CPS: DFG Joint: Medium: Collaborative Research: Data-Driven Secure Holonic control and Optimization for the Networked CPS (aDaptioN)

CPS：DFG 联合：媒介：协作研究：网络 CPS 的数据驱动安全完整控制和优化 (aDaptioN)

• 批准号: 1932406
• 负责人: Anuradha Annaswamy
• 金额: $ 22.2万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1932406&HistoricalAwards=false
• 关键词: CPS; DFG; Joint; Medium; Collaborative

The proposed decentralized/distributed control and optimization for the critical cyber-physical networked infrastructures (CPNI) will improve the robustness, security and resiliency of the electric distribution grid, which directly impacts the life of citizens and national economy. The proposed control and optimization architectures are flexible, adapt to changing operating scenarios, respond quickly and accurately, provide better scalability and robustness, and safely operate the system even when pushed towards the edges by leveraging massive sensor data, distributed computation, and edge computing. The algorithms and platform will be released open source and royalty-free and the project team will work with industry members and researchers for wider usage of the developed algorithms for other CPNI. Developed artifacts as part of the proposed work will be integrated in existing undergraduate and graduate related courses. Undergraduate students will be engaged in research through supplements and underrepresented and pre-engineering students will be engaged through existing outreach activities at home institutions including Imagine U program and 4-H Teens summer camp programs and the Pacific Northwest Louis Stokes Alliance for Minority Participations. Additionally, project team plans to organize a workshop in the third year to demonstrate the fundamental concepts and applications of the proposed control and optimization architecture to advance CPNI. Developed solutions can be extended for range of applications in multiple CPNIs beyond use cases discussed in the proposed work.While the proposed control architecture with edge computing offer great potential; coordinating decentralized control and optimization is extremely challenging due to variable network and computational delays, several interleavings of message arrivals, disparate failure modes of components, and cyber security threats leading to several fundamental theoretical problems. Proposed work offers number of novel solutions including (a) adaptive and delay-aware control algorithms, (b) Predictive control and distributed optimization with realistic cyber-physical constraints, (c) threat sharing, data-driven detection and mitigation for cyber security, (d) coordination and management of computing nodes, (e) knowledge learning and sharing. Proposed solutions will be a step towards advancing fundamentals in CPNI and in engineering next generation CPNI. The proposed work also aims to use high fidelity testbed to evaluate developed algorithms and tools for specific CPNI: electric distribution grid.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.

拟议的对关键网络物理网络基础设施（CPNI）的分散/分布式控制和优化将提高电力电网的鲁棒性，安全性和弹性，这直接影响公民和国民经济的生活。所提出的控制和优化体系结构是灵活的，适应了不断变化的操作场景，快速，准确地响应，提供更好的可扩展性和鲁棒性，并通过利用大量传感器数据，分布式计算和边缘计算来朝着边缘进行安全操作。该算法和平台将发布开源和免版税，项目团队将与行业成员和研究人员合作，以更广泛的使用，以更广泛地使用其他CPNI的开发算法。作为拟议工作的一部分，开发的工件将集成到现有的本科和研究生相关课程中。本科生将通过补充剂进行研究，而代表性不足和工程学的学生将通过在家庭机构中的现有外展活动进行参与，包括Imagine U计划和4-H青少年夏令营计划以及西北太平洋西北路易斯·斯托克斯联盟（Pacific Northwest Louis Stokes Alliance）参加少数派参与。 此外，项目团队计划在第三年组织研讨会，以展示拟议的控制和优化体系结构的基本概念和应用，以推动CPNI。可以扩展开发的解决方案，以扩展针对拟议工作中讨论的多个CPNI的应用范围。虽然提出的带有边缘计算的控制架构具有巨大的潜力；由于可变的网络和计算延迟，消息到达的几个交织，组件的不同故障模式以及网络安全威胁导致了几个基本理论问题，因此协调分散的控制和优化非常具有挑战性。拟议的工作提供了许多新颖的解决方案，包括（a）自适应和延迟感受的控制算法，（b）预测性控制和分布式优化，并具有现实的网络物理约束，（c）威胁共享，数据驱动的检测和缓解网络安全性，（d）计算节点的协调和管理，（d）计算节点的协调和管理，（e）知识学习。拟议的解决方案将是迈向CPNI和工程下一代CPNI的基础知识的一步。拟议的工作还旨在使用高保真测试床来评估特定CPNI的已发达算法和工具：电力分销网格。该奖项反映了NSF的法定任务，并认为使用基金会的智力优点和更广泛影响的审查标准，认为值得通过评估来获得支持。

项目成果

Distributed Frequency Divider-based Model Predictive Control for Frequency Control of Multi-Area Power Systems

• DOI: 10.1109/smartgridcomm57358.2023.10333904
• 发表时间: 2023-10
• 期刊: 2023 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)
• 作者: Tobias Heins;Paula Chanfreut;S. Gurumurthy;Priyank Srivastava;Antonello Monti;Anuradha M. Annaswamy

Flattening the Duck Curve: A Case for Distributed Decision Making

压平鸭子曲线：分布式决策的案例

• DOI: 10.1109/pesgm48719.2022.9917019
• 发表时间: 2022
• 期刊: 2022 IEEE Power & Energy Society General Meeting (PESGM
• 作者: Haider, Rabab;Ferro, Giulio;Robba, Michela;Annaswamy, Anuradha M.
• 通讯作者: Annaswamy, Anuradha M.

Accelerated Algorithms for a Class of Optimization Problems with Equality and Box Constraints

一类具有等式和框约束的优化问题的加速算法

• DOI: 10.23919/acc55779.2023.10156180
• 发表时间: 2023
• 期刊: IEEE
• 作者: Parashar, Anjali;Srivastava, Priyank;Annaswamy, Anuradha M.
• 通讯作者: Annaswamy, Anuradha M.

Voltage regulation in distribution grids: A survey

• DOI: 10.1016/j.arcontrol.2023.03.008
• 发表时间: 2023-03
• 期刊: Annu. Rev. Control.
• 作者: P. Srivastava;R. Haider;V. Nair;V. Venkataramanan;Anuradha M. Annaswamy;A. Srivastava

Distributed operational management of microgrids: a second order dual update approach

• DOI: 10.1016/j.ifacol.2023.10.1851
• 发表时间: 2023
• 期刊: IFAC-PapersOnLine
• 作者: G. Ferro;M. Robba;Federico Delfino;R. Haider;Anuradha M. Annaswamy