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Stochastic synergies of urban transportation system and smart grid in smart cities considering V2G and V2S concepts

机译:考虑V2G和V2S概念的智能城市中城市交通系统与智能电网的随机协同作用

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Serious challenges such as rapid growth in population, environmental pollution, and possibility of energy shortage have motivated researchers for designing optimal energy operation strategies through the concept of smart city. Buildings and electric transport systems, especially subway systems and Plug in Electric Vehicles (PEVs), are among the major energy consumption systems in a smart city. In this paper, a linear model is proposed for the co-optimization planning and operation of distributed energy resources and transportation systems in an interconnected system that analyzes the interactions of such an interconnected system. The idea of Regenerative Breaking Energy (RBE) is deployed to improve the operation of the subway system through the interconnected subway system in the smart city. For the optimal operation of the smart city, an optimization formulation is devised to minimize the total cost of the city in the presence of subway RBE. In this paper, the traffic and length of the routes are modeled considering Vehicle to Grid (V2G) and Vehicle to Subway (V2S) located in the parking lots. Furthermore, the degradation model is developed to increase the PEVs' battery life. An unscented transformation (UT) approach is utilized to construct a stochastic framework based on the uncertainty method, to handle the uncertain behaviors of PEVs and distributed energy resource and loads in the smart city. Finally, the proposed model is implemented and its performance is analyzed in both the stochastic and deterministic frameworks.
机译:人口,环境污染和能源短缺的迅速增长的严重挑战具有通过智能城市的概念设计最佳能源运行策略的研究人员。建筑物和电动运输系统,尤其是地铁系统和插入电动车辆(PEV),是智能城市的主要能耗系统之一。本文提出了一种线性模型,用于在互连系统中的分布能源和运输系统的共同优化规划和运行,分析这种互连系统的相互作用。部署了再生断裂能量(RBE)的思想,以通过智能城市的互联地铁系统改善地铁系统的运行。为了智能城市的最佳运行,设计优化配方,以最大限度地减少地铁rbe存在的城市的总成本。在本文中,将路线的流量和长度考虑到网格(V2G)和位于停车场中的地铁(V2S)的车辆。此外,开发了降解模型以增加PEV的电池寿命。利用未控制的变换(UT)方法来构建基于不确定性方法的随机框架,以处理PEV的不确定行为和智能城市的分布能源和负载。最后,实现了所提出的模型,并在随机和确定性框架中分析其性能。

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