DOI:10.35833/MPCE.2020.000136 |
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Multi-commodity Optimization of Peer-to-peer Energy Trading Resources in Smart Grid |
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Page view: 207
Net amount: 630 |
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Author:
Olamide Jogunola1,Bamidele Adebisi1,Kelvin Anoh2,Augustine Ikpehai3,Mohammad Hammoudeh4,Georgina Harris5
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Author Affiliation:
1.Manchester Metropolitan University, Manchester, UK;2.Department of Electrical and Electronic Engineering, University of Bolton, Bolton, UK;3.Department of Engineering and Mathematics, Sheffield Hallam University, Sheffield, UK;4.Department of Computing and Mathematics, Manchester Metropolitan University, Manchester, UK;5.School of Science, Engineering and Environment, University of Salford, Salford, UK
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Foundation: |
This work was supported in part by the Peer-to-peer Energy Trading and Sharing-3M (multi-times, multi-scales, multi-qualities) project funded by EPSRC (No. EP/N03466X/1) and in part, by ENERGY-IQ, a UK-Canada Power Forward Smart Grid Demonstrator project funded by The Department for Business, Energy and Industrial Strategy (BEIS) (No. 7454460). |
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Abstract: |
Utility maximization is a major priority of prosumers participating in peer-to-peer energy trading and sharing (P2P-ETS). However, as more distributed energy resources integrate into the distribution network, the impact of the communication link becomes significant. We present a multi-commodity formulation that allows the dual-optimization of energy and communication resources in P2P-ETS. On one hand, the proposed algorithm minimizes the cost of energy generation and communication delay. On the other hand, it also maximizes the global utility of prosumers with fair resource allocation. We evaluate the algorithm in a variety of realistic conditions including a time-varying communication network with signal delay signal loss. The results show that the convergence is achieved in a fewer number of time steps than the previously proposed algorithms. It is further observed that the entities with a higher willingness to trade the energy acquire more satisfactions than others. |
Keywords: |
Distributed algorithm ; social welfare ; peer-to-peer energy trading and sharing ; multi-commodity networks ; economic dispatch ; packet loss ; peer-to-peer energy trading ; distributed dual-gradient (DDG). |
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Received:March 05, 2020
Online Time:2022/01/28 |
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