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首页> 外文期刊>IEEE systems journal >Cloud-Assisted Context-Aware Vehicular Cyber-Physical System for PHEVs in Smart Grid
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Cloud-Assisted Context-Aware Vehicular Cyber-Physical System for PHEVs in Smart Grid

机译:智能电网中PHEV的云辅助上下文感知车载网络物理系统

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摘要

Plug-in Hybrid Electric Vehicles (PHEVs) can be one of the cost-effective options of modern intelligent transportation systems in smart grid (SG) which can balance the demand and supply by temporarily storing the electrical energy in their batteries. In this paper, we propose a new context-aware layered architecture for demand side management using vehicular cyber-physical system (VCPS) with cloud support. We have used the concept of Bayesian coalition game and learning automata for an intelligent context-aware data collection and processing using a new payoff function for the players in the coalition game. In the proposed scheme, vehicles are assumed as the players which sense the SG environment during their mobility and collect information from it. The players in the game perform actions such as alert generation, and information dissemination. For each action, players receive a feedback from the environment according to which they update their action probability vector. The performance of the proposed scheme shows that there is a reduction in energy shortage by 30%, and information processing delay of 10%–15%. In addition, there is an increase of 15% in energy sold back to the grid using the proposed scheme. The results obtained demonstrate the effectiveness of the proposed scheme.
机译:插电式混合动力汽车(PHEV)可以成为智能电网(SG)中现代智能交通系统的一种经济高效的选择,该系统可以通过将电能临时存储在其电池中来平衡供需。在本文中,我们提出了一种新的上下文感知分层体系结构,用于使用带有云支持的车载网络物理系统(VCPS)进行需求侧管理。我们使用贝叶斯联盟游戏的概念和学习自动机来进行智能情境感知数据收集和处理,并为联盟游戏中的玩家使用了新的收益功能。在提出的方案中,假定车辆是在移动过程中感知SG环境并从中收集信息的参与者。游戏中的玩家执行警报生成和信息传播等动作。对于每个动作,玩家都会收到来自环境的反馈,据此他们会更新其动作概率向量。拟议方案的性能表明,能源短缺减少了30%,信息处理延迟减少了10%-15%。此外,使用提议的方案,回输给电网的能源增加了15%。获得的结果证明了该方案的有效性。

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