Mobility-As-A-Service for Resilience Delivery in Power Grids: Stochastic Programming Advancements under Decision-Dependent Uncertainties

电网经常受到极端紧急情况的影响，可能使社区断电，并对健康和公共安全构成严重威胁。该NSF项目旨在提供一种新的决策模式来部署移动的电源（例如，移动的储能系统、移动的应急发电机、电动汽车和电动公交车），以增强社区和关键基础设施在面临极端事件时的应变能力。该项目将为灾害发生前和灾害发生期间移动的电力资源的分配和调度决策（预先定位、路由和调度）的不确定性管理方式带来变革。要做到这一点，就必须考虑到不确定性，这些不确定性不能简单地随着时间的推移而解决，而解决这些不确定性取决于是否实际作出部署这些灵活资源的决定，即，决策依赖的不确定性。该项目的智力优势包括设计新的数学优化模型和权宜方法，以解决提出的问题，促进电网弹性的移动性即服务。该项目更广泛的影响包括组织一个关于电力系统高级随机规划的跨学科研讨会系列，本科女生/少数民族学生参与项目研究，通过出版物传播项目成果，并向华盛顿大都市区的K-12学生展示研究成果。该项目通过开发新的风险中性和风险厌恶的随机优化问题和重新制定服务恢复，包括决策相关的不确定性（DDU），打破了目前的做法。由于难以解决这样的模型，通常采取随机混合整数非线性（多项式）规划（MINLP）问题的形式，所提出的研究还侧重于发展计算效率高的方法来解决DDU嵌入式优化模型的移动性作为一种服务的弹性。所提出的模型将占移动的电源与各种异构灵活的资源，在配电网，网络重构的做法，维修人员，运输系统的约束和时间表的协调。该计划的完成需要一种跨学科的方法，将数学规划和电力系统工程学科的关键方法结合起来，从而实现多个研究领域的融合。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Power grids are constantly subject to extreme emergencies that may leave communities without electricity and are critical threats to health and public safety. This NSF project aims to offer a new decision-making paradigm to deploy mobile power sources (e.g., mobile energy storage systems, mobile emergency generators, electric vehicles, and electric buses) for enhancing the resilience of communities and critical infrastructures when facing extreme events. The project will bring transformative change to how uncertainties are managed when making allocation and dispatch decisions of mobile power resources (pre-positioning, routing, and scheduling) before and during disasters. This will be achieved by accounting for uncertainties that cannot be resolved simply with the passage of time, but whose resolution depends on whether or not the decision to deploy these flexible resources is actually made, i.e., decision-dependent uncertainty. The intellectual merits of the project include devising new mathematical optimization models and expedient methods to solve the proposed problems promoting mobility-as-a-service for resilience in power grids. The broader impacts of the project include organizing an interdisciplinary seminar series on Advanced Stochastic Programming for Power Systems, undergraduate female/minority student involvement in the project research, dissemination of the project findings through publications, and research showcase to K-12 students in the Washington metropolitan area.Going beyond the traditional service restoration problems with exogenous uncertainties, this project disrupts the current practice by developing new risk-neutral and risk-averse stochastic optimization problems and reformulations for service restoration that incorporate decision-dependent uncertainty (DDU). Due to the difficulty to solve such models—that typically take the form of stochastic mixed-integer nonlinear (polynomial) programming (MINLP) problems, the proposed research also focuses on the development of computationally efficient methods to solve DDU-embedded optimization models on mobility-as-a-service for resilience. The proposed models will account for the coordination of mobile power sources with a variety of heterogeneous flexible resources in power distribution grids, network reconfiguration practices, repair crews, and transportation system constraints and schedules. The completion of this plan requires an interdisciplinary approach combining key methodologies from the mathematical programming and power systems engineering disciplines, thereby enabling convergence of multiple research areas.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.