Proof of Inherent Intelligence Consensus Mechanism Empowering Blockchain-Enabled Transactive Energy
An evolving energy system with a dispersed infrastructure may not be compatible with traditional centralized optimization and management techniques. Blockchain, a peer-to-peer immutable distributed ledger technology, has the potential to significantly contribute to the management of emerging trends...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10820186/ |
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| author | Imran Hussain Hafiz Ashiq Hussain Nasim Ullah Stanislav Misak |
| author_facet | Imran Hussain Hafiz Ashiq Hussain Nasim Ullah Stanislav Misak |
| author_sort | Imran Hussain |
| collection | DOAJ |
| description | An evolving energy system with a dispersed infrastructure may not be compatible with traditional centralized optimization and management techniques. Blockchain, a peer-to-peer immutable distributed ledger technology, has the potential to significantly contribute to the management of emerging trends of decentralized power networks. However, complex optimization problems associated with the decentralized power grid are poorly integrated into the existing blockchain applications. Here, we suggest Proof of Inherent Intelligence (PoII), a novel prosumer-centric consensus mechanism designed to assist multi-interest party optimization challenges of the distributed power grid. We demonstrate PoII’s operation and performance with comprehensive mathematical modeling of energy pool-market trading and scheduling optimization problems. The efficiency of the proposed framework is evaluated against the existing blockchain applications for peer-to-peer energy transactions in terms of latency, throughput, tolerance against adversaries, vulnerability, and optimization capabilities. A thorough case study of the power grid that includes thermal, wind, and intermittent generation sources is presented to assess the effectiveness of the proposed consensus mechanism. Power demand, reserves, trading, and scheduling scenarios in both the day-ahead and balancing markets are among the peer-to-peer energy transactional elements that are assessed to support the efficacy of the suggested consensus approach. |
| format | Article |
| id | doaj-art-38ae6b7191c34d84b5fd67ac31cd5aef |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-38ae6b7191c34d84b5fd67ac31cd5aef2025-01-14T00:02:25ZengIEEEIEEE Access2169-35362025-01-01135042505510.1109/ACCESS.2024.352541610820186Proof of Inherent Intelligence Consensus Mechanism Empowering Blockchain-Enabled Transactive EnergyImran Hussain0https://orcid.org/0000-0002-4369-7149Hafiz Ashiq Hussain1https://orcid.org/0000-0002-2728-1098Nasim Ullah2https://orcid.org/0000-0001-5536-3560Stanislav Misak3https://orcid.org/0000-0002-7344-6930Department of Electrical and Computer Engineering, Air University, Islamabad, PakistanDepartment of Electrical and Computer Engineering, Air University, Islamabad, PakistanDepartment of Electrical Engineering, College of Engineering, Taif University, Taif, Saudi ArabiaENET Center, VSB-Technical University of Ostrava, Ostrava, Czech RepublicAn evolving energy system with a dispersed infrastructure may not be compatible with traditional centralized optimization and management techniques. Blockchain, a peer-to-peer immutable distributed ledger technology, has the potential to significantly contribute to the management of emerging trends of decentralized power networks. However, complex optimization problems associated with the decentralized power grid are poorly integrated into the existing blockchain applications. Here, we suggest Proof of Inherent Intelligence (PoII), a novel prosumer-centric consensus mechanism designed to assist multi-interest party optimization challenges of the distributed power grid. We demonstrate PoII’s operation and performance with comprehensive mathematical modeling of energy pool-market trading and scheduling optimization problems. The efficiency of the proposed framework is evaluated against the existing blockchain applications for peer-to-peer energy transactions in terms of latency, throughput, tolerance against adversaries, vulnerability, and optimization capabilities. A thorough case study of the power grid that includes thermal, wind, and intermittent generation sources is presented to assess the effectiveness of the proposed consensus mechanism. Power demand, reserves, trading, and scheduling scenarios in both the day-ahead and balancing markets are among the peer-to-peer energy transactional elements that are assessed to support the efficacy of the suggested consensus approach.https://ieeexplore.ieee.org/document/10820186/Distributed energy resourcesenergy schedulingenergy tradingpower networksmart contractsmart grid |
| spellingShingle | Imran Hussain Hafiz Ashiq Hussain Nasim Ullah Stanislav Misak Proof of Inherent Intelligence Consensus Mechanism Empowering Blockchain-Enabled Transactive Energy IEEE Access Distributed energy resources energy scheduling energy trading power network smart contract smart grid |
| title | Proof of Inherent Intelligence Consensus Mechanism Empowering Blockchain-Enabled Transactive Energy |
| title_full | Proof of Inherent Intelligence Consensus Mechanism Empowering Blockchain-Enabled Transactive Energy |
| title_fullStr | Proof of Inherent Intelligence Consensus Mechanism Empowering Blockchain-Enabled Transactive Energy |
| title_full_unstemmed | Proof of Inherent Intelligence Consensus Mechanism Empowering Blockchain-Enabled Transactive Energy |
| title_short | Proof of Inherent Intelligence Consensus Mechanism Empowering Blockchain-Enabled Transactive Energy |
| title_sort | proof of inherent intelligence consensus mechanism empowering blockchain enabled transactive energy |
| topic | Distributed energy resources energy scheduling energy trading power network smart contract smart grid |
| url | https://ieeexplore.ieee.org/document/10820186/ |
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