CAREER: A Decentralized Optimization Framework for Next-Gen Transportation and Power Systems with Large-scale Transportation Electrification

该学院早期职业发展（CAREER）项目旨在提高交通和电力系统（TPS）的可持续性和弹性，以应对电动汽车（EV）和清洁能源的快速部署。传统的、针对具体系统的办法往往不足以或无法解决密切联系和分散决策的问题。本研究通过为系统级规划和操作提供一种新的机制设计来满足这一基本挑战。开发的方法有可能扩展到其他基础设施系统，在那里异构的利益相关者在一个大规模的网络相互作用。研究结果将有助于为电动汽车的采用和间歇性清洁能源的电网整合提供未来战略。综合研究和教育活动旨在促进知识转移给学生，从业者和公众，包括K-12和大学生，公用事业公司和交通规划机构。这个CAREER项目的科学目标是促进对分散式TPS机制设计的理解。更具体地说，研究工作将推进以下方面的知识：（1）网络建模策略，以阐明具有不完整信息的异构和分散的利益相关者之间的时空互动;（2）分散的TPS的最佳信息感知和共享策略;以及（3）公平意识的市场机制设计，以优化利用电动汽车和清洁能源的TPS。同时，该奖项将融合凸化、分解和变分分析理论，以科普TPS规划和运营中多主体交互、多阶段决策和多维场景所带来的计算挑战。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 Faculty Early Career Development (CAREER) project aims to enhance the sustainability and resilience of transportation and power systems (TPSs) in response to rapid deployment of electric vehicles (EVs) and clean energy. Traditional, system-specific approaches are often inadequate or unable to address close couplings and decentralized decision-making scheme. This research meets this fundamental challenge by offering a novel mechanism design for system-level planning and operation. The methodologies developed have the potential to extend to other infrastructure systems, where heterogeneous stakeholders interact with each other over a large-scale network. Research findings will help inform future strategies for EV adoption and grid integration of intermittent clean energy sources. The integrated research and education activities are intended to facilitate knowledge transfer to students, practitioners, and the public, including K-12 and college students, utility companies, and transportation planning agencies. The scientific goal of this CAREER project is to advance the understanding of the mechanism design of decentralized TPSs. More specifically, the research efforts will advance the knowledge on (1) network modeling strategies to elucidate the spatiotemporal interactions among heterogeneous and decentralized stakeholders with incomplete information, (2) optimal information sensing and sharing strategies for decentralized TPSs, and (3) equity-aware market mechanism design to optimize TPSs leveraging EVs and clean energy. Meanwhile, it will integrate convexification, decomposition, and variational analysis theories to cope with the computational challenges brought by multi-agent interaction, multi-stage decision-making, and multi-dimensional scenarios for TPSs planning and operation.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.