I-Corps: Approximate Dynamic Programming and Artificial Neural Network Control for Microgrids
I-Corps:微电网的近似动态规划和人工神经网络控制
基本信息
- 批准号:1744159
- 负责人:
- 金额:$ 5万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2017
- 资助国家:美国
- 起止时间:2017-07-01 至 2020-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The broader impact/commercial potential of this I-Corps project is to act as a catalyst in the growth of distributed generation and microgrid industries. This artificial intelligence based control system will potentially provide an electrical network that is reliable by reducing outages and restoration costs with incredibly fast bidirectional power flow, secured with real time diagnostics, self-healing and adaptive capabilities, and more economical by reducing equipment failures and minimizing power losses. The product potentially three broad markets, including utilities, distributed generation and consumer. The solution will enhance energy generation from renewables, improve microgrid efficiency, reliability, stability and power quality, and add intelligent control to conventional power systems. Inverter capabilities are presently a significant challenge for integrating distributed generation sources. The proposed innovation would potentially provide an appropriate solution to address this challenge.This I-Corps project develops a neural network control technology for microgrid control and management. Microgrids are one path for integrating renewable and distributed generation sources into the grid and can generally support a future smart electricity grid. A key challenge in microgrid adoption is adequate control of power inverters. Problems include high oscillations when connecting or disconnecting an energy source, fluctuating voltage and frequency, malfunctions and reliability, competing control between inverters, and high harmonic distortions. The proposed innovation uses adaptive dynamic programming and artificial neural networks to implement microgrid control. It integrates into one controller the advantages of conventional control methods, including optimal control, proportional integral control, predictive control, and sliding mode control. The proposed innovation has the potential to overcome the limitations of the conventional control technologies and better meet customer demands and requirements.
这个I-Corps项目更广泛的影响/商业潜力是作为分布式发电和微电网行业增长的催化剂。这种基于人工智能的控制系统将潜在地提供一种电网,该电网通过以令人难以置信的快速双向功率流减少停电和恢复成本而可靠,通过真实的时间诊断、自我修复和自适应能力而安全,并且通过减少设备故障和最小化功率损耗而更经济。该产品潜在的三个广阔的市场,包括公用事业,分布式发电和消费。该解决方案将增强可再生能源的发电能力,提高微电网的效率、可靠性、稳定性和电能质量,并为传统电力系统增加智能控制。逆变器能力目前是集成分布式发电源的重大挑战。该项目为微电网的控制和管理开发了一种神经网络控制技术。微电网是将可再生能源和分布式发电资源整合到电网中的一种途径,通常可以支持未来的智能电网。 微电网采用的一个关键挑战是对功率逆变器的充分控制。问题包括连接或断开电源时的高振荡、波动的电压和频率、故障和可靠性、逆变器之间的竞争控制以及高谐波失真。所提出的创新使用自适应动态规划和人工神经网络来实现微电网控制。它集成到一个控制器的传统控制方法,包括最优控制,比例积分控制,预测控制和滑模控制的优点。提出的创新有可能克服传统控制技术的局限性,更好地满足客户的需求和要求。
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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Shuhui Li其他文献
Quantitative Modeling and Decoupling Method for Assembly Deformation Analysis Considering Residual Stress from Manufacturing Process
考虑制造过程残余应力的装配变形分析定量建模与解耦方法
- DOI:
10.1061/(asce)as.1943-5525.0000400 - 发表时间:
2015-05 - 期刊:
- 影响因子:2.4
- 作者:
Lina Zhang;Hua Wang;Shuhui Li;Zhongqin Lin - 通讯作者:
Zhongqin Lin
An optimal trajectory planning method for path tracking of industrial robots
工业机器人路径跟踪的最优轨迹规划方法
- DOI:
10.1017/s0263574718001145 - 发表时间:
2018-10 - 期刊:
- 影响因子:2.7
- 作者:
Xianxi Luo;Shuhui Li;Shubo Liu;Guoquan Liu - 通讯作者:
Guoquan Liu
Dynamic P-Q Capability and Abnormal Operation Analysis of a Wind Turbine With Doubly Fed Induction Generator
双馈感应发电机风电机组的动态P-Q能力及异常运行分析
- DOI:
10.1109/jestpe.2021.3133527 - 发表时间:
2022 - 期刊:
- 影响因子:5.5
- 作者:
Bing Lu;Shuhui Li;H. Das;Yixiang Gao;Jing Wang;M. Baggu - 通讯作者:
M. Baggu
Design of Logarithmic-Index Fiber for Orbital Angular Momentum (OAM)Transmission
用于轨道角动量(OAM)传输的对数折射率光纤设计
- DOI:
10.1364/cleopr.2018.w3a.100 - 发表时间:
2018 - 期刊:
- 影响因子:0
- 作者:
Pei;Shuhui Li;Zhe Xu;Ruixuan Zhao;L. Shen;Jian Wang - 通讯作者:
Jian Wang
Demonstration of a Visible-Light Communication Link Employing High-Base Vector Beam Modulation/Demodulation
采用高基矢量光束调制/解调的可见光通信链路演示
- DOI:
10.1364/acpc.2014.af4b.8 - 发表时间:
2014 - 期刊:
- 影响因子:0
- 作者:
Yifan Zhao;Jing Du;Shuhui Li;Jun Liu;Long Zhu;Jian Wang - 通讯作者:
Jian Wang
Shuhui Li的其他文献
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{{ truncateString('Shuhui Li', 18)}}的其他基金
PFI-RP: Development of Novel Inverter Technologies and Prototypes for Enhanced Power Generation from Renewable Energy Resources
PFI-RP:开发新型逆变器技术和原型以增强可再生能源发电
- 批准号:
2141067 - 财政年份:2022
- 资助金额:
$ 5万 - 项目类别:
Standard Grant
PFI:AIR - TT: Toward Commercialization: Development of Neural Network Control and Power Converter Prototype for Renewables and Smart Grid Integration
PFI:AIR - TT:迈向商业化:开发用于可再生能源和智能电网集成的神经网络控制和电源转换器原型
- 批准号:
1414379 - 财政年份:2014
- 资助金额:
$ 5万 - 项目类别:
Standard Grant
II-New: Modern Computing Infrastructure for Research and Education of Future Smart and Renewable Energy Systems
II-新:用于未来智能和可再生能源系统研究和教育的现代计算基础设施
- 批准号:
1059265 - 财政年份:2011
- 资助金额:
$ 5万 - 项目类别:
Standard Grant
Collaborative Research: Wind Power - Neural Network Control, Multidisciplinary Integration, and Advanced Simulation
合作研究:风电-神经网络控制、多学科集成和高级仿真
- 批准号:
1102038 - 财政年份:2011
- 资助金额:
$ 5万 - 项目类别:
Standard Grant
Course Restructuring and Laboratory Development in Power Electronics and Electric Drives
电力电子与电力驱动课程重组与实验室建设
- 批准号:
0311145 - 财政年份:2003
- 资助金额:
$ 5万 - 项目类别:
Standard Grant
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