Integrated Power Grid and Microgrids with Massively Distributed Intelligent Sensors

具有大规模分布式智能传感器的综合电网和微电网

• 批准号: 1807974
• 负责人: Zhixin Miao
• 金额: $ 39.73万
• 依托单位: University of South Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-15 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1807974&HistoricalAwards=false
• 关键词: Integrated; Power; Grid; Microgrids; Massively

AbstractImproving the reliability of the electric power grid is one of the critical challenges facing the nation. To meet this challenge, we believe that the Intelligent Sensors and Analyzers advanced technology proposed here can begin to transform our power grid and its affiliated microgrids to a Next-Generation-Smart-Grid. It could also enhance our power and energy sustainability and restorability in severely adverse weather conditions. It has the potential of starting a new revolution in creating intelligent Power Grid and Microgrids by extending todays microchip technology to integrated multi-sensing and information processing in a single compact device -- specialized for Power and Energy arena. Advanced sensor models integrated with Power Grid and Microgrids models will be developed for achieving the true potential of the intelligent sensors and analyzers (proposed herein) that would be deployable on a massive scale. The project will also promote teaching, training and learning in this key technology area. Specifically, the sensors, process-flow, and specialized microchip design activity of the project will be imported into the undergraduate senior-design projects. The project will also significantly benefit several graduate courses including a new course on Smart Power Grids, and existing courses on Micro-Electro-Mechanical-Systems II, and System on a Chip. The advances will be shared with the power and energy industry, government, and academia through a dedicated web site and, of course, through scientific publications.As stated above, the goal of this project is to improve the reliability and restoration capability of wide area Power Grid as well as its affiliated Microgrids thereby reducing power outages and their cascade effects. Our solution is to embed novel intelligent sensors with distributed processing tools to provide real time monitoring and control of "Power Grid as well as its affiliated Microgrids" from transmission and distribution levels. The problems associated with the present lack of a real time intelligent infrastructure to monitor and control Power Grids -- on a massively distributed basis, have resulted in numerous blackouts and other serious inefficiencies. Our sensors/analyzers will provide accurate information to protective relays, enable intelligent islanding, a means by which the modeling of loads can be based upon accurate measured data rather than estimated data, for load shedding plans. The unique sensor architecture, fabrication, and signal processing issues will be addressed through an advanced Heterogeneous Sensor System on a Chip. As just stated, included will be Microgrids, in which the focus will be on islanding and restoration, sensors, estimation of key variables (frequency, phase and amplitude -- for harmonics as well when desired), defect and fault tolerance, thereby reliability improvement. Microgrids incorporate renewable energy sources, among others. System on a Chip based sensors can provide effective, real-time monitoring and control that is self-healing, for such sources. In short, the main objectives are the following: (1) Multi-Sensor (including Micro-Electro-Mechanical-Systems) design, fab, and test, (2) Intelligence: analog and digital sections design, fab, test (for "Power Grid and Microgrids"), (3) Power Grid and Microgrids objectives: Fault detection, islanding, active & reactive power estimation, theoretical models & simulations, (4) Final Heterogeneous System on a Chip design, fabrication, tests; Also, tests in our Smart Grid Lab.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.

