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<p>Vehicle-to-vehicle (V2V) energy trading has grown as a promising approach to alleviate grid load without intermediaries. Blockchain technology is widely recognized as the most feasible solution to address security and privacy concerns in the Internet of Electric Vehicles (IoEV). The IoEV energy trading involves Electric Vehicles (EVs) supplying energy to other vehicles, grids, communities, and buildings. There is a critical need for a scalable, efficient, secure, and cost-effective scheme to facilitate IoEV energy trading transactions. IoEV-based energy trading plays an essential role in reducing demand-response loads during peak hours, all without requiring additional storage or production resources. Thus, this research introduced a novel secure data and Energy Trading (E-Trading) model based on Blockchain in the Internet of EVs (IoEV). In IoEV, the data is preserved using several security measures, like encryption, a hashing function, and polynomials. Also, the Trusted Authority (TA), Vehicles, SmartMeters, Roadside Units (RSU), Blockchain, and Inter-Planetary File System (IPFS) are the entities associated with the proposed model. Moreover, the high volume of EV integration is done by blockchain technology and this helps in visualizing the next generation as it helps develop novel privacy-protected Blockchain-based Data Trading (D-Trading) and storage Model. Here, the two scenarios namely D-trading and E-trading are considered, where the D-trading acts as a relational and reliable platform for data and resources, and the E-trading trends screening to preserve the privacy of EVs. Here, the proposed Coot-based Honey Badger Algorithm (CHBA) is used for account mapping and it is generated by the integration of Coot Algorithm (CA) and Honey Badger Algorithm (HBA). Moreover, the proposed CHBA method is assessed by various performance metrics, such as trading rate, trading energy volume, Transaction cost, Execution cost, and Memory usage and obtained a maximum trading rate of 88.022%, a maximum trading energy volume of 84.483&#xa0;kW, a minimum Transaction cost of 0.661, a minimum Execution cost of 0.727 and a minimum Memory usage of 4.744&#xa0;MB.</p>

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Blockchain-based secure data communication with an optimal energy trading model in the IoEV system

  • 期刊论文

  • 发表日期：

    2025年4月10日

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  • Muthuvinayagam M,
  • M. Belsam Jeba Ananth,
  • Agalya V

摘要

Vehicle-to-vehicle (V2V) energy trading has grown as a promising approach to alleviate grid load without intermediaries. Blockchain technology is widely recognized as the most feasible solution to address security and privacy concerns in the Internet of Electric Vehicles (IoEV). The IoEV energy trading involves Electric Vehicles (EVs) supplying energy to other vehicles, grids, communities, and buildings. There is a critical need for a scalable, efficient, secure, and cost-effective scheme to facilitate IoEV energy trading transactions. IoEV-based energy trading plays an essential role in reducing demand-response loads during peak hours, all without requiring additional storage or production resources. Thus, this research introduced a novel secure data and Energy Trading (E-Trading) model based on Blockchain in the Internet of EVs (IoEV). In IoEV, the data is preserved using several security measures, like encryption, a hashing function, and polynomials. Also, the Trusted Authority (TA), Vehicles, SmartMeters, Roadside Units (RSU), Blockchain, and Inter-Planetary File System (IPFS) are the entities associated with the proposed model. Moreover, the high volume of EV integration is done by blockchain technology and this helps in visualizing the next generation as it helps develop novel privacy-protected Blockchain-based Data Trading (D-Trading) and storage Model. Here, the two scenarios namely D-trading and E-trading are considered, where the D-trading acts as a relational and reliable platform for data and resources, and the E-trading trends screening to preserve the privacy of EVs. Here, the proposed Coot-based Honey Badger Algorithm (CHBA) is used for account mapping and it is generated by the integration of Coot Algorithm (CA) and Honey Badger Algorithm (HBA). Moreover, the proposed CHBA method is assessed by various performance metrics, such as trading rate, trading energy volume, Transaction cost, Execution cost, and Memory usage and obtained a maximum trading rate of 88.022%, a maximum trading energy volume of 84.483 kW, a minimum Transaction cost of 0.661, a minimum Execution cost of 0.727 and a minimum Memory usage of 4.744 MB.