CIF: Small: Collaborative Research: From Communication to Power Networks: Adaptive Energy Management for Power Systems with Renewables

CIF：小型：合作研究：从通信到电力网络：可再生能源电力系统的自适应能源管理

基本信息

批准号：
1423316
负责人：
Georgios Giannakis
金额：
$ 25.48万
依托单位：
University of Minnesota-Twin Cities
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=1423316&HistoricalAwards=false
关键词：
CIF Small Collaborative Research Communication

项目摘要

Pressing environmental issues, security of energy supply sites, as well as their reliability in case of grid outages, drive research and development efforts toward renewable energy sources (RES) worldwide. RES however are volatile and intermittent, exhibit large fluctuations, and are certainly uncertain. Accounting for the uncertainty of RES is key to efficient management of distributed energy resources (DER), which include electricity generators, energy storage units (batteries) and programmable loads (such as smart appliances). These are the basic entities of a microgrid comprising a localized collection of DER that can operate in either grid-connected or islanded modes. Attractive features of microgrids include the ability to integrate constantly growing amounts of green energy, and highly reliable autonomous operation even in case of grid outages, e.g., under natural disasters. The overarching theme of this project is reliable and economic microgrid energy management that accounts for the uncertainty and volatility of high-penetration renewables.In particular, this research addresses the major microgrid energy management challenges through development of (i) robust and risk-constrained methodologies, which adapt to the uncertain RES; and (ii) tractable, scalable, and decentralized control and coordination of DER units. One of the main features of this project?s research is scheduling of controllable DER, such as fuel-based generators, batteries, and smart appliances, in a way that guarantees system-wide efficiency objectives even in the face of unpredictable RES generation. Emphasis is also placed on development of scalable algorithms, whose complexity increases gracefully with the proliferation of generation and storage units as well as and controllable loads in microgrids, and modern distribution systems, in general. In a nutshell, this project contributes to significantly upgrading the analysis and design of microgrid operations.

紧迫环境问题，能源供应站点的安全性以及在电网中断的情况下的可靠性，将研究和开发工作推动了全球可再生能源（RES）的工作。但是，RES是挥发性且间歇性的，表现出很大的波动，当然是不确定的。考虑RES的不确定性是有效管理分布式能源（DER）的关键，其中包括发电机，储能单元（电池）和可编程负载（例如智能设备）。这些是微电网的基本实体，该实体包括一个可以在网格连接或岛上模式下运行的局部DER集合。微电网的有吸引力的特征包括能够整合不断增长的绿色能源的能力，以及即使在自然灾害下发生网格中断的情况下，即使存在电网中断，也可以进行高度可靠的自主操作。该项目的总体主题是可靠且经济的微电网能源管理，它说明了高渗透可再生能源的不确定性和波动性。尤其是，本研究解决了通过（i）（i）（i）强大和风险约束方法的主要微电网能源管理挑战，这些方法适应不确定的RES；（ii）DER单位的可拖动，可扩展和分散的控制和协调。该项目的研究的主要功能之一是安排可控的DER，例如基于燃料的发电机，电池和智能设备，以确保即使面对不可预测的RES生成，也可以保证系统范围内的效率目标。重点也放在可扩展算法的开发上，其复杂性随着发电和存储单元的扩散以及微电网和现代分配系统的可控载荷而优雅地增加。简而言之，该项目有助于显着升级微电网操作的分析和设计。

项目成果

期刊论文数量（20）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Reinforcement Learning for 5G Caching with Dynamic Cost

DOI：
10.1109/icassp.2018.8462673
发表时间：
2018-04
期刊：
2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
影响因子：
0
作者：
A. Sadeghi;Fatemeh Sheikholeslami;A. Marques;G. Giannakis
通讯作者：
A. Sadeghi;Fatemeh Sheikholeslami;A. Marques;G. Giannakis

An Online Convex Optimization Approach to Real-Time Energy Pricing for Demand Response