Data-Driven Operation and Control of Active Power Distribution Systems with High Penetration of Distributed Energy Resources and Energy Storage

大规模时间变化和空间分离的分布式能源（DERs）、存储设备和灵活负载的扩展对有功配电系统的管理提出了固有的计算挑战。此外，这些设备运行的时间尺度和配置要求（如微电网的形成）涉及在优化框架内集成动态系统模型。考虑到这些挑战，本项目旨在开发配电系统中最优潮流的新算法，具有大量有源设备的配电系统中子网的分布式建模，以及可确保与供应商驱动控制器无缝集成的二次控制框架。来自当地公用事业的真实数据和模型将被用来证明该方法的可行性。该项目的教育和推广活动包括：a)让学生从不同的本科生和研究生群体（包括弱势群体和少数族裔学生）中参与基于问题的学习；b)设计先进的电力系统控制课程，采用凸优化和分布式控制方法；c)提供一个平台，激励和吸引工程专业的学生，尤其是弱势群体和女性。d)通过pi的研究实验室和北卡罗来纳大学夏洛特分校的中心开发一个全面的传播平台。该项目将调查：a)一种新颖的基于后退水平控制（RHC）的混合整数二阶锥规划（MISOCP）模型，用于配电系统中的最优潮流，该模型可以扩展到集成数千个聚合节点，并为考虑不平衡配电系统运行的无源和有源设备提供设设点（整数或实数）；B)随机模型预测共识框架，用于具有大量有源设备的配电系统中子网的分布式建模；c)二次控制框架，提供改进的有功/无功功率控制，并确保与供应商驱动的控制器无缝集成，从而提高电能质量和稳定性；d)实现平台，包括具有实际数据的通信回路和来自本地公用事业的模型，以证明该方法的可行性。所提出的优化框架可以为配电系统中所有活动节点的决策控制变量和设定点（包括开关和变压器分接）提供全局解。此外，该方法可以结合随机或确定性变化的设备，如DERs和能量存储，考虑到每个子网。此外，该体系结构可以与现有的供应商驱动的控制器无缝集成，从而能够适应分布式资源的高输入，并为决策和网格状态变量的指数增长提供低成本的解决方案。该奖项反映了美国国家科学基金会的法定使命，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。

The expansion of large scale temporally changing and spatially separated distributed energy resources (DERs), storage devices and, flexible loads exhibit inherent computational challenges for management of active power distribution systems. Also, time-scale of operation of these devices and configuration requirements such as micro grid formation, involves integrating dynamic system models within the optimization framework. Considering these challenges, this project aims to develop novel algorithms for optimal power flow in power distribution systems, distributed modeling of subnetworks in power distribution system with large number of active devices, and a secondary control framework that can ensure seamless integration with vendor driven controllers. Real-life data and models from the local utility will be utilized to demonstrate feasibility of the methodology. Educational and outreach activities of this project include a) engaging students in problem-based learning from diverse undergraduate and graduate groups including under-represented and minority students, b) designing advanced curriculum on power system control with convex optimization and distributed control approaches, c) providing a platform to motivate and attract students in engineering especially the underrepresented minorities and women, and d) developing a comprehensive dissemination platform through PIs research lab and the center at University of North Carolina at Charlotte.The project will investigate: a) a novel Receding Horizon Control (RHC) based mixed-integer second order cone programming (MISOCP) model for optimal power flow in power distribution systems that can scale up to integrate thousands of aggregated nodes and provide set points (integer or real) for passive and active devices considering unbalanced distribution system operation, b) a stochastic model predictive consensus framework for distributed modeling of subnetworks in power distribution system with large number of active devices, c) a secondary control framework that provides improved active/reactive power control and can ensure seamless integration with vendor driven controllers in turn enhancing power quality and stability, and d) an implementation platform including communication loops with real-life data and models from the local utility that proves feasibility of the methodology. The proposed optimization framework can provide global solutions for decision control variables and set points, including switches and transformer taps, at all active nodes in power distribution system. Also, the methodology can incorporate stochastic or deterministic changes in the devices such as DERs and energy storage, considering each subnetwork. Moreover, the architecture can be seamlessly integrated with the existing vender driven controllers thus capable of accommodating high in-feed of distributed resources and providing a low-cost solution to exponential increase in decision and grid state variables.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.