Advancing Phasor Measurement Unit (PMU) Technology
先进的相量测量单元 (PMU) 技术
基本信息
- 批准号:1232305
- 负责人:
- 金额:$ 36万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2012
- 资助国家:美国
- 起止时间:2012-11-15 至 2016-10-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Research Objectives and Approaches:The objective of this research is to develop effective, efficient, and practical algorithms for phasor measurement unit operation and application. The approach is to: 1) develop the next generation phasor measurement unit with novel signal modeling and processing to enable both static and dynamic analysis; 2) gain a thorough understanding of bad phasor data processing by exploring methods of bad data identification and removal; 3) establish a theoretical framework to explicitly deal with bad data using statistical inference and compressive sensing; and 4) identify from simulation where our methods bring improved situational awareness, and verify with field data.Intellectual Merit:The gap between the current state of the art in phasor measurement units and their envisioned capability calls for advanced technology beyond today?s industry standards. This research proposal will contribute to this endeavor by developing novel signal processing techniques tailored for thephasor measurement unit and its applications. Successful development of the algorithms will also have impact on a number of fundamental problems of synchronization and anomaly detection in signal processing.Broader Impacts:In the U.S., power interruptions cost up to $135 billion each year. A main cause is inadequate situational awareness. With the proposed advancement, the next generation phasor measurement units will provide a picture of grid conditions that is truly accurate, anytime, and everywhere. Besides integrating research issues into our curriculum, special efforts will be made to enrich graduate student training with industrial internships, and to recruit and retain women and underprivileged students.
研究目标与方法:本研究的目的是为相量测量单元的操作和应用开发有效、高效和实用的算法。方法是:1)开发具有新颖信号建模和处理的下一代相量测量单元,以实现静态和动态分析;2)深入了解坏相量数据处理,探索坏相量数据识别和去除方法;3)建立理论框架,利用统计推理和压缩感知明确处理不良数据;4)从模拟中识别出我们的方法在哪些方面提高了态势感知能力,并通过现场数据进行验证。知识价值:相量测量单元的当前技术状态与其设想的能力之间的差距要求超越今天的先进技术?美国行业标准。本研究计划将通过开发适合相量测量单元及其应用的新型信号处理技术来促进这一努力。这些算法的成功开发也将对信号处理中的同步和异常检测等一些基本问题产生影响。更广泛的影响:在美国,电力中断每年造成的损失高达1350亿美元。一个主要原因是对形势的认识不足。随着提出的进步,下一代相量测量单元将提供一个真正准确的网格条件的图片,随时随地。除了将研究问题纳入我们的课程外,我们将特别努力以工业实习丰富研究生培训,并招募和留住女性和贫困学生。
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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Liuqing Yang其他文献
On the Optimality of Data-Aided Coarse Timing With Dirty Templates
脏模板数据辅助粗定时的最优性
- DOI:
10.1109/tvt.2013.2288949 - 发表时间:
2014-05 - 期刊:
- 影响因子:6.8
- 作者:
Wenshu Zhang;Liuqing Yang;Xiang Cheng;Wei Zang - 通讯作者:
Wei Zang
Wireless Body Area Networks for Healthcare: A Feasibility Study
用于医疗保健的无线体域网:可行性研究
- DOI:
- 发表时间:
2009 - 期刊:
- 影响因子:0
- 作者:
Bo Yu;Liuqing Yang - 通讯作者:
Liuqing Yang
Aromatic Oligoamide Macrocycles from Bimolecular Coupling of Folded Oligomeric Precursors
来自折叠寡聚前体双分子偶联的芳香族寡酰胺大环化合物
- DOI:
- 发表时间:
- 期刊:
- 影响因子:3.3
- 作者:
Kazuhiro Yamato;Xiao Cheng Zeng;Lihua Yuan;Xiaheng Zhang;Bing Gong;Lijian Zhong;Pengchi Deng;Liuqing Yang;Wen Feng - 通讯作者:
Wen Feng
Graph-Based File Dispatching Protocol With D2D-Enhanced UAV-NOMA Communications in Large-Scale Networks
大规模网络中基于图的文件调度协议和 D2D 增强型 UAV-NOMA 通信
- DOI:
10.1109/jiot.2020.2994549 - 发表时间:
2020-09 - 期刊:
- 影响因子:10.6
- 作者:
Baoji Wang;Rongqing Zhang;Chen Chen;Xiang Cheng;Liuqing Yang;Hang Li;Ye Jin - 通讯作者:
Ye Jin
Cooperative Jamming via Spectrum Sharing for Secure UAV Communications
通过频谱共享进行协作干扰以实现安全的无人机通信
- DOI:
10.1109/lwc.2019.2953725 - 发表时间:
2020-03 - 期刊:
- 影响因子:6.3
- 作者:
Yupeng Li;Rongqing Zhang;Jianhua Zhang;Liuqing Yang - 通讯作者:
Liuqing Yang
Liuqing Yang的其他文献
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{{ truncateString('Liuqing Yang', 18)}}的其他基金
CPS: Medium: Collaborative Research: Collective Intelligence for Proactive Autonomous Driving (CI-PAD)
CPS:中:协作研究:主动自动驾驶集体智慧 (CI-PAD)
- 批准号:
1932413 - 财政年份:2019
- 资助金额:
$ 36万 - 项目类别:
Standard Grant
Hybrid mmWave mMIMO Transceiver Design for Doubly-Selective Channels
适用于双选通道的混合毫米波 mMIMO 收发器设计
- 批准号:
1935915 - 财政年份:2019
- 资助金额:
$ 36万 - 项目类别:
Standard Grant
Collaborative Research: EARS: Large-Scale Statistical Learning based Spectrum Sensing and Cognitive Networking
合作研究:EARS:基于大规模统计学习的频谱感知和认知网络
- 批准号:
1343189 - 财政年份:2014
- 资助金额:
$ 36万 - 项目类别:
Standard Grant
CAREER: ACOustic Underwater Sensor NETwork (ACOUSNET) -- Multi-Level Adaptations
职业:声学水下传感器网络(ACOUSNET)——多级适应
- 批准号:
1129043 - 财政年份:2010
- 资助金额:
$ 36万 - 项目类别:
Continuing Grant
CAREER: ACOustic Underwater Sensor NETwork (ACOUSNET) -- Multi-Level Adaptations
职业:声学水下传感器网络(ACOUSNET)——多级适应
- 批准号:
0845722 - 财政年份:2009
- 资助金额:
$ 36万 - 项目类别:
Continuing Grant
Efficient MIMO Transceivers Based on Channel Decomposition Techniques
基于信道分解技术的高效 MIMO 收发器
- 批准号:
0621879 - 财政年份:2006
- 资助金额:
$ 36万 - 项目类别:
Standard Grant
相似海外基金
Secure State Estimation in Smart Grids via Phasor Measurement Units
通过相量测量单元进行智能电网的安全状态估计
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527762-2018 - 财政年份:2018
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Amplifier Interface Design for Real-Time Simulation of Phasor Measurement Unit
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- 批准号:
484335-2015 - 财政年份:2015
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Monitoring and controlling of power systems using phasor measurement data
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- 批准号:
249606-2011 - 财政年份:2014
- 资助金额:
$ 36万 - 项目类别:
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