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

下一代电网面临着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)的挑战。这项研究的重点是开发一种智能微电网的优化设计和控制的基本方法，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炭或石油发电机不同，因为它们是间歇性的，无法准确预测，也不能调度。这项研究将开发统计方法来研究由于发电不确定性而导致的电网可靠性的基本极限，最终目的是对智能电网有新的理解。此外，拟议的研究将开发电压和频率调节以及经济调度的最优控制算法，明确考虑虚拟和真实的储能能力以及可再生发电机组的主动管理。这些控制算法将在基本原理的基础上开发，而不是简单地调整现有控制程序，并将设计为以分布式方式实施，以尽可能减少对支持电网的过于昂贵的通信基础设施的需求。广泛影响：这项研究将精确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，将对设计和优化智能计量和负荷管理技术非常有益。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控制器执行器，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，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.