Coordinated clustering algorithms to support charging infrastructure design for electric vehicles

M. Momtazpour, P. Butler, M. S. Hossain, M. C. Bozchalui, Naren Ramakrishnan, Ratnesh K. Sharma
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引用次数: 35

Abstract

The confluence of several developments has created an opportune moment for energy system modernization. In the past decade, smart grids have attracted many research activities in different domains. To realize the next generation of smart grids, we must have a comprehensive understanding of interdependent networks and processes. Next-generation energy systems networks cannot be effectively designed, analyzed, and controlled in isolation from the social, economic, sensing, and control contexts in which they operate. In this paper, we develop coordinated clustering techniques to work with network models of urban environments to aid in placement of charging stations for an electrical vehicle deployment scenario. We demonstrate the multiple factors that can be simultaneously leveraged in our framework in order to achieve practical urban deployment. Our ultimate goal is to help realize sustainable energy system management in urban electrical infrastructure by modeling and analyzing networks of interactions between electric systems and urban populations.
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支持电动汽车充电基础设施设计的协同聚类算法
几种发展的汇合为能源系统现代化创造了一个有利的时机。在过去的十年中,智能电网吸引了许多不同领域的研究活动。为了实现下一代智能电网,我们必须对相互依赖的网络和过程有一个全面的了解。下一代能源系统网络不可能脱离其运行的社会、经济、传感和控制环境而进行有效的设计、分析和控制。在本文中,我们开发了协同聚类技术,与城市环境的网络模型一起工作,以帮助在电动汽车部署场景中放置充电站。我们展示了可以在我们的框架中同时利用的多种因素,以实现实际的城市部署。我们的最终目标是通过建模和分析电力系统与城市人口之间的相互作用网络,帮助实现城市电力基础设施的可持续能源系统管理。
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