshad, R.R.
Alattab, A.A.
Thakur, S.
Breslin, J.G.
Hassan, M.F.
Abimannan, S.
Husain, S.
Jameel, S.M.
Network analysis in a peer-to-peer energy trading model using blockchain and machine learning
author_facet Shukla, S.
Hussain, S.
Irshad, R.R.
Alattab, A.A.
Thakur, S.
Breslin, J.G.
Hassan, M.F.
Abimannan, S.
Husain, S.
Jameel, S.M.
author_sort Shukla, S.
title Network analysis in a peer-to-peer energy trading model using blockchain and machine learning
title_short Network analysis in a peer-to-peer energy trading model using blockchain and machine learning
title_full Network analysis in a peer-to-peer energy trading model using blockchain and machine learning
title_fullStr Network analysis in a peer-to-peer energy trading model using blockchain and machine learning
title_full_unstemmed Network analysis in a peer-to-peer energy trading model using blockchain and machine learning
title_sort network analysis in a peer-to-peer energy trading model using blockchain and machine learning
publishDate 2024
url http://scholars.utp.edu.my/id/eprint/38084/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175193267&doi=10.1016%2fj.csi.2023.103799&partnerID=40&md5=a357b85aa2d5df62df1aa640bcf1302f
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