CAREER: A "first-principles" approach to the smart electric grid: fundamental limits and optimal control algorithms

下一代电网面临的挑战是在保持可靠性的同时整合越来越多的可再生能源发电，如风能。这项研究的重点是开发一种基本的方法来优化设计和控制的智能微电网，并开发一套开源的工具，以促进新的智能电网应用的开发。智力优势：可再生能源发电机在几个关键方面与传统的煤或油基发电机不同，因为它们是间歇性的，无法准确预测，也无法调度。本研究将开发统计方法，以调查由于发电不确定性而导致的电网可靠性的基本限制，最终目的是对智能电网有新的认识。此外，拟议的研究将开发电压和频率调节和经济调度的最优控制算法，明确考虑到虚拟和真实的能量存储能力和可再生发电机的主动管理。这些控制算法将基于第一原理开发，而不是简单地调整现有的控制程序，并将尽可能以分布式方式实现，以最大限度地减少对支持电网的过于昂贵的通信基础设施的需求。这项研究将精确地量化存储和需求响应能力在减轻发电不确定性影响方面的影响，在设计和优化智能计量和负载管理技术方面非常有益。该项目的目标之一是开发一套开源工具，如用于小型风力涡轮机和电池的智能传感器和执行器，以促进智能电网和分布式发电的小规模实验。该项目还将涉及广泛的本科生研究活动，研究结果将在技术出版物和会议上广泛传播。

The next generation electric grid faces the challenge of integrating a growing amount of renewable energy generation such as wind while maintaining reliability. This research is focused on developing a fundamental approach to the optimal design and control of a smart electric microgrid, and to develop an open-source set of tools to facilitate the development of new smart grid applications. Intellectual Merit: Renewable energy generators differ in several key ways from conventional coal or oil-based generators, in that they are intermittent, cannot be accurately forecast and are not dispatchable. This research will develop statistical methods to investigate the fundamental limits of grid reliability because of generation uncertainty, with the ultimate aim of developing new understanding of the smart electric grid. Furthermore, the proposed research will develop optimal control algorithms for voltage and frequency regulation and economic dispatch explicitly taking into account virtual and real energy storage capabilities and active management of renewable generators. These control algorithms will be developed from a first principles basis, rather than simply tweaking existing control procedures and will be designed to be implemented in a distributed way to the extent possible to minimize the need for an excessively expensive communication infrastructure supporting the grid.Broader Impacts: This research will precisely quantify the effects of storage and demand response capabilities in mitigating the effects of generation uncertainty and would be highly beneficial in designing and optimizing smart metering and load-management technologies. One of the aims of this project is to develop an open-source set of tools such as smart sensors and controller-actuators for small wind turbines and batteries, to facilitate small-scale experimentation with smart grid and distributed generation. This project will also involve extensive undergraduate research activity and results will be widely disseminated in technical publications and conferences.