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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.

紧迫的环境问题、能源供应场所的安全性以及在电网中断情况下的可靠性，推动了全球可再生能源（RES）的研发工作。然而，可再生能源是不稳定和间歇性的，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（如智能家电）。这些是微电网的基本实体，包括可以在并网或孤岛模式下操作的DER的本地化集合。微电网的吸引人的特征包括集成不断增长的绿色能源的能力，以及即使在电网中断的情况下也高度可靠的自主操作，例如，在自然灾害中。该项目的首要主题是可靠和经济的微电网能源管理，解决高渗透率可再生能源的不确定性和波动性。特别是，该研究通过开发（i）强大的和风险约束的方法来解决主要的微电网能源管理挑战，适应不确定的RES;和（ii）易于处理的，可扩展的，分散的DER单元的控制和协调。该项目的主要特点之一是？的研究是调度可控的DER，如燃料发电机，电池和智能电器，以保证系统范围内的效率目标，即使在不可预测的RES生成。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以及微电网和现代配电系统中的可控负载的扩散而优雅地增加。简而言之，该项目有助于显著提升微电网运营的分析和设计。

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