Collaborative Research: Wind Power - Neural Network Control, Multidisciplinary Integration, and Advanced Simulation
Collaborative Research: Wind Power - Neural Network Control, Multidisciplinary Integration, and Advanced Simulation
批准号:
1102038
负责人:
Shuhui Li
金额:
$18.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-08-01 至 2014-07-31
中文摘要
本研究的目标是利用自适应动态规划神经控制机制开发智能矢量控制技术、智能风电提取和管理策略以及先进的仿真和测试机制。这将提高风能转换系统的效率和可靠性,并为美国2030年20%的透风率愿景加强风电并入电力公用事业系统的能力。智能优点本研究的智力优点包括:1)自适应动态规划矢量控制技术,以克服传统矢量控制技术的不足;2)智能风电提取和管理技术,以提高风力发电的效率和可靠性;3)实际系统约束下的智能控制集成策略;4)先进的仿真和测试机制;5)智能可持续能源系统课程,以提高学生在多学科领域的能力。可持续能源系统的快速发展和复杂性的增加,使得开发智能化和网络化的技术用于可持续能源系统领域的研究和教育变得越来越迫切。这项研究将加强未来智能和可持续能源系统的优化和智能技术,并增加EPSCoR国家对先进科学研究的参与。这项研究应该对美国的以下任务区产生直接或间接的影响:减少进口能源,减少与能源有关的排放,提高能源效率,以及在先进能源技术方面引领美国的技术。
英文摘要
The objective of this research is to develop intelligent vector control technology, intelligent wind power extraction and management strategy, and advanced simulation and testing mechanisms by using Adaptive Dynamic Programming neural control mechanisms. This will improve the efficiency and reliability of wind energy conversion systems and enhance wind power integration into the electric utility system for the 20% wind penetration vision of the United States in 2030. INTELLECTUAL MERITS The intellectual merits of this research include development of: 1) Adaptive Dynamic Programming vector control technology to overcome the deficiency of conventional vector control technology, 2) intelligent wind power extraction and management techniques to improve wind power production efficiency and reliability, 3) intelligent control integration strategy under practical system constraints, 4) advanced simulation and testing mechanisms, and 5) a curriculum in Intelligent Sustainable Energy Systems to enhance student capability in multidisciplinary fields.BROADER IMPACTSThe broader impacts of this research are significant. The rapid development and increased complexities of sustainable energy systems make it increasingly urgent to develop intelligent and cyber-enabled technologies for research and education of sustainable energy system field. This research will enhance optimal and intelligent technology for future smart and sustainable energy systems and increase the participation of an EPSCOR state in advanced scientific research. The research should have direct or indirect impacts to the following mission areas of the United States: reduction in imported energy, reduction of energy-related emissions, improvements in energy efficiency, and a technological lead for the United States in advanced energy techniques.
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PFI-RP: Development of Novel Inverter Technologies and Prototypes for Enhanced Power Generation from Renewable Energy Resources
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批准号:2141067
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项目类别:Standard Grant
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资助金额:$55.0万
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财政年份:2022
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负责人:Shuhui Li
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依托单位:
I-Corps: Approximate Dynamic Programming and Artificial Neural Network Control for Microgrids
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资助金额:$5.0万
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PFI:AIR - TT: Toward Commercialization: Development of Neural Network Control and Power Converter Prototype for Renewables and Smart Grid Integration
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批准号:1414379
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资助金额:$19.99万
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财政年份:2014
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依托单位:
II-New: Modern Computing Infrastructure for Research and Education of Future Smart and Renewable Energy Systems
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批准号:1059265
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项目类别:Standard Grant
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资助金额:$47.57万
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财政年份:2011
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负责人:Shuhui Li
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批准号:0311145
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项目类别:Standard Grant
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资助金额:$7.59万
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财政年份:2003
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负责人:Shuhui Li
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依托单位:
国内基金
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