Collaborative Research: Advancing Robust Control and State Estimation of Converter-Based Power Systems

合作研究：推进基于转换器的电力系统的鲁棒控制和状态估计

• 批准号: 2151571
• 负责人: Ahmad Taha
• 金额: $ 26.5万
• 依托单位: Vanderbilt University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2151571&HistoricalAwards=false
• 关键词: Collaborative; Research; Advancing; Robust; Control

Future power grids, the nation’s most critical infrastructure, will be extremely difficult to manage due to large-scale integration of renewable energy resources. The strategy proposed in this project is aided by new grid technologies (converter-based assets in wind/solar farms and high-frequency sensing devices) that are developed and deployed to allow new real-time control-theoretic algorithms to be implemented with little overhead---while guaranteeing grid stability and resilience. The literature in this area had addressed various scientific research questions, but mostly adopted simplified models that cannot adequately capture the real-time operation of future grids. This project addresses this science gap by developing a new set of real-time algorithms, leading to a more robust operation of future power grids characterized with high penetration of renewable energy resources. These control algorithms can be implemented by grid operators throughout the nation. The project will also include: a) hosting an outreach workshop on renewable energy systems for a low-income, minority-majority, and female-only high school in San Antonio; b) organizing a technical industry workshop that showcases the created algorithms in the state of Iowa; c) disseminating the created scientific methods within the curricula at the University of Texas at San Antonio and Iowa State University.This project aims at modernizing grid control methods which has traditionally relied on linear systems theory. In particular, the control-theoretic literature addressed a plethora of grid challenges with a focus on linearized, differential equation models whereby algebraic constraints (i.e., power flows) are eliminated. This is in contrast with the more realistic, complex nonlinear differential algebraic equation (NDAE) models. Linearizing grid models around operating points and eliminating algebraic constraints have proven to be a reliable strategy---a trade-off between complexity and tractability. Yet as grids are increasingly pushed to their limits via intermittent renewables, their physical states risk escaping operating regions due to a poor prediction of wind or solar. In lieu of linear differential equation models, control of NDAEs is highly beneficial for grids that are characterized by highly uncertain renewables. This guarantees grid stability for larger operating conditions. Given the limitations of present power system models and the lack of theoretical foundations for control and dynamic state estimation of grid NDAEs, this project will: 1) create a physically representative NDAE model of a power system with a mix of conventional machines and a variety of converter-based technologies; 2) investigate a general theory of dynamic state estimation and robust feedback control algorithms that consider the uncertain nature of power grids modeled via higher-order NDAEs; 3) obtain computationally tractable routines that can be implemented in control centers of power grids. The created theoretical foundations have applications in wide area control, converter-based control, centralized and decentralized and robust dynamic state estimation. This research is critical to guarantee acceptable performance of modern and future power systems and will lead to advancing the state-of-the-art of grid control studies.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.

由于可再生能源的大规模整合，未来最关键的基础设施的电力网格将非常困难。该项目中提出的策略得到了新的网格技术（风/太阳能农场和高频传感设备的基于转换器的资产），这些策略是开发和部署的，这些技术可以实现新的实时控制理论算法，同时很少使用高架----同时保证网格稳定性和弹性。该领域的文献已经解决了各种科学研究问题，但是大多采用了简化的模型，这些模型无法充分捕获未来网格的实时操作。该项目通过开发一套新的实时算法来解决这一科学差距，从而导致未来电网的更强大的操作，其特征是可再生能源的高渗透率。这些控制算法可以由全国电网运营商实施。该项目还将包括：a）在圣安东尼奥举办有关低收入，少数群体和仅女性高中的可再生能源系统的外展研讨会； b）组织一个技术行业研讨会，以展示爱荷华州创建的算法； c）在得克萨斯大学圣安东尼奥和爱荷华州立大学的课程中传播创建的科学方法。该项目旨在将传统上依赖线性系统理论的电网控制方法现代化。特别是，控制理论文献解决了许多网格挑战，重点是线性化的微分方程模型，该方程模型消除了代数约束（即功率流）。这与更现实，更复杂的非线性差异代数方程（NDAE）模型形成鲜明对比。事实证明，围绕操作点并消除代数约束的网格模型是可靠的策略，这是一种可靠的策略 - 复杂性和障碍之间的权衡。然而，随着网格越来越多地通过间歇性可再生能源推向其极限，由于对风或太阳能的预测较差，其身体状态可能会逃避操作区域。对NDAE的控制代替线性微分方程模型，对以高度不确定的可再生能源为特征的网格非常有益。这确保了较大的操作条件的网格稳定性。鉴于当前的电力系统模型的局限性以及缺乏控制网格NDAE的控制和动态状态估计的理论基础，该项目将：1）创建具有传统机器和各种基于转换器技术的电力系统的物理代表性的NDAE模型； 2）研究动态状态估计和鲁棒反馈控制算法的一般理论，该算法考虑了通过高阶NDAE模拟的功率网格的不确定性质； 3）获取可以在电网控制中心实现的计算处理程序。创建的理论基础具有广泛控制，基于转换器的控制，集中和分散且强大的动态状态估计的应用。这项研究对于保证现代和未来的电力系统的可接受性能至关重要，并将导致推进网格控制研究的最新作用。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和更广泛的影响评估标准来评估值得支持。

项目成果

Optimal Placement of PMUs in Power Networks: Modularity Meets A Priori Optimization

PMU 在电力网络中的最佳布局：模块化满足先验优化

• DOI: 10.23919/acc55779.2023.10156230
• 发表时间: 2023
• 期刊: American Control Conference 2023
• 作者: Kazma, Mohamad H.;Taha, Ahmad F.
• 通讯作者: Taha, Ahmad F.

Revisiting the Optimal PMU Placement Problem in Multi-Machine Power Networks

重新审视多机电力网络中的最佳 PMU 放置问题

• 发表时间: 2023
• 期刊: IEEE transactions on control systems technology
• 影响因子: 4.8
• 作者: Kazma, Mohamad;Taha, Ahmad F.
• 通讯作者: Taha, Ahmad F.

Robust Feedback Control of Power Systems With Solar Plants and Composite Loads

• DOI: 10.1109/tpwrs.2023.3323222
• 发表时间: 2023-10
• 期刊: IEEE Transactions on Power Systems
• 影响因子: 6.6
• 作者: Muhammad Nadeem;MirSaleh Bahavarnia;Ahmad F. Taha

On Updating Static Output Feedback Controllers Under State-Space Perturbation

状态空间扰动下更新静态输出反馈控制器

• 发表时间: 2023
• 期刊: IEEE transactions on automatic control
• 影响因子: 6.8
• 作者: Bahavarnia, MirSaleh;Taha, Ahmad F.
• 通讯作者: Taha, Ahmad F.

Ode Transformations Of Nonlinear DAE Power Systems

非线性 DAE 电力系统的颂变换

• 发表时间: 2023
• 期刊: Proceedings of the American Control Conference
• 作者: Kazma, Mohamad;Taha, Ahmad F.
• 通讯作者: Taha, Ahmad F.