Performance Guarantees for Electric Vehicle Fast Charging Station Management

该补助金将资助研究，以开发有效的电动汽车充电站管理解决方案，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，并且不利用用于车辆充电的功率控制优化。给定对电网供应的电力的可用性的典型约束，常规充电解决方案可能导致不期望的性能，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电动汽车的充电需求在数量和多样性方面都将增加，地理分布的充电站的空间和时间变化显著，以及可再生能源的不稳定性对电网造成了重大压力，预计这些结果将加剧。该项目将通过应用动态系统、控制和优化技术来应对这些挑战，以获得新的充电站管理解决方案，从而在有限的电源供应下缩短充电时间，提高电池寿命和用户满意度，并改善电网对安全电源的支持。将进行行业外联，以展示成果，完善研究方向，并寻求新技术的商业化。针对高中生和本科生的电动汽车充电暑期研讨会将用于促进STEM的参与，包括目前代表性不足的群体的个人。这项研究旨在为最大功率限制和电网集成限制下的电动汽车快速充电站充电功率管理的分区方法奠定基础。它通过将快速充电站管理建模为充电协议、充电功率分配、充电定价和电网交互方面的多目标优化问题来实现这一结果，该问题受到电化学电池退化、电力市场定价、本地光伏发电、车辆到电网服务和需求响应的动态约束。一个关键的挑战是构造一个李雅普诺夫函数，该函数能够将长期优化范围分解为时间排队，短期和小规模的子问题，并保证渐近收敛到原始问题的最优解。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.