CRII: CPS: Architecture and Distributed Computation in the Networked Control Paradigm: An Autonomous Grid Example

该提案将建立一个框架，用于开发在网络控制系统（NCS）环境中运行的分布式网络物理系统。由于物理系统的庞大规模，计算和通信挑战是独特的，并且系统元素之间的通信包括重大损失和延迟的可能性，因此特别关注应用程序。这方面的一个例子是电网，其中包括大规模部署分布式和网络化相量测量单元（pmu）和风能资源。尽管在理论层面上已经对NCS中数据丢失和延迟的影响进行了大量建模和分析，但它们对网络物理系统行为的影响却很少受到关注。因此，过去对“智能电网”所做的许多研究都过度简化了模型的“物理”部分，从而忽略了模型维度和电网动态异质性的核心计算挑战。在理解NCS中的不确定性（例如带宽限制、数据包丢失、数据包定向障碍、延迟、信号丢失等）与大型风电场电网中的不确定性（例如风力的可变性、故障和非线性、拓扑的变化等）对电网可靠运行的影响方面，仍然存在明显的差距。为了应对这些挑战，该项目将首次开发一个建模框架，通过NCS、分布式计算和包括分布式风力发电资源在内的大型电网的联合模拟，发现迄今为止未知的相互作用。最重要的是，它通过频域抽象解决了分布式计算中的挑战，并提出了两种在丢包期间稳定网格的新技术。更广泛的影响在于对智能电网延迟和中断的影响提供更深入的了解。这将使能源传输资产得到更好的利用，并提高可再生能源的整合。该项目将促进妇女参与STEM学科，并将包括与当地印第安部落社区学院的联系。该项目将使用适用于各种CPS的方法，对网络延迟和掉线的影响进行基本理解。它将通过对电网的代表性次瞬态模型的建模充分性研究，以及吉尔伯特模型在通信网络中丢包的表示，为智能电网提供变革性的广域测量系统研究。最重要的是，提出了平衡截断和最优汉克尔范数近似等频域抽象的基本概念，大大减轻了分布式计算的负担。最后，提出了一种新颖的“减少复制”方法和“改进卡尔曼滤波”方法来解决遇到丢包时使用风电场控制的电网稳定问题。

This proposal will establish a framework for developing distributed Cyber-Physical Systems operating in a Networked Control Systems (NCS) environment. Specific attention is focused on an application where the computational, and communication challenges are unique due to the sheer size of the physical system, and communications between system elements include potential for significant losses and delays. An example of this is the power grid which includes large-scale deployment of distributed and networked Phasor Measurement Units (PMUs) and wind energy resources. Although, much has been done to model and analyze the impact of data dropouts and delay in NCS at a theoretical level, their impact on the behavior of cyber physical systems has received little attention. As a result much of the past research done on the `smart grid' has oversimplified the `physical' portion of the model, thereby overlooking key computational challenges lying at the heart of the dimensionality of the model and the heterogeneity in the dynamics of the grid. A clear gap has remained in understanding the implications of uncertainties in NCS (e.g. bandwidth limitations, packet dropout, packet disorientation, latency, signal loss, etc.) cross-coupled with the uncertainties in a large power grid with wind farms (e.g. variability in wind power, fault and nonlinearity, change in topology etc.) on the reliable operation of the grid. To address these challenges, this project will, for the first time, develop a modeling framework for discovering hitherto unknown interactions through co-simulation of NCS, distributed computing, and a large power grid included distributed wind generation resources. Most importantly, it addresses challenges in distributed computation through frequency domain abstractions and proposes two novel techniques in grid stabilization during packet dropout. The broader impact lies in providing deeper understanding of the impact of delays and dropouts in the Smart Grid. This will enable a better utilization of energy transmission assets and improve integration of renewable energy sources. The project will facilitate participation of women in STEM disciplines, and will include outreach with local Native American tribal community collegesThis project will develop fundamental understanding of impact of network delays and drops using an approach that is applicable to a variety of CPS. It will enable transformative Wide-Areas Measurement Systems research for the smart grid through modeling adequacy studies of a representative sub-transient model of the grid along with the representation of packet drop in the communication network by a Gilbert model. Most importantly, fundamental concepts of frequency domain abstraction including balanced truncation and optimal Hankel-norm approximation are proposed to significantly reduce the burden of distributed computing. Finally, a novel `reduced copy' approach and a `modified Kalman filtering' approach are proposed to address the problem of grid stabilization using wind farm controls when packet drop is encountered.