Advanced Signal Processing for Smard Grid and Renewable Energy Sources

适用于智能电网和可再生能源的高级信号处理

• 批准号: 1405327
• 负责人: Xiaodong Wang
• 金额: $ 30万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1405327&HistoricalAwards=false
• 关键词: Advanced; Signal; Processing; Smard; Grid

Modernizing the electric power grid has become a major national priority for many countries across the globe. With the increasing penetration of renewable and distributed energy sources along with the necessary means of energy storage technologies, it is envisioned that the so-called "smart grids" will make the production and delivery of electricity more reliable and more cost-effective, and will allow consumers to make more informed decisions about their energy consumption. The smart grid transforms the legacy grid that provides a one-way centrally generated power flow to end users into a more distributed and dynamic system of two-way flow of power and information. The essential concept of the smart grid, where the intelligence will be to a large extent distributed, is the integration of power electronics, real-time metering, digital communications, signal processing, and control technologies into the power system. Communications and information technology play a critical role in the smart grid. As the power grid becomes more complex, more interconnected, and more intelligent, large amount of data will be generated by meters, sensors and synchrophasors. Advanced techniques for managing, analyzing and acting on such data need to be developed. Further, as more and more renewable energy sources, such as photovoltaic (PV) solar arrays and wind turbine arrays are deployed, novel techniques are needed to optimize and monitor the energy generation performance. The numerous technical challenges that accompany the future smart-grid systems call for novel solutions. Hence it is important at this time to perform research that addresses the theoretical aspects of smart grid and renewable energy sources, and to acquire insights and theoretical tools that may help propel significant advances in this field. This project focuses on three major topics that are related to the distributed intelligence for smart grid and renewable energy sources: (1) to develop distributed and secure nonlinear state estimation methods for both power transmission and power distribution grids; (2) to develop decentralized sequential joint change detection and estimation algorithms for real-time detection and mitigation of cyber attacks in smart grid; and (3) to develop decentralized model-free adaptive algorithms for online optimization and monitoring of solar PV arrays, and for controlling of wind turbine arrays, respectively. Smart grid and renewable energy sources bring profound changes to the society and the proposed research will lead to new and powerful techniques for grid state estimation, cyber attack detection and mitigation, and efficient utilization of renewable energy sources. In addition to conducting theoretical analysis, computational procedures will be developed to facilitate the analytical work. The new concepts and algorithms developed under ideal conditions will be tailored to operate in practical systems with various constraints. It is expected that the proposed research will not only enhance our understanding of the fundamental underpinnings of the complex smart-grid systems and renewable energy sources, but also produce new and powerful tools for future electrical power systems. By coordinating with an established outreach program, this project will actively engage K-12 students and traditionally under-represented groups and inspire these students to pursue STEM (science, technology, engineering and mathematics) education and careers.

现代化电力电网已成为全球许多国家的主要国家优先事项。随着可再生能源和分布式能源的渗透以及必要的储能技术的渗透，可以预见，所谓的“智能电网”将使电力的生产和交付更加可靠，更具成本效益，并使消费者能够对他们的能源消耗做出更加知识的决策。智能网格将传统网格转换为单程中心生成的功率流，使最终用户成为双向电源和信息流的分布式和动态系统。智能电网的基本概念在很大程度上分布在智能上，是电力电子，实时计量，数字通信，信号处理和控制技术的集成。通信和信息技术在智能电网中起着至关重要的作用。随着电网变得更加复杂，更加互连，更聪明，大量数据将由仪表，传感器和同步声产生。需要开发用于管理，分析和行动此类数据的高级技术。此外，随着越来越多的可再生能源（例如光伏（PV）太阳阵列和风力涡轮机阵列）被部署，需要新颖的技术来优化和监视能源发电性能。未来智能网格系统伴随的许多技术挑战都要求提供新颖的解决方案。因此，在此时进行研究很重要，以解决智能电网和可再生能源的理论方面，并获得可能有助于推动该领域的重大进步的见解和理论工具。该项目侧重于与智能电网和可再生能源的分布式智能有关的三个主要主题：（1）为电力传输和发电机网格开发分布式和保护非线性状态估计方法； （2）开发分散的顺序关节变化检测和估计算法，以实时检测和缓解智能电网的网络攻击； （3）开发分散的无模型自适应算法，以在线优化和监视太阳能PV阵列，并分别控制风力涡轮机阵列。智能电网和可再生能源为社会带来了深刻的变化，拟议的研究将为网格状态估算，网络攻击检测和缓解以及有效利用可再生能源提供新的强大技术。除了进行理论分析外，还将制定计算程序以促进分析工作。在理想条件下开发的新概念和算法将量身定制，以在具有各种限制的实用系统中运行。预计拟议的研究不仅将增强我们对复杂的智能网格系统和可再生能源的基本基础的理解，而且还为未来的电力系统生成了新的和强大的工具。通过与既定的外展计划进行协调，该项目将积极与K-12学生和传统代表性不足的团体互动，并激发这些学生追求STEM（科学，技术，工程和数学）教育和职业。