摘要提高电网的可靠性是国家面临的重大挑战之一。为了迎接这一挑战，我们相信，这里提出的智能传感器和分析仪先进技术可以开始将我们的电网及其附属微电网转变为下一代智能电网。它还可以增强我们的电力和能源的可持续性，以及在恶劣天气条件下的恢复能力。它有可能在创建智能电网和微电网方面开启一场新的革命，将当今的微芯片技术扩展到单个紧凑型设备中集成多传感器和信息处理--专门用于电力和能源领域。将开发与电网和微电网模型集成的先进传感器模型，以实现可大规模部署的智能传感器和分析仪(在此建议)的真正潜力。该项目还将促进这一关键技术领域的教学、培训和学习。具体来说，该项目的传感器、工艺流程和专业微芯片设计活动将被引入到本科高级设计项目中。该项目还将显著受益于几门研究生课程，包括一门关于智能电网的新课程，以及现有的关于微电子机械系统II和芯片上系统的课程。这些进展将通过专门的网站和科学出版物与电力和能源行业、政府和学术界分享。如上所述，该项目的目标是提高广域电网及其附属微电网的可靠性和恢复能力，从而减少停电及其级联影响。我们的解决方案是在分布式处理工具中嵌入新型智能传感器，从输电和配电两个层面对电网及其附属微电网进行实时监测和控制。与目前缺乏实时智能基础设施来监测和控制电网有关的问题--在大规模分布的基础上--已导致多次停电和其他严重的低效。我们的传感器/分析仪将为保护继电器提供准确的信息，实现智能孤岛，这是一种根据准确的测量数据而不是估计数据对负荷进行建模的方法，用于负荷削减计划。独特的传感器架构、制造和信号处理问题将通过先进的异类传感器芯片系统来解决。如上所述，将包括微电网，重点将放在孤岛和恢复、传感器、关键变量(频率、相位和幅度--如果需要的话--也包括谐波)的估计、缺陷和容错，从而提高可靠性。微电网结合了可再生能源和其他能源。基于片上系统的传感器可以为这类信号源提供有效的、实时的、自我修复的监测和控制。简而言之，主要目标是：(1)多传感器(包括微电子机械系统)的设计、制造和测试；(2)智能：模拟和数字部分的设计、制造和测试(用于“电网和微电网”)；(3)电网和微电网的目标：故障检测、孤岛、有源和无功功率估计、理论模型和仿真；(4)最终的异质片上系统设计、制造和测试；此外，我们智能电网实验室的测试。这一奖项反映了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

Mechanism Analysis of Wind Turbine Var Oscillations

风电机组无功振荡机理分析

• DOI: 10.1109/tie.2022.3224198
• 发表时间: 2022
• 期刊: IEEE Transactions on Industrial Electronics
• 影响因子: 7.7
• 作者: Fan, Lingling;Miao, Zhixin;Shah, Shahil
• 通讯作者: Shah, Shahil

DQ Admittance Model Extraction for IBRs via Gaussian Pulse Excitation

通过高斯脉冲激励提取 IBR 的 DQ 导纳模型

• DOI: 10.1109/tpwrs.2023.3256119
• 发表时间: 2023
• 期刊: IEEE Transactions on Power Systems
• 影响因子: 6.6
• 作者: Fan, Lingling;Miao, Zhixin;Bao, Li;Shah, Shahil;Ramakrishna, Rahul H.
• 通讯作者: Ramakrishna, Rahul H.

Piezoelectric Lateral-Extensional Mode Resonators With Reconfigurable Electrode and Resonance Mode-Switching Behavior Enabled by a VO₂ Thin-Film

压电横向延伸模式谐振器，具有可重构电极和由 VO™ 薄膜实现的谐振模式切换行为

• DOI: 10.1109/tuffc.2022.3156845
• 发表时间: 2023
• 期刊: and Frequency Control
• 作者: Liu, Ting Hung;Han, Xu;Pastrana, Juan;Sepulveda, Nelson;Wang, Jing
• 通讯作者: Wang, Jing

Fault Tolerance for Islandable-Microgrid Sensors

孤岛微电网传感器的容错

• DOI: 10.1109/dft52944.2021.9568353
• 发表时间: 2021
• 期刊: IEEE
• 作者: Jain, Vijay K.;Chapman, Glenn H.
• 通讯作者: Chapman, Glenn H.

Realization of Enhanced Phase Locked Loop using Raspberry Pi and LabVIEW

使用Raspberry Pi和LabVIEW实现增强型锁相环

• DOI: 10.1109/naps46351.2019.9000278
• 发表时间: 2019
• 期刊: IEEE
• 作者: Kolla, Rama;Wang, Zhengyu;Miao, Zhixin;Fan, Lingling
• 通讯作者: Fan, Lingling