Al-Shehari Taher, Kadrie Mohammed, Alfakih Taha, Alsalman Hussain, Kuntavai T, Vidhya R G, Dhanamjayulu C, Shukla Shubhi, Khan Baseem
Computer Skills, Department of Self-Development Skill, Common First Year Deanship, King Saud University, 11362, Riyadh, Saudi Arabia.
Department of Information Systems, College of Computer and Information Sciences, King Saud University, 11543, Riyadh, Saudi Arabia.
Sci Rep. 2024 Aug 19;14(1):19208. doi: 10.1038/s41598-024-69542-w.
The rise of Electric Vehicles (EVs) has introduced significant advancement and evolution in the electricity market. In smart transportation, the EVs have earned more popularity because of its numerous benefits including lower carbon footprints, higher performance, and sophisticated energy trading mechanisms. These potential benefits have resulted in widespread EV adoption across the world. Despite its benefits, energy management remains the biggest challenge in EVs and it is mainly because of the lack of Charging Stations (CSs) near EVs. This creates a demand for an effective, secure and reliable energy management framework for EVs. This study presents a secure data and energy trade paradigm based on Blockchain (BC) in the Internet of EVs (IoEV). BC technology prepares for the high volume of EV integration that serves as the foundation for the next generation, and to assist in developing unique privacy-protected BC-based D-Trading and storage Models. Entities evaluated for the proposed model include Trusted Authority (TA), Vehicles, Smart Meters, Roadside Units (RSU), BC, and Inter-Planetary File System (IPFS). In addition, E-trading involves several phases, including the acquiring E-trading demand requests, E-trading response requests, request matching and token assignment. Moreover, account mapping is performed using a Mayfly Pelican Optimization Algorithm (MPOA), which is created by merging the Mayfly Algorithm (MA) and Pelican Optimization Algorithm (POA). Various security features are used to protect data and energy trade in IoEV, including encryption, hashing, polynomials, and others. The testing results revealed that the MPOA outperformed the state-of-the-art results regarding memory consumption, trading rate, transaction cost, and trading energy volume with values of 4.605 MB, 91%, 0.654, and 90 kW, respectively.
电动汽车(EV)的兴起给电力市场带来了重大进步和变革。在智能交通领域,电动汽车因其诸多优势而更受欢迎,这些优势包括更低的碳足迹、更高的性能以及先进的能源交易机制。这些潜在优势促使电动汽车在全球范围内广泛普及。尽管电动汽车有诸多好处,但能源管理仍是其面临的最大挑战,主要原因是电动汽车附近缺乏充电站。这就催生了对一种有效、安全且可靠的电动汽车能源管理框架的需求。本研究提出了一种基于区块链(BC)的安全数据和能源交易范式,应用于电动汽车物联网(IoEV)。区块链技术为大量电动汽车的集成做好准备,这是下一代技术的基础,并有助于开发独特的基于区块链的隐私保护D交易和存储模型。针对所提出模型评估的实体包括可信机构(TA)、车辆、智能电表、路边单元(RSU)、区块链和星际文件系统(IPFS)。此外,电子交易涉及多个阶段,包括获取电子交易需求请求、电子交易响应请求、请求匹配和令牌分配。而且,账户映射使用蜉蝣鹈鹕优化算法(MPOA)来执行,该算法是通过合并蜉蝣算法(MA)和鹈鹕优化算法(POA)创建的。各种安全特性被用于保护IoEV中的数据和能源交易,包括加密、哈希、多项式等。测试结果表明,在内存消耗、交易率、交易成本和交易能量量方面,MPOA的表现优于现有技术结果,其值分别为4.605MB、91%、0.654和90kW。