CAREER: Scalable and Secure Control of Distributed Grid-Edge Resources for Enhanced Grid Reliability

职业：对分布式电网边缘资源进行可扩展且安全的控制，以增强电网可靠性

• 批准号: 2145408
• 负责人: Mingxi Liu
• 金额: $ 50.01万
• 依托单位: University of Utah
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-15 至 2027-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2145408&HistoricalAwards=false
• 关键词: CAREER; Scalable; Secure; Control; Distributed

The growing penetration of renewable energy brings unprecedented operational challenges to the modern power system, demanding additional power system flexibility to enhance grid reliability. This NSF CAREER project aims to bolster the nation’s grid decarbonization and energy security by developing a grid-edge resource (GER) management framework to increase power system flexibility. The project will bring transformative changes to GER management by overcoming three intertwined challenges, i.e., high scalability requirements, major privacy concerns, and surging cybersecurity risks. This will be achieved by synthesizing ideas from optimization, machine learning, statistics, and cryptology to establish an efficient, private, and secure GER control framework. The intellectual merits of the project include (1) developing a scalable framework that enables efficient cooperative control of heterogeneous GERs; (2) investigating privacy preservation measures for strongly coupled decentralized GER control; (3) investigating models, and detection and mitigation strategies of stealthy cyber-attacks that target at decentralized GER control algorithms. The broader impacts of the project include (1) unleashing heterogeneous GERs to enhance grid reliability and deepen grid decarbonization; (2) advancing the grid’s ability to integrate increasing amounts of renewable generation and GERs in a cost-effective, secure, and reliable way; (3) providing the industry with insight into developing new market products. The integrated education plan will spread control and power system concepts to youth-in-custody, K-12 students, and underrepresented groups, motivating them to pursue STEM education and careers. Existing GER control frameworks may fail in large-scale deployment because they invariably ignore scalability issues caused by network dimension and GER heterogeneity, lack efficient measures to protect GER owners’ privacy, and lack the understanding of stealthy for-purpose cyber-attacks. To advance the knowledge, this project will (1) develop new optimization, machine learning, and statistical tools to construct a GER control framework that is agnostic to GER type, scalable with respect to GER population and network dimension, and applicable for different grid services; (2) characterize privacy risks in GER management and develop cryptology-based and non-cryptology-based privacy-preserving decentralized optimization paradigms; (3) constitute cyber-attack vectors that leverage decentralized GER control algorithms for stealthy attack purposes, determine the detectability of those attacks, and develop corresponding detection and mitigation strategies.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.

可再生能源的渗透不断增长，为现代电力系统带来了前所未有的运营挑战，要求额外的电力系统灵活性以提高电网可靠性。这个NSF职业项目旨在通过开发网格边缘资源（GER）管理框架来增强电力系统的灵活性来增强美国的网格脱碳和能源​​安全。该项目将通过克服三个交织在一起的挑战，即高可伸缩性要求，主要隐私问题和激增的网络安全风险来为GER管理带来变革性的变化。这将通过综合优化，机器学习，统计和密码学来建立高效，私人和安全的GER控制框架来实现这一目标。该项目的智力优点包括（1）开发一个可扩展的框架，该框架能够有效地对异构GERS进行合作控制； （2）研究强烈耦合分散的GER控制的隐私准备措施； （3）研究模型以及针对分散的GER控制算法的隐身网络攻击的检测和缓解策略。该项目的更广泛影响包括（1）释放异质GER，以增强网格可靠性和加深电网脱碳； （2）推进电网以一种具有成本效益，安全和可靠的方式整合越来越多的可再生能源生成和GER的能力； （3）为行业提供开发新市场产品的洞察力。综合教育计划将把控制和电力系统的概念传播给年轻人，K-12学生和代表性不足的群体，激励他们购买STEM教育和职业。现有的GER控制框架可能会在大规模部署中失败，因为它们总是忽略由网络维度和GER异质性引起的可伸缩性问题，缺乏有效的措施来保护GER所有者的隐私，并且对目的网络攻击缺乏对隐身性的理解。为了促进知识，该项目将（1）开发新的优化，机器学习和统计工具，以构建不可知的GER类型的GER控制框架，相对于GER人群和网络维度可扩展，并适用于不同的网格服务； （2）表征GER管理中的隐私风险，并开发基于密码和基于非晶状体的基于隐私的隐私保护优化范式； （3）构成网络攻击向量，该向量利用分散的GER控制算法来实现隐形攻击目的，确定这些攻击的可检测性，并制定相应的检测和缓解策略。该奖项反映了NSF的法定任务，并认为通过基金会的知识优点和广泛的criperia criperia criperia criperia criperia criperia criptia criperia criperia rection the the奖励。

项目成果

Exploration of For-Purpose Decentralized Algorithmic Cyber Attacks in EV Charging Control

• DOI: 10.1109/isie51358.2023.10227968
• 发表时间: 2023-03
• 期刊: 2023 IEEE 32nd International Symposium on Industrial Electronics (ISIE)
• 作者: Mahan Fakouri Fard;XiangMin Hou;Mingxi Liu

Distributed Privacy-Preserving Electric Vehicle Charging Control Based on Secret Sharing

• DOI: 10.1016/j.epsr.2022.108357
• 发表时间: 2021-10
• 期刊: ArXiv
• 作者: X. Huo;Mingxi Liu

ADMM-Based Distributed DC Optimal Power Flow with Power Flow Control

• DOI: 10.1109/naps56150.2022.10012190
• 发表时间: 2022-10
• 期刊: 2022 North American Power Symposium (NAPS)
• 作者: Xinyang Rui;Mingxi Liu;M. Sahraei-Ardakani;T. Nudell

Multi-Agent Reinforcement Learning Based Electric Vehicle Charging Control for Grid-Level Services

• DOI: 10.1109/iecon49645.2022.9968587
• 发表时间: 2022-10
• 期刊: IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society
• 作者: Md Golam Dastgir;X. Huo;Mingxi Liu

Two-Level Decentralized-Centralized Control of Distributed Energy Resources in Grid-Interactive Efficient Buildings

并网互动高效建筑中分布式能源的两级分散-集中控制

• DOI: 10.1109/lcsys.2022.3230321
• 发表时间: 2023
• 期刊: IEEE Control Systems Letters
• 影响因子: 3
• 作者: Huo, Xiang;Dong, Jin;Cui, Borui;Liu, Boming;Lian, Jianming;Liu, Mingxi
• 通讯作者: Liu, Mingxi