Integrated Control of Wind Farms, Facts Devices and the Power Network Using Neural Networks and Adaptive Critic Designs

使用神经网络和自适应批评设计对风电场、事实设备和电力网络进行集成控制

基本信息

  • 批准号:
    0524183
  • 负责人:
  • 金额:
    $ 24万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2005
  • 资助国家:
    美国
  • 起止时间:
    2005-08-01 至 2009-07-31
  • 项目状态:
    已结题

项目摘要

Intellectual Merit: Building on earlier success with smaller systems, this team will develop general-purpose integrated control systems using brain-like design principles to handle larger and more complex systems than have been ever been controlled in the past using such principles. They will be integrating together the use of adaptive dynamic programming (sometimes called "reinforcement learning" or "adaptive critics"), recurrent neural networks (which provide unique capabilities in approximating nonlinear dynamical systems), learning and adaptation, and particle swarm optimization techniques. They will be developing this integration in the context of managing a large complex real system (initially in computer simulation, and then in the laboratory) dominated by partially observed continuous variables, nonlinearity and random disturbances.Broader benefits: The testbed to be controlled represents large windfarms using the most advanced, affordable and efficient (but hard to manage) systems of wind turbines and electronic power control hardware ("FACTS"). The ability to achieve such reliable control and efficiency, at low cost, will be crucial to the goal of supplying 20 percent of the world's electrical energy by wind. It will be crucial to making intermittent power like wind more valuable to the grid - and hence more deserving of larger payments from the grid to wind generators, in a rational market system. The team also has active partnerships with Africa and with Brazil, which can supply some of the advanced low-cost FACTS technology needed to achieve success - and perhaps also some additional testbeds. This project may be a crucial step in bring the ideals of an intelligent adaptive power grid into the real world.
智力优势:基于早期在小型系统上取得的成功,该团队将使用类脑设计原理开发通用集成控制系统,以处理比过去使用此类原理控制的更大,更复杂的系统。他们将整合使用自适应动态规划(有时称为“强化学习”或“自适应批评”),递归神经网络(提供近似非线性动态系统的独特能力),学习和适应以及粒子群优化技术。他们将在管理大型复杂的真实的系统的背景下开发这种集成(最初在计算机模拟中,然后在实验室中)由部分观测到的连续变量、非线性和随机干扰主导。被控制的试验台代表了使用最先进的,风力涡轮机和电子功率控制硬件(“FACTS”)的可负担且高效(但难以管理)的系统。以低成本实现这种可靠的控制和效率的能力,对于实现风能供应世界20%电能的目标至关重要。这对于使像风能这样的间歇性电力对电网更有价值至关重要--因此在一个理性的市场体系中,电网更应该向风力发电机支付更高的费用。该团队还与非洲和巴西建立了积极的合作伙伴关系,这些国家可以提供取得成功所需的一些先进的低成本FACTS技术,也许还可以提供一些额外的测试平台。这个项目可能是将智能自适应电网的理想带入真实的世界的关键一步。

项目成果

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Ronald Harley其他文献

Approximate dynamic programming based supplementary reactive power control for DFIG wind farm to enhance power system stability
基于近似动态规划的双馈风电场补充无功控制增强电力系统稳定性
  • DOI:
    10.1016/j.neucom.2015.03.089
  • 发表时间:
    2015-12
  • 期刊:
  • 影响因子:
    6
  • 作者:
    Guo Wentao;Feng Liu;Jennie Si;Dawei He;Ronald Harley;Shengwei Mei
  • 通讯作者:
    Shengwei Mei

Ronald Harley的其他文献

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{{ truncateString('Ronald Harley', 18)}}的其他基金

Collaborative Research: Planning Grant: I/UCRC for Real-Time Intelligence for Smart Electric Grid Operations (RISE)
合作研究:规划资助:I/UCRC 智能电网运营实时智能 (RISE)
  • 批准号:
    1464603
  • 财政年份:
    2015
  • 资助金额:
    $ 24万
  • 项目类别:
    Standard Grant
Student Support for IEMDC 2013 Conference Participation. To be Held May 12-15,2013 in Chicago, IL.
学生参与 IEMDC 2013 会议的支持。
  • 批准号:
    1338551
  • 财政年份:
    2013
  • 资助金额:
    $ 24万
  • 项目类别:
    Standard Grant
Collaborative Research: Computational Intelligence Methods For Dynamic Stochastic Optimization Of Smart Grid Operation With High Penetration Of Renewable Energy
合作研究:可再生能源高渗透智能电网运行动态随机优化的计算智能方法
  • 批准号:
    1232031
  • 财政年份:
    2012
  • 资助金额:
    $ 24万
  • 项目类别:
    Standard Grant
Sequence component models to calculate fault current contributions from wind generators
用于计算风力发电机故障电流贡献的序列组件模型
  • 批准号:
    1028546
  • 财政年份:
    2010
  • 资助金额:
    $ 24万
  • 项目类别:
    Standard Grant
GOALI: Neural Networks and Adaptive Critic Designs For Energy Security and Sustainability
GOALI:用于能源安全和可持续性的神经网络和自适应批评设计
  • 批准号:
    0802047
  • 财政年份:
    2008
  • 资助金额:
    $ 24万
  • 项目类别:
    Standard Grant
Neural Networks for Estimating and Compensating the Nonlinear Characteristics of Nonstationary Complex Systems
用于估计和补偿非平稳复杂系统非线性特性的神经网络
  • 批准号:
    0601521
  • 财政年份:
    2006
  • 资助金额:
    $ 24万
  • 项目类别:
    Standard Grant
Planning visit to Mexico: Intelligent Techniques to Operation, Control and Diagnosis of Power Plants and Power Systems Including FACTS Devices
计划访问墨西哥:包括FACTS设备在内的发电厂和电力系统的运行、控制和诊断的智能技术
  • 批准号:
    0519161
  • 财政年份:
    2005
  • 资助金额:
    $ 24万
  • 项目类别:
    Standard Grant
Workshop on Global Dynamic Optimization of the Electric Power Grid in Atlanta, GA
佐治亚州亚特兰大电网全球动态优化研讨会
  • 批准号:
    0224592
  • 财政年份:
    2002
  • 资助金额:
    $ 24万
  • 项目类别:
    Standard Grant

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