Collaborative Research: CISE-MSI: DP: CPS: Cyber Resilient 5G Enabled Virtual Power System for Growing Power Demand
协作研究:CISE-MSI:DP:CPS:支持网络弹性 5G 的虚拟电源系统,满足不断增长的电力需求
基本信息
- 批准号:2219701
- 负责人:
- 金额:$ 14.5万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-10-01 至 2025-09-30
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).The demand for clean power is on the rise globally. The United States Department of Energy has projected that the percentage of clean electricity generated by solar power will increase to 33% to compete with the ever-growing electricity demand in the United States (US) by the year 2050. To minimize the upgradation of the existing substation and source infrastructure, it is favorable to integrate a solar energy source aided with battery storage system at the distribution level. The combination of these energy sources can be managed efficiently to behave like a "single utility-scale power station”. This is the concept of Virtual Power Plant (VPP). This project aims to address the implementation of cyber-secure pole mounted solar and battery systems equipped with smart controllers to provide a framework to remotely control and optimize the system to provide a solution to the growing power demands. Furthermore, by employing and mentoring students from underrepresented backgrounds in STEM, this project will aim at bridging the gap in institutions across the US. It will train the next generation of scholars from minority serving universities and marginalized communities in the fields of cybersecurity, utilization of renewable resources, and machine learning to address the pressing problems of this age.The technical aspect of the project aims to design and implement a 5G-enabled, cyber resilient smart Artificial Intelligence (AI) based microinverter for a pole-mounted solar power system with an energy storage system connected to the low-voltage distribution networks to operate as a VPP. The data collected from the smart microinverter will be used to train a predictive model to better manage the system for improved performance. A secure and privacy-preserving 5G based communication protocol will allow uninterrupted and secure data flow between the photovoltaic and the battery system, the smart microinverter, and the Supervisory Control and Data Acquisition (SCADA) system. Hence, a security framework based on Machine Learning (ML) models will be designed and it will be based on prior cyber-attack datasets and will include continuous learning using the data collected from smart controllers and the SCADA system used to detect cyber-attacks and exploring mitigation solutions for 5G-enabled SCADA-controlled VPP network system. Guidelines and procedures will be designed to help secure the physical systems while ensuring privacy and data protection by alerting administrators regarding security compromises of the VPP network to mitigate the risks and attacks.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.
该奖项的全部或部分资金来自《2021年美国救援计划法案》(公法117-2)。全球对清洁能源的需求正在上升。美国能源部预测,到2050年,太阳能发电的清洁电力比例将增加到33%,以与美国日益增长的电力需求竞争。为了最大限度地减少现有变电站和电源基础设施的升级,在配电层面上集成太阳能电源和电池存储系统是有利的。这些能源的组合可以被有效地管理,就像一个“单一公用事业规模的发电站”一样。这就是虚拟发电厂的概念。该项目旨在解决配备智能控制器的网络安全杆装太阳能和电池系统的实施,以提供远程控制和优化系统的框架,从而为不断增长的电力需求提供解决方案。此外,通过聘用和指导STEM中代表性不足的学生,该项目将旨在弥合美国各地院校之间的差距。该项目将在网络安全、可再生资源利用和机器学习领域培训来自少数族裔服务大学和边缘化社区的下一代学者,以解决这个时代的紧迫问题。该项目的技术方面旨在设计和实现一种基于5G、具有网络弹性的智能人工智能(AI)微逆变器,用于杆装太阳能系统,该系统具有连接到低压配电网的储能系统,作为VPP运行。从智能微逆变器收集的数据将用于训练预测模型,以更好地管理系统,以提高性能。基于安全和隐私保护的5G通信协议将允许光伏和电池系统、智能微逆变器和监控和数据采集(SCADA)系统之间不间断和安全的数据流。因此,将设计一个基于机器学习(ML)模型的安全框架,该框架将基于先前的网络攻击数据集,并将包括使用从智能控制器和用于检测网络攻击的SCADA系统收集的数据进行持续学习,并为启用5G的SCADA控制的VPP网络系统探索缓解解决方案。指导方针和程序旨在通过提醒管理员注意VPP网络的安全危害来帮助确保物理系统的安全,同时确保隐私和数据保护,以减少风险和攻击。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Kanwalinderjit Kaur其他文献
Kanwalinderjit Kaur的其他文献
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{{ truncateString('Kanwalinderjit Kaur', 18)}}的其他基金
Collaborative Research:CISE-MSI:RCBP-RF:CNS:Orchestration of Network Slicing for 5G-Enabled IoT Devices Using Reinforcement Learning
合作研究:CISE-MSI:RCBP-RF:CNS:使用强化学习为支持 5G 的物联网设备进行网络切片编排
- 批准号:
2318634 - 财政年份:2023
- 资助金额:
$ 14.5万 - 项目类别:
Standard Grant
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- 批准号:10774081
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