CPS:Medium:Collaborative Research:Information and Computation Hierarchy for Smart Grids

CPS：中：协作研究：智能电网的信息和计算层次结构

• 批准号: 1135844
• 负责人: Lang Tong
• 金额: $ 132.5万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-15 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1135844&HistoricalAwards=false
• 关键词: CPS; Medium; Collaborative; Research; Information

The electric grid in the United States has evolved over the past century from a series of small independent community-based systems to one of the largest and most complex cyber-physical systems today. However, the established conditions that made the electric grid an engineering marvel are being challenged by major changes, the most important being a worldwide effort to mitigate climate change by reducing carbon emissions.This research investigates key aspects of a computation and information foundation for future cyber-physical energy systems?the smart grids. The overall project objective is to support high penetrations of renewable energy sources, community based micro-grids, and the widespread use of electric cars and smart appliances.The research has three interconnected components that, collectively, address issues of computation architecture, information hierarchy, and experimental modeling and validation. On computation architecture, the framework based on cloud computing is investigated for the scalable, consistent, and secure operations of smart grids. The research aims to quantify fundamental design tradeoffs among scalability, data consistency, security, and trustworthiness for emerging applications of smart grids. On information hierarchy, temporal and spatial characteristics of information hierarchy are investigated with the goal of gaining a foundational understanding on how information should be partitioned, collected, distributed, compressed, and aggregated. The research also develops an open and scalable experimental platform (SmartGridLab) for empirical investigations and testing of algorithms and concepts developed in this project. SmartGridLab integrates the hardware testbed with a software simulator so that software virtual nodes can interact with physical nodes in the testbed. This research also includes a significant education component aimed at integrating frontier research with undergraduate and graduate curricula.

在过去的一个世纪里，美国的电网已经从一系列独立的小型社区系统发展成为当今最大和最复杂的网络物理系统之一。然而，使电网成为工程奇迹的既定条件正受到重大变化的挑战，最重要的是通过减少碳排放来减缓气候变化的全球努力。本研究探讨了未来网络物理能源系统的计算和信息基础的关键方面。智能电网。该项目的总体目标是支持可再生能源的高渗透率、基于社区的微电网以及电动汽车和智能电器的广泛使用。这项研究有三个相互关联的组成部分，它们共同解决了计算架构、信息层次、实验建模和验证等问题。在计算体系结构方面，研究了基于云计算的智能电网可扩展性、一致性和安全性运行框架。该研究旨在量化智能电网新兴应用的可扩展性、数据一致性、安全性和可信度之间的基本设计权衡。在信息层次上，研究了信息层次的时间和空间特征，目的是对信息应该如何划分、收集、分发、压缩和聚合有一个基本的理解。该研究还开发了一个开放和可扩展的实验平台（SmartGridLab），用于实证调查和测试该项目中开发的算法和概念。SmartGridLab将硬件试验台与软件模拟器集成在一起，使软件虚拟节点能够与试验台中的物理节点进行交互。这项研究还包括一个重要的教育组成部分，旨在将前沿研究与本科和研究生课程相结合。