NSF Convergence Accelerator–Track D: AI-Grid: AI-Enabled, Provably Resilient, Programmable Networked Microgrids

NSF 融合加速器 - 轨道 D：人工智能网格：人工智能支持、可证明弹性、可编程网络微电网

• 批准号: 2134840
• 负责人: Peng Zhang
• 金额: $ 500万
• 依托单位: SUNY at Stony Brook
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2134840&HistoricalAwards=false
• 关键词: NSF; Convergence; Accelerator; Track; AI

Coordinated networked microgrids (NMs) promise to significantly enhance power grid reliability. Three main challenges prevent their wide adoption: 1) Lack of understanding of NM dynamics; 2) Big data but limited/unscalable analytics; 3) Cyber-infrastructure bottlenecks. This project aims to develop AI-Grid: AI-enabled, provably resilient NMs. Key innovations are a programmable platform integrating reliable modeling under uncertainty, reachability analysis, formal control, high-assurance software architectures, and cybersecurity technologies to enable scalable, autonomic, and ultra-resilient microgrids and NMs.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

协调的联网微电网（NM）有望显着提高电网的可靠性。三个主要挑战阻碍了它们的广泛采用：1）缺乏对NM动态的理解; 2）大数据但有限/不可扩展的分析; 3）网络基础设施瓶颈。 该项目旨在开发AI-Grid：支持AI的，可证明具有弹性的NM。主要创新是一个可编程平台，集成了不确定性下的可靠建模、可达性分析、正式控制、高保证软件架构和网络安全技术，以实现可扩展、自主和超弹性的微电网和NM。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响评审标准进行评估，被认为值得支持。

项目成果

The Black-Box Simplex Architecture for Runtime Assurance of Autonomous CPS

• DOI: 10.1007/978-3-031-06773-0_12
• 发表时间: 2021-02
• 作者: Usama Mehmood;S. Sheikhi;Stanley Bak;S. Smolka;S. Stoller

A distributed simplex architecture for multi-agent systems

多智能体系统的分布式单纯形体系结构

• DOI: 10.1016/j.sysarc.2022.102784
• 发表时间: 2023
• 期刊: Journal of Systems Architecture
• 影响因子: 4.5
• 作者: Mehmood, Usama;Roy, Shouvik;Damare, Amol;Grosu, Radu;Smolka, Scott A.;Stoller, Scott D.
• 通讯作者: Stoller, Scott D.

Computationally Distributed and Asynchronous Operational Optimization of Droop-Controlled Networked Microgrids

下垂控制网络微电网的计算分布式异步运行优化

• DOI: 10.1109/oajpe.2022.3188733
• 发表时间: 2022
• 期刊: IEEE Open Access Journal of Power and Energy
• 影响因子: 3.8
• 作者: Nikmehr, Nima;Bragin, Mikhail A.;Zhang, Peng;Luh, Peter B.
• 通讯作者: Luh, Peter B.

Efficient Operations of Micro-Grids with Meshed Topology and Under Uncertainty through Exact Satisfaction of AC-PF, Droop Control and Tap-Changer Constraints

• DOI: 10.3390/en15103662
• 发表时间: 2022-05
• 期刊: Energies
• 影响因子: 3.2
• 作者: Mikhail A. Bragin;B. Yan;Akash Kumar;N. Yu;P. Zhang

Novel Resolution of Unit Commitment Problems Through Quantum Surrogate Lagrangian Relaxation

通过量子替代拉格朗日弛豫新解决单位承诺问题

• DOI: 10.1109/tpwrs.2022.3181221
• 发表时间: 2022
• 期刊: IEEE Transactions on Power Systems
• 影响因子: 6.6
• 作者: Feng, Fei;Zhang, Peng;A. Bragin, Mikhail;Zhou, Yifan
• 通讯作者: Zhou, Yifan