EAGER: Integrated Planning and Operation of Electricity-Transportation Networks for Wireless Electric Vehicle Charging

EAGER：电动汽车无线充电的电力交通网络综合规划和运营

• 批准号: 1550448
• 负责人: Mohammad Khodayar
• 金额: $ 15.49万
• 依托单位: Southern Methodist University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1550448&HistoricalAwards=false
• 关键词: EAGER; Integrated; Planning; Operation; Electricity

Several cutting-edge technologies are expected to fundamentally change the way engineers would plan, design and operate the highway infrastructure system. Among these technologies are electric vehicles with in-motion wireless charging capabilities. Unlike the widely available plug-in electric vehicles, the new technology enables vehicles to charge wirelessly while traveling via charging pads installed along the highway links. This emerging technology is expected to increase the travel range of the electric vehicles, and hence improve its social acceptance, which ultimately leads to reducing dependence on conventional fuel resources for transportation. This EArly-concept Grant for Exploratory Research (EAGER) project is motivated by the need to develop an integrated framework for policy making, planning and operation management of wireless charging technology in urban transportation networks. This framework addresses several conceptual and methodological complexities inherited in the interconnected transportation-electricity infrastructure systems, and provides necessary tools to design and operate such complex infrastructure systems. The successful completion of this EAGER is expected to advance the development of sustainable transportation infrastructure systems characterized by reduced greenhouse gas generation and improved urban mobility. The interdisciplinary research involves the collaboration of expertise in the areas of planning and operation of electrical power networks, transportation network modeling and traffic operation management, and operations research and system engineering. The collaborative environment leads to rapid dissemination of knowledge and discovery results to the research and education community, and stimulates educational development in sustainable transportation.The framework incorporates mathematical formulations and cutting-edge solution methodologies representing the mutual interactions between policy making efforts to promote electric vehicle technology, and market-driven coordinated expansion planning and network design in the hybrid electricity and transportation infrastructure systems. The market-driven structure is presented by complementarity models with non-convex feasible set that capture the demand elasticity and policy-driven incentives. The competition in electricity and transportation network operation is presented by hierarchical oligopoly structure coupling equilibrium problems with equilibrium constraints. Each problem represents non-cooperative multi-leader-follower game with incomplete information to model the strategic behavior of the participants. The effectiveness of the solutions are validated through developing a high-resolution agent-based simulation platform which represents the integrated operation of the traffic and electricity networks considering multiple scenarios representing the uncertainty in the operation environment.

几项尖端技术预计将从根本上改变工程师规划、设计和运营高速公路基础设施系统的方式。这些技术包括具有动态无线充电功能的电动汽车。与广泛使用的插电式电动汽车不同，这项新技术使车辆在行驶时可以通过安装在高速路上的充电板进行无线充电。这项新兴技术预计将增加电动汽车的行驶里程，从而提高其社会接受度，最终导致减少对传统燃料资源的运输依赖。这一早期概念探索性研究资助(AGER)项目的动机是需要为城市交通网络中无线充电技术的政策制定、规划和运营管理制定一个综合框架。这一框架解决了相互关联的交通-电力基础设施系统中继承的几个概念和方法上的复杂性，并为设计和运营这种复杂的基础设施系统提供了必要的工具。这一项目的成功完成预计将推动可持续交通基础设施系统的发展，其特点是减少温室气体的产生和改善城市机动性。跨学科研究涉及电力网络规划和运营、交通网络建模和交通运营管理、运营研究和系统工程等领域的专业知识协作。协作环境导致知识和发现成果迅速传播到研究和教育界，并刺激可持续交通领域的教育发展。框架包含数学公式和尖端解决方案方法，代表了混合动力电力和交通基础设施系统中促进电动汽车技术的政策制定努力与市场驱动的协调扩展规划和网络设计之间的相互作用。市场驱动结构由具有非凸可行集的互补模型来描述，该模型捕捉了需求弹性和政策驱动的激励。电力运输网络运营中的竞争问题表现为具有均衡约束的层次型寡头垄断结构。每个问题都是不完全信息的非合作多领导者-追随者博弈，用来模拟参与者的策略行为。通过开发一个高分辨率的基于智能体的仿真平台来验证解决方案的有效性，该平台考虑了代表运行环境中的不确定性的多个场景，代表了交通和电力网络的综合运行。