CAREER: Operation of Distribution Grids in the Context of High-Penetration Distributed Energy Resources and Flexible Loads

在消费端，分布式能源(DER)和灵活负载(如光伏电池板、电动汽车(EVS)和储能系统(ESSS)的数量正在迅速增长。这些小型分布式设备通过可支持双向功率流动的电力电子接口连接到低压配电网。尽管这些设备体积很小，但如果聚集在一起，它们提供了电网可靠和安全运行所需的相当大一部分能源和辅助服务(例如，无功支持、频率调节、负载跟踪)。在未来的配电网中，有大量这样的小型有源设备，实时控制和聚合将带来计算挑战。当聚合需要与传统电网控制操作协调时，计算挑战进一步增加，这些操作涉及整数决策变量，例如负载分接开关、电容器组和网络开关。该职业项目致力于解决DER渗透率大、负载灵活的配电网的运行和计算问题。该项目的目标是：i)新的混合整数二阶锥规划(MISOCP)配电网最优潮流和聚合模型，该模型对于具有数千个聚合节点的实际大小的电网来说是易于计算的；ii)实时调度DER和灵活负载的有功和无功的分布式控制算法；以及III)在电网级别和DER聚合级别的资产的概率调度模型，以最小化配电网运行的预期约束违反。这些分布式优化和控制模型将提供足够快的调度解决方案，使得分布式级别的聚合可以很容易地跟踪各种时间分辨率的应用的电网信号。该职业项目的教育和外联活动包括：i)设计分布式控制和优化的高级课程，以培养在校和在线本科生和研究生水平的电力工程学生；ii)通过为K-12学生提供参与密歇根理工大学智能电网运营中心(SGOC)的多项活动的机会，激励他们学习科学、技术、工程和数学(STEM)；iii)利用密歇根理工大学的移动微电网实验室，通过积极演示基本的电力工程概念，接触德克萨斯州的西班牙裔学生和南达科他州的美国原住民学生。

The number of distributed energy resources (DERs) and flexible loads such as photovoltaic (PV) panels, electric vehicles (EVs), and energy storage systems (ESSs) are rapidly growing at the consumer end. These small distributed devices connect to low voltage power distribution grids via power electronic interfaces that can support bi-directional power flows. Despite being small in size, if aggregated, these devices a provide significant portion of the energy and ancillary services (e.g., reactive power support, frequency regulation, load following) necessary for reliable and secure operation of electric power grids. In future distribution grids, with numerous such small active devices, real-time control and aggregation will entail computational challenges. The computational challenges further increase when the aggregation requires coordination with legacy grid control actions which involve integer decision variables, such as load tap changers, capacitor banks, and network switches. This CAREER project concentrates around solving operational and computational issues for distribution grids with large penetration of DERs and flexible loads. This CAREER project aims to develop: i) novel mixed-integer second order cone programming (MISOCP) models of distribution optimal power flow and aggregation, which are computationally tractable for practical-sized power grids with thousands of aggregation nodes, ii) distributed control algorithms in dispatching active and reactive power of DER and flexible loads in real time, and iii) a probabilistic dispatch model of the assets at the grid level and at the DER aggregation level that minimizes expected constraint violation of distribution grid operations. These distributed optimization and control models will provide dispatch solutions sufficiently fast that the aggregation at the distribution level could easily track grid signals for applications ranging over various time resolutions. The educational and outreach activities of this CAREER project include: i) to design advanced curriculum on distributed control and optimization to train on-campus and online undergraduate and graduate level power engineering students, ii) to motivate K-12 students in pursuing science, technology, engineering, and math (STEM) by providing them opportunities to participate on several activities at Michigan Tech's Smart Grid Operations Center (SGOC), and iii) to reach out to Hispanic students in Texas and Native American students in South Dakota through active demonstration of fundamental power engineering concepts by using Michigan Tech's Mobile Microgrid Laboratory.