GOALI: ASCENT: Online Stability Assessment, Flexibility, and Enhancement of IBR-dominated Power Systems

目标:ASCENT:IBR 主导电力系统的在线稳定性评估、灵活性和增强

基本信息

  • 批准号:
    2328248
  • 负责人:
  • 金额:
    $ 123.31万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-09-01 至 2026-08-31
  • 项目状态:
    未结题

项目摘要

This NSF project aims to develop a comprehensive theoretical framework for modeling, designing, sensing, and controlling the post-fault stability of future power systems with varying levels of inverter-based resources and synchronous generators. The project will use an innovative energy-function-based approach to study how system stability responds to configurations, pre-fault conditions, and faults. This work promises to transform how we assess and enhance the stability of power systems, advancing scientific knowledge in this critical field. The intellectual merits of the project include (1) using energy-function-based and direct methods for stability assessment, which significantly reduce the need for detailed time-domain simulations; (2) considering inverters' fast dynamics and generators' slow dynamics as a two-time-scale system, thereby simplifying the complexity of stability analysis; and (3) implementing bounded control theory to narrow the gap between simulation results and actual hardware performance, enhancing the practical applicability of the findings. The project outcomes will likely have a broader impact in diverse fields, including robotics, ecosystem modeling, and optimization. Creating an online stability assessment tool will benefit utility engineers, while an inverter design guide will inform and influence the work of the power electronics community. Additionally, the project will engage diverse individuals through various activities at the four participating institutions, reinforcing its educational and societal benefits.The technical goals of this project involve establishing the theoretical foundations of energy functions for two-time-scale systems, exploring the connection between power system stability and inverter controller dynamics, and minimizing discrepancies between power system models and inverter hardware. This will be accomplished by applying direct methods to identify stability regions, conducting theoretical investigations, and validating findings across software simulations, hardware-in-the-loop simulations, and a physical 108-converter network. As a Grant Opportunities for Academic Liaison with Industry (GOALI) project, the team will collaborate with a utility partner on a realistic transmission system model. The project will rigorously validate the proposed online transient stability assessment method on a 5000-bus system, encompassing a broad spectrum of IBR penetrations from 0 to 100%.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.
该NSF项目旨在开发一个全面的理论框架,用于对具有不同水平的逆变器资源和同步发电机的未来电力系统的故障后稳定性进行建模、设计、传感和控制。该项目将使用一种创新的基于能量函数的方法来研究系统稳定性如何响应配置、故障前条件和故障。这项工作有望改变我们评估和提高电力系统稳定性的方式,推进这一关键领域的科学知识。该项目的智能优点包括:(1)使用基于能量函数的直接方法进行稳定性评估,大大减少了对详细的时域仿真的需要;(2)将逆变器的快动态和发电机的慢动态视为一个双时间尺度系统,从而简化了稳定性分析的复杂性;(3)采用有界控制理论,缩小了仿真结果与实际硬件性能之间的差距,增强了结果的实用性。项目成果可能会在多个领域产生更广泛的影响,包括机器人、生态系统建模和优化。创建在线稳定性评估工具将使公用事业工程师受益,而逆变器设计指南将为电力电子界的工作提供信息并产生影响。此外,该项目将通过在四个参与机构的各种活动吸引不同的个人参与,加强其教育和社会效益。该项目的技术目标包括建立双时间尺度系统的能量函数的理论基础,探索电力系统稳定性和逆变器控制器动态之间的联系,以及最小化电力系统模型和逆变器硬件之间的差异。这将通过应用直接方法来确定稳定区域、进行理论研究并验证跨软件模拟、硬件在环模拟和物理108转换器网络的结果来实现。作为一个学术与工业联系机会(GOALI)项目,该团队将与一个公用事业合作伙伴合作建立一个现实的传输系统模型。该项目将在5000母线系统上严格验证建议的在线暂态稳定评估方法,涵盖从0到100%的广泛IBR渗透率。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。

项目成果

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Ziang Zhang其他文献

A Guided Deep Reinforcement Learning Method For Distribution Voltage Regulation via Battery Systems
通过电池系统进行配电电压调节的引导式深度强化学习方法
Modified Eigen-Decomposition-Based Interval Analysis (MEDIA) for Power System Dynamic State Estimation
用于电力系统动态估计的改进的基于特征分解的区间分析(MEDIA)
  • DOI:
    10.1109/tpwrs.2023.3299463
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    6.6
  • 作者:
    Yuting Chen;N. Zhou;Ziang Zhang
  • 通讯作者:
    Ziang Zhang
Coping with perceived overqualification: The effect of coping strategies on employee outcomes in the hospitality industry
应对感知到的资历过高问题:应对策略对酒店业员工成果的影响
Enhancing synergistic catalytic combustion for the co-removal of PCDD/Fs and additional pollutants from sintering flue gases: A review on catalyst development
强化协同催化燃烧以共同去除烧结烟气中的二噁英及其他污染物:催化剂研发综述
  • DOI:
    10.1016/j.seppur.2025.132132
  • 发表时间:
    2025-08-14
  • 期刊:
  • 影响因子:
    9.000
  • 作者:
    Ying Zhang;Caiting Li;Qi Huang;Xuan Liu;Jungang Zhao;Ziang Zhang;Youcai Zhu;Le Huang;Kuang Yang
  • 通讯作者:
    Kuang Yang
Discrete States-Based Trajectory Planning for Nonholonomic Robots
非完整机器人的基于离散状态的轨迹规划

Ziang Zhang的其他文献

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