US Ignite: Focus Area 1: An Integrated Reconfigurable Control and Self-Organizing Communication Framework for Advanced Community Resilience Microgrids

US Ignite：重点领域 1：用于高级社区弹性微电网的集成可重构控制和自组织通信框架

• 批准号: 1915756
• 负责人: Lei Wu
• 金额: $ 47.7万
• 依托单位: Stevens Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1915756&HistoricalAwards=false
• 关键词: US; Ignite; Focus; Area; Integrated

The United States is experiencing an increasing frequency of catastrophic weather events that inflict serious social and economic impacts. A critical issue associated with such catastrophes is the availability of electricity for the recovery efforts. Community resilience microgrids can connect critical loads in the community and share the distributed energy resources of multiple providers to enhance the availability of electricity supply during disruptions. However, community resilience microgrids are complex networked systems, and their operation can be often interrupted or halted due to the cascaded growth of failures in interconnected electrical and communications components or the unwillingness or inability of individual microgrid partners to respond. In order to enable the full functionality of community resilience microgrids, this project investigates an integrated reconfigurable control and self-organizing communication framework for enhancing operations in both grid-connected and islanded modes. The effectiveness and benefit of the proposed framework will be demonstrated and evaluated through the hardware-in-the-loop simulation and an actual community microgrid project, which will ultimately provide a model for the successful deployment of community resilience microgrids in the U.S. and beyond. In addition to including doctoral students in research and creating educational materials for the next generation operators and researchers of electrical and communications systems, projects will involve underrepresented students in evaluating social, economic, and resilience benefits of integrated control and communication approaches.Coordinated dynamic control strategies for distributed energy resources and loads of multiple owners across different timescales, together with their distinct communication requirements, are the key to the resilient and economic operation of community microgrids in both grid-connected and islanded modes. This research will address these challenges by (1) exploring a hierarchically reconfigurable centralized/distributed control strategy to optimally manage power flows of distribution lines, dispatches of distributed energy resources and flexible loads, and the voltage and frequency of the microgrid across multiple timescales; (2) investigating a self-organizing infrastructure with network topology adjustment and multi-scale data aggregation for flexible, fast, and reliable communication; (3) developing an integrated reconfigurable control and self-organizing communication framework to study the interdependency and interaction between control strategies and communication requirements; and (4) validating, demonstrating, and promoting the developed framework through the hardware-in-the-loop simulation and an ongoing community microgrid project.

美国正经历灾难性天气事件的频率越来越多，造成严重的社会和经济影响。与此类灾难相关的一个关键问题是恢复工作的电力可用性。社区弹性微电网可以连接社区中的关键负载，并共享多个提供商的分布式能源，以增强干扰过程中电力供应的可用性。但是，社区弹性微电网是复杂的网络系统，由于互连电气和通信组件的失败的增长，或者单个微电网伴侣无法做出反应，因此通常会中断或停止其操作。为了启用社区弹性微电网的全部功能，该项目研究了一个综合的可重新配置控制和自组织的通信框架，以增强网格连接和岛屿模式的操作。拟议框架的有效性和好处将通过硬件仿真和一个实际的社区微电网项目来证明和评估，该项目最终将为成功部署美国及其他地区的社区弹性微电网提供模型。除了在研究中包括博士生并为下一代运营商和电气和通信系统的研究人员创建教育材料外，项目还将涉及不足的学生评估综合控制和沟通方法的社会，经济和弹性益处。协调的动态控制策略，用于各种跨越跨越的分布式能源和负载，以及各种跨越各种各样的经济范围，以及跨越各种各样的经济运作，是众所周知的跨度，以及跨越了跨越的经济范围。网格连接和岛屿模式。这项研究将通过（1）探索层次可重新配置的集中/分布式控制策略，以最佳管理分配线路的功率流，分布式能源的调度和柔性载荷，以及在多个时间尺度上的微网络的电压和频率； （2）通过网络拓扑调整和多尺度数据聚合来调查自组织基础架构，以进行灵活，快速和可靠的通信； （3）开发一个综合的可重构控制和自组织沟通框架，以研究控制策略和沟通要求之间的相互依存关系和相互作用； （4）通过循环模拟和正在进行的社区微电网项目验证，演示和促进开发的框架。

项目成果

Low-Latency Communications for Community Resilience Microgrids: A Reinforcement Learning Approach

• DOI: 10.1109/tsg.2019.2931753
• 发表时间: 2020-03-01
• 期刊: IEEE TRANSACTIONS ON SMART GRID
• 影响因子: 9.6
• 作者: Elsayed, Medhat;Erol-Kantarci, Melike;Li, Jie
• 通讯作者: Li, Jie

Reputation-enabled Federated Learning Model Aggregation in Mobile Platforms

• DOI: 10.1109/icc42927.2021.9500928
• 发表时间: 2021-06
• 期刊: ICC 2021 - IEEE International Conference on Communications
• 作者: Yuwei Wang;B. Kantarci

Power Loss-Aware Transactive Microgrid Coalitions under Uncertainty

• DOI: 10.3390/en13215782
• 发表时间: 2020-11
• 期刊: Energies
• 影响因子: 3.2
• 作者: M. Sadeghi;Shahram Mollahasani;M. Erol-Kantarci

Cost-Optimized Microgrid Coalitions Using Bayesian Reinforcement Learning

• DOI: 10.3390/en14227481
• 发表时间: 2021-11
• 期刊: Energies
• 影响因子: 3.2
• 作者: Mohammad Sadeghi;Shahram Mollahasani;M. Erol-Kantarci

Transfer Reinforcement Learning for 5G New Radio mmWave Networks

• DOI: 10.1109/twc.2020.3044597
• 发表时间: 2021-05-01
• 期刊: IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
• 影响因子: 10.4
• 作者: Elsayed, Medhat;Erol-Kantarci, Melike;Yanikomeroglu, Halim
• 通讯作者: Yanikomeroglu, Halim