Performance Guarantees for Electric Vehicle Fast Charging Station Management

电动汽车快速充电站管理的绩效保证

• 批准号: 2312196
• 负责人: Jiangfeng Zhang
• 金额: $ 69.9万
• 依托单位: Clemson University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2312196&HistoricalAwards=false
• 关键词: Performance; Guarantees; Electric; Vehicle; Fast

This grant will fund research that enables the development of effective solutions for the management of electric vehicle charging stations that reduce operating costs, shorten queuing time, and lessen battery degradation, thereby promoting the progress of science and advancing national prosperity. Existing fast charging station management solutions are based on conservatively forecasted charging demand and do not leverage power control optimization for vehicle charging. Given typical constraints on the availability of grid-supplied power, conventional charging solutions may result in undesirable performance, including longer charging/queuing times and faster battery degradation. Such outcomes are expected to be exacerbated as projected increases in the charging needs of battery and hybrid electric vehicles, in terms of both number and diversity, significant spatial and temporal variability at geographically distributed charging stations, and intermittency of renewable power resources impose significant stresses on the electric power grid. This project will address these challenges by applying dynamic systems, control, and optimization techniques to derive new charging station management solutions that guarantee performance in terms of reduced charging time under limited power supplies, increased battery life and user satisfaction, and improved grid support for a secure power supply. Industry outreach will be conducted to present outcomes, refine research directions, and seek commercialization of new technology. Summer workshops on electric vehicle charging for high school and undergraduate students will be used to promote engagement with STEM, including of individuals from currently underrepresented groups.This research aims to develop the foundations of a compartmentalization approach to charging power management at electric vehicle fast charging stations under maximum power restrictions and grid integration constraints. It accomplishes this outcome by modeling fast charging station management as a multi-objective optimization problem in terms of charging protocols, charging power allocation, charging pricing, and power grid interactions, constrained by the dynamics of electrochemical battery degradation, electricity market pricing, local photovoltaic power generation, vehicle to grid service, and demand response. A critical challenge is the construction of a Lyapunov function that enables a decomposition of the long-period optimization horizon into temporally queued, short-term and small-scale subproblems with guaranteed asymptotic convergence to the optimal solution of the original problem. A systematic verification and validation framework for virtual prototyping and hardware-in-the-loop testing will be implemented to investigate the performance of fast charging station management solutions under real-world conditions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这笔赠款将用于研究开发有效的电动汽车充电站管理解决方案，以降低运营成本，缩短排队时间，减少电池退化，从而促进科学进步和国家繁荣。现有的快速充电站管理解决方案基于保守预测的充电需求，没有对车辆充电进行电源控制优化。由于电网供电的可用性受到典型的限制，传统的充电解决方案可能会导致不理想的性能，包括更长的充电/排队时间和更快的电池退化。由于预计电池和混合动力汽车的充电需求在数量和多样性方面都会增加，在地理上分布的充电站的空间和时间变异性很大，以及可再生能源的间歇性对电网造成重大压力，预计这种结果将会加剧。该项目将通过应用动态系统、控制和优化技术来解决这些挑战，以得出新的充电站管理解决方案，以确保在有限电源下缩短充电时间、延长电池寿命和用户满意度，并改进电网支持以实现安全电源。将进行行业推广，以展示成果，完善研究方向，并寻求新技术的商业化。将利用面向高中生和本科生的电动汽车充电暑期讲习班来促进与STEM的接触，包括目前代表不足的群体的个人。本研究旨在开发在最大功率限制和电网集成限制下电动汽车快速充电站充电电源管理的分区方法的基础。它通过将快速充电站管理建模为一个多目标优化问题来实现这一结果，该问题涉及充电协议、充电功率分配、充电定价和电网相互作用，受电化学电池退化、电力市场定价、当地光伏发电、车网服务和需求响应等动态约束。一个关键的挑战是构造一个Lyapunov函数，它能够将长周期的优化水平分解成时间排队的、短期的和小规模的子问题，并保证渐近收敛到原始问题的最优解。将实施虚拟样机和硬件在环测试的系统验证和确认框架，以调查快速充电站管理解决方案在真实条件下的性能。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。