Design, Stability and Optimality of Cyber-networks for Frequency Regulation in the Smart Grid

该研究项目旨在开发有助于将清洁能源整合到电网中的方法。我们正处于未来几十年能源系统向更可持续形式的历史性转变的风口浪尖。关键的技术挑战之一是在电网的所有点上始终平衡供需。传统上，供需平衡是通过使发电量适应波动的需求来维持的。这在未来将变得无效，因为风能和太阳能等可再生电力来源是随机和不可控的。另一方面，将有越来越多的分布式能源，如电动汽车、智能建筑、智能家电、存储设备和其他电力电子控制器，不仅可以消耗，而且可以感知、计算、通信和执行。我们将设计无处不在的、持续的负荷侧频率调节方法，以补充当前的发电侧控制，证明这些方法在大型分布式能源网络中的稳定性和最优性，并研究它们与发电机侧控制的相互作用。像智能电网这样的网络物理网络由受其自身物理定律支配的物理网络和在物理网络上感知、通信、计算和执行的网络组成。我们的出发点是观察到网络的拓扑可能不同于物理网络的拓扑。例如，并不是物理网络中的每个节点都有传感器或控制器，这限制了网络的拓扑结构。另一方面，物理网络中没有直接连接的两个节点可能能够例如通过无线信道进行通信，并且这为网络的设计提供了额外的自由度。我们将开发一种理论来阐明网络对物理网络的稳定性和最优性的影响，基于理论上的见解设计有效的网络和频率调节算法，并通过仿真验证这些设计。

This research project aims at developing methods to help integrate clean energy into the electric power grid. We are at the cusp of a historic transformation of our energy system into a more sustainable form in the coming decades. One of the key technical challenges is balancing supply and demand at all times at all points of grid. Traditionally, supply-demand balance is maintained by adapting generation to fluctuating demand. This will become ineffective in the future because sources of renewable generation of electricity such as wind and solar power are random and uncontrollable. On the other hand, there will be more and more distributed energy resources such as electric vehicles, smart buildings, smart appliances, storage devices, and other power electronic controllers that not only consume, but may also sense, compute, communicate and actuate. We will design methods for ubiquitous, continuous load-side frequency regulation to supplement the current generation-side control, prove the stability and optimality of these methods in a large network of distributed energy resources, and study their interaction with generator-side control.A cyberphysical network such as a smart grid consists of a physical network governed by its own laws of physics and a cyber-network that senses, communicates, computes, and actuates on the physical network. Our starting point is the observation that the topology of the cyber-network may be different from that of the physical network. For instance, not every node in the physical network may have sensors or controllers, and this constrains the topology of the cyber-network. On the other hand, two nodes that are not directly connected in the physical network may be able to communicate, e.g., through a wireless channel, and this provides an extra degree of freedom for the design of the cyber-network. We will develop a theory to clarify the impact of the cyber-network on the stability and optimality of the physical network, design effective cyber-networks and frequency regulation algorithms based on the theoretical insights, and validate these designs through simulations.