Collaborative Research: Large-Signal Stability Analysis and Enhancement of Converter-Dominated DC Microgrid

摘要：虽然直流微电网具有许多众所周知的优势(例如，更简单、更高效、更紧凑的电力转换系统以及更少的电缆铜消耗)，但其独特的直流电气特性，如直接P-V耦合(即即使是很小的负载/发电变化也可能导致电压闪变和设备故障)和系统惯性(即非常小的过载能力)，对电网的稳定性构成了巨大的挑战。小干扰稳定只能保证系统在平衡点的稳定性，但不能确定稳定域的真实边界，因此当系统存在大扰动时，在确保稳定方面存在很大的局限性。现有文献中的大信号分析工具要么适用范围有限，要么理论基础不严密。因此，迫切需要建立换流为主的直流微网大干扰稳定分析的基本知识库和全面的直流电网稳定设计准则。本项目的研究成果直接有助于我国在越来越多的微电网和分布式能源的情况下保持电力的高可靠性和高弹性的总体目标。拟议的教育和外展研究计划将(I)将该项目的理论框架、精心策划的数据集和试验床纳入密歇根大学迪尔伯恩分校和得克萨斯大学奥斯汀分校的现有课程；(Ii)促进K-12学生对STEM的兴趣；(Iii)通过公共访问网站、顶级会议和期刊出版物以及各种媒体，在公共领域传播所有项目材料、过程、设计和结果；通过在微电网上创建具有社会意义的项目，为未被充分代表的本科生提供丰富的研究机会。该项目的目标是：(A)朝着推导具有多个分布式能源和恒定功率负载的直流微电网大信号全局稳定的充分判据迈出严格的一步，这仍然是一个悬而未决的难题，因为传统的小干扰稳定性分析不适用于发生大扰动时的换流器为主的电力系统，如故障、脉冲功率负载或负载切换；以及(B)研究一种系统的方法，以一种理论上合理但易于实施的方式来提高变流器主导的直流微电网的全局渐近稳定性，最终弥合控制理论、电力系统和电力电子这三个传统上相互脱节的领域之间的技术差距。拟议的项目旨在通过利用PI的专业知识(例如，电力系统、电力电子、优化、控制理论和机器学习)的范围和深度来实现这一目标。所提出的研究将在以下几个方面具有智力优势：(1)理解恒功率负荷100%穿透和基于换流器的分布式能源的无惯性直流微网大信号稳定判据的基本知识库；(2)具有稳定性意识的转换器，以理论上合理但易于实现的方式共同提高以换流器为主的直流微网的全局渐近稳定性；(3)用于估计具有多个均衡的一般动态系统(即直流微网)的吸引区的严格数学方法和安全学习算法；和(4)电源硬件在回路试验台，允许创新的稳定性感知转换器的概念验证原型的动态交互。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Title: Collaborative Research: Large-Signal Stability Analysis and Enhancement of Converter-Dominated DC MicrogridAbstract: While DC microgrids have many well-understood advantages (e.g., simpler, more efficient and compact power conversion system as well as less copper consumption in the cables), the unique DC electric characteristics, such as direct P-V coupling (i.e., even a small load/generation change can lead to voltage flickers and equipment malfunctions) and low system inertia (i.e., very little overload capacity), pose great challenges to grid stability. Small-signal stability can only ensure the stability of the system at the equilibrium point, but the true boundary of the stability domain cannot be determined; hence there are major limitations in securing stability when the system has large disturbances. Existing large-signal analysis tools in the literature have either limited applicable ranges or non-rigorous theoretical foundations. Therefore, there is an urgent need to develop a fundamental knowledge base of large-signal stability analysis in converter-dominated DC microgrids and a comprehensive design guideline for DC grid stability. The research findings of this project directly contribute to the overall goal in our country to maintain high reliability and resilience electricity with more and more microgrids and distributed energy sources. The proposed education and outreach research plan will (i) incorporate theoretical frameworks, curated data sets, and testbed from this project into the existing curriculum at both the University of Michigan-Dearborn and the University of Texas at Austin; (ii) promote K-12 students’ interest in STEM; (iii) disseminate all project materials, processes, designs and results in the public domain via public-access websites, top-ranking conference and journal publications and in diverse media; and (iv) provide rich research opportunities to under-represented undergraduates by creating societally meaningful projects on microgrids.The goal of this project is to (a) take a rigorous step toward deriving the sufficient criteria for large-signal global stability in DC microgrids with multiple distributed energy sources and constant power loads, which is still an unsolved puzzle because traditional small-signal stability analysis does not apply to converter-dominated power systems when a large disturbance occurs, such as a fault, a pulse power load, or load switching; and (b) investigate a systematic methodology to improve the global asymptotic stability of a converter-dominated DC microgrid in a theoretically sound yet easy-to-implement manner, ultimately bridging the technology gap between three traditionally disjointed areas: control theory, power systems, and power electronics. The proposed project aims to fulfill this goal by leveraging the range and depth of the PIs’ expertise (e.g., power systems, power electronics, optimization, control theory, and machine learning). The proposed research will have intellectual merits in the following areas: (1) a fundamental knowledge base to understand the large-signal stability criteria of inertia-less DC microgrids with 100% penetration of constant power loads and converter-based distributed energy sources; (2) a stability-aware converter to collectively improve the global asymptotic stability of converter-dominated DC microgrids in a theoretically sound yet easy-to-implement manner; (3) rigorous mathematical methods and safe learning algorithms for estimating the region of attraction of a general dynamic system (i.e., a DC microgrid) with multiple equilibria; and (4) a power-hardware-in-the-loop testbed allowing for dynamic interactions of the proof-of-concept prototypes of innovative stability-aware converters.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.