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Bi-Directional Mutual Energy Trade between Smart Grid and Energy Districts Using Renewable Energy Credits
A central authority, in a conventional centralized energy trading market, superintends energy and financial transactions. The central authority manages and controls transparent energy trading between producer and consumer, imposes a penalty in case of contract violation, and disburses numerous rewar...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8124214/ https://www.ncbi.nlm.nih.gov/pubmed/33946631 http://dx.doi.org/10.3390/s21093088 |
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author | Rehman, Sana Khan, Bilal Arif, Jawad Ullah, Zahid Aljuhani, Abdullah J. Alhindi, Ahmad Ali, Sahibzada M. |
author_facet | Rehman, Sana Khan, Bilal Arif, Jawad Ullah, Zahid Aljuhani, Abdullah J. Alhindi, Ahmad Ali, Sahibzada M. |
author_sort | Rehman, Sana |
collection | PubMed |
description | A central authority, in a conventional centralized energy trading market, superintends energy and financial transactions. The central authority manages and controls transparent energy trading between producer and consumer, imposes a penalty in case of contract violation, and disburses numerous rewards. However, the management and control through the third party pose a significant threat to the security and privacy of consumers’/producers’ (participants) profiles. The energy transactions between participants involving central authority utilize users’ time, money, and impose a computational burden over the central controlling authority. The Blockchain-based decentralized energy transaction concept, bypassing the central authority, is proposed in Smart Grid (SG) by researchers. Blockchain technology braces the concept of Peer-to-Peer (P2P) energy transactions. This work encompasses the SolarCoin-based digital currency blockchain model for SG incorporating RE. Energy transactions from Prosumer (P) to Prosumer, Energy District to Energy District, and Energy District to SG are thoroughly investigated and analyzed in this work. A robust demand-side optimized model is proposed using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to maximize Prosumer Energy Surplus (PES), Grid revenue (GR), percentage energy transactions accomplished, and decreased Prosumer Energy Cost (PEC). Real-time averaged energy data of Australia are employed, and a piece-wise energy price mechanism is implemented in this work. The graphical analysis and tabular statistics manifest the efficacy of the proposed model. |
format | Online Article Text |
id | pubmed-8124214 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-81242142021-05-17 Bi-Directional Mutual Energy Trade between Smart Grid and Energy Districts Using Renewable Energy Credits Rehman, Sana Khan, Bilal Arif, Jawad Ullah, Zahid Aljuhani, Abdullah J. Alhindi, Ahmad Ali, Sahibzada M. Sensors (Basel) Article A central authority, in a conventional centralized energy trading market, superintends energy and financial transactions. The central authority manages and controls transparent energy trading between producer and consumer, imposes a penalty in case of contract violation, and disburses numerous rewards. However, the management and control through the third party pose a significant threat to the security and privacy of consumers’/producers’ (participants) profiles. The energy transactions between participants involving central authority utilize users’ time, money, and impose a computational burden over the central controlling authority. The Blockchain-based decentralized energy transaction concept, bypassing the central authority, is proposed in Smart Grid (SG) by researchers. Blockchain technology braces the concept of Peer-to-Peer (P2P) energy transactions. This work encompasses the SolarCoin-based digital currency blockchain model for SG incorporating RE. Energy transactions from Prosumer (P) to Prosumer, Energy District to Energy District, and Energy District to SG are thoroughly investigated and analyzed in this work. A robust demand-side optimized model is proposed using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to maximize Prosumer Energy Surplus (PES), Grid revenue (GR), percentage energy transactions accomplished, and decreased Prosumer Energy Cost (PEC). Real-time averaged energy data of Australia are employed, and a piece-wise energy price mechanism is implemented in this work. The graphical analysis and tabular statistics manifest the efficacy of the proposed model. MDPI 2021-04-29 /pmc/articles/PMC8124214/ /pubmed/33946631 http://dx.doi.org/10.3390/s21093088 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Rehman, Sana Khan, Bilal Arif, Jawad Ullah, Zahid Aljuhani, Abdullah J. Alhindi, Ahmad Ali, Sahibzada M. Bi-Directional Mutual Energy Trade between Smart Grid and Energy Districts Using Renewable Energy Credits |
title | Bi-Directional Mutual Energy Trade between Smart Grid and Energy Districts Using Renewable Energy Credits |
title_full | Bi-Directional Mutual Energy Trade between Smart Grid and Energy Districts Using Renewable Energy Credits |
title_fullStr | Bi-Directional Mutual Energy Trade between Smart Grid and Energy Districts Using Renewable Energy Credits |
title_full_unstemmed | Bi-Directional Mutual Energy Trade between Smart Grid and Energy Districts Using Renewable Energy Credits |
title_short | Bi-Directional Mutual Energy Trade between Smart Grid and Energy Districts Using Renewable Energy Credits |
title_sort | bi-directional mutual energy trade between smart grid and energy districts using renewable energy credits |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8124214/ https://www.ncbi.nlm.nih.gov/pubmed/33946631 http://dx.doi.org/10.3390/s21093088 |
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