Multi-Scale Analysis and Control of Smart Energy Systems

智能电网的一个主要方面是引入本质上随机和分布式的可再生能源生产，这降低了半集中式控制器有效控制系统的能力。为了弥补这种影响，引入了分布式通信、监测和控制系统。微电网是这些组件的操作和交互的逻辑单元，也是与公用电网的接口。即使在局部尺度上，系统的复杂性和多面性也使得对微电网动态的分析、预测和控制成为一项具有挑战性的任务。该项目将电力系统控制、设计和仿真与先进的理论分析和控制结合到一个创新的框架中。所设想的方法将在智能能源系统中实现许多新颖的应用，从系统适应到用户行为、用户分类和对消费者的反馈。该项目将吸引本科生和研究生参与研究工作，并将为UCI创造新的课程机会。年代的学生。项目中处理的问题的复杂性源于大量相互连接的异构子系统相互作用并对整个系统行为做出贡献。这种交互作用表现在不同的拓扑尺度和抽象层次上。子系统在物理层相互作用，电信号通过物理互连传播。然而，在逻辑状态层面上存在显著的时间和组件间的相互依赖关系，即一组描述微电网组件和影响因素当前状态的变量。逻辑层的控制通常采用调度和管理框架的形式。大多数先前的工作要么考虑物理领域，要么考虑逻辑领域，而没有提供一个清晰的方法来连接这两个相互依赖的领域。该项目将使用先进的动态规划、图论和估计理论来创建物理和逻辑系统之间的双向信息流和控制，其中学习算法被设计用于将物理和逻辑信号映射到更高级别的逻辑状态。

One of the principal aspects of the SmartGrid is the introduction of intrinsically stochastic and distributed renewable energy production, which decreases the ability of semi-centralized controllers to effectively control the system. To compensate for this effect, distributed communication, monitoring, and control systems are introduced. The microgrid is the logical unit of operations and interaction of these components, as well as the interface to the utility grid. The complexity and multifaceted nature of the system even at the local scale makes the analysis, prediction and control of the microgrid's dynamics a challenging task. The project will conjugate power system control, design and simulation with advanced theoretical analysis and control to an innovative framework. The envisioned methodology will enable a number of novel applications in smart energy systems ranging from system adaptation to user behavior, user classification, and feedback to the consumer. The project will engage undergraduate and graduate students in the research effort, and will create new curriculum opportunities for UCI?s students.The complexity of the problem addressed in the project originated from the large number of interconnected heterogeneous sub-systems interact and contribute to the overall system behavior. This interaction manifests at different topological scales and abstraction levels. The sub-systems interact at the physical level, where the electrical signals travel through the physical interconnections. However, significant temporal and inter-component interdependencies exist at the logical state level, that is, a set of variables describing the current state of microgrid components and influential factors. Control of the logical level typically takes the form of scheduling and management frameworks. Most prior work considers either the physical or the logical domain, without providing a clear methodology to bridge these two interdependent domains. The project will use advanced Dynamic Programming, graph theory, and estimation theory to create a bidirectional flow of information and control between the physical and logical systems, where learning algorithms are designed to map physical and logical signals to higher level logical states.