A Testing Framework for Blockchain-Based Energy Trade Microgrids Applications
Distributed energy generation disrupts traditional energy markets by blurring the line between producers and consumers and enabling the emerging prosumers to trade energy in per-to-peer transactions. Blockchain technology automates peer-to-peer energy trades in a distributed database architecture th...
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10440275/ |
| _version_ | 1797289843538001920 |
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| author | Ameni Boumaiza Antonio Sanfilippo |
| author_facet | Ameni Boumaiza Antonio Sanfilippo |
| author_sort | Ameni Boumaiza |
| collection | DOAJ |
| description | Distributed energy generation disrupts traditional energy markets by blurring the line between producers and consumers and enabling the emerging prosumers to trade energy in per-to-peer transactions. Blockchain technology automates peer-to-peer energy trades in a distributed database architecture that achieves security and cost-effectiveness using cryptographic hashing and consensus-based verification. Before its deployment, an energy blockchain trading application needs to be tested in a virtual environment that is analogous to the real-world setting to ensure correct implementation and identify potential obstacles and opportunities. This study suggests executing such a testing within a framework that integrates a Geographic Information System (GIS) environment with an Agent-Based Modeling (ABM) simulation platform. The application of this testing framework to a case study of solar Photovoltaic (PV) energy trade among household peers in in Doha, Qatar, shows how the integration of the GIS environment offers a detailed analysis of transactions in local housing community markets. The ABM simulation reveals that population density, energy market prices, and household proximity significantly influence residential PV energy trading in Qatar. The ensuing simulation environment provides a decision-support platform for designing and implementing decentralized trading systems based on blockchain technology, and high-performance computing can enhance model performance for scalable energy blockchain analysis in Qatar and beyond. |
| first_indexed | 2024-03-07T19:11:52Z |
| format | Article |
| id | doaj.art-ff9e5f8bdfc1418fa3c0915c569f2e7a |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-07T19:11:52Z |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-ff9e5f8bdfc1418fa3c0915c569f2e7a2024-03-01T00:01:07ZengIEEEIEEE Access2169-35362024-01-0112274652748310.1109/ACCESS.2024.336799910440275A Testing Framework for Blockchain-Based Energy Trade Microgrids ApplicationsAmeni Boumaiza0https://orcid.org/0000-0002-8147-0076Antonio Sanfilippo1Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University, Ar-Rayyan, QatarQatar Environment and Energy Research Institute, Hamad Bin Khalifa University, Ar-Rayyan, QatarDistributed energy generation disrupts traditional energy markets by blurring the line between producers and consumers and enabling the emerging prosumers to trade energy in per-to-peer transactions. Blockchain technology automates peer-to-peer energy trades in a distributed database architecture that achieves security and cost-effectiveness using cryptographic hashing and consensus-based verification. Before its deployment, an energy blockchain trading application needs to be tested in a virtual environment that is analogous to the real-world setting to ensure correct implementation and identify potential obstacles and opportunities. This study suggests executing such a testing within a framework that integrates a Geographic Information System (GIS) environment with an Agent-Based Modeling (ABM) simulation platform. The application of this testing framework to a case study of solar Photovoltaic (PV) energy trade among household peers in in Doha, Qatar, shows how the integration of the GIS environment offers a detailed analysis of transactions in local housing community markets. The ABM simulation reveals that population density, energy market prices, and household proximity significantly influence residential PV energy trading in Qatar. The ensuing simulation environment provides a decision-support platform for designing and implementing decentralized trading systems based on blockchain technology, and high-performance computing can enhance model performance for scalable energy blockchain analysis in Qatar and beyond.https://ieeexplore.ieee.org/document/10440275/Spatial temporal accesssocial simulationpower gridartificial intelligencesolar energyblockchain technology |
| spellingShingle | Ameni Boumaiza Antonio Sanfilippo A Testing Framework for Blockchain-Based Energy Trade Microgrids Applications IEEE Access Spatial temporal access social simulation power grid artificial intelligence solar energy blockchain technology |
| title | A Testing Framework for Blockchain-Based Energy Trade Microgrids Applications |
| title_full | A Testing Framework for Blockchain-Based Energy Trade Microgrids Applications |
| title_fullStr | A Testing Framework for Blockchain-Based Energy Trade Microgrids Applications |
| title_full_unstemmed | A Testing Framework for Blockchain-Based Energy Trade Microgrids Applications |
| title_short | A Testing Framework for Blockchain-Based Energy Trade Microgrids Applications |
| title_sort | testing framework for blockchain based energy trade microgrids applications |
| topic | Spatial temporal access social simulation power grid artificial intelligence solar energy blockchain technology |
| url | https://ieeexplore.ieee.org/document/10440275/ |
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