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

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
批准号:
0524183
负责人:
Ronald Harley
金额:
$24.0万
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
项目状态:
已结题
起止时间:
2005-08-01 至 2009-07-31

项目摘要

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中文摘要
翻译
智力优势:在早期小型系统成功的基础上,该团队将使用类似大脑的设计原则开发通用集成控制系统,以处理比过去使用此类原则控制的更大、更复杂的系统。他们将把自适应动态编程(有时被称为“强化学习”或“自适应批评”)、递归神经网络(在逼近非线性动态系统方面提供独特能力)、学习和适应以及粒子群优化技术的使用结合起来。他们将在管理一个由部分观察到的连续变量、非线性和随机干扰主导的大型复杂真实系统(最初在计算机模拟中,然后在实验室中)的背景下开发这种集成。更广泛的好处:要控制的试验台代表使用最先进、负担得起和高效(但很难管理)的风力涡轮机和电子功率控制硬件(FACTS)系统的大型风电场。以低成本实现如此可靠的控制和效率的能力,对于实现世界上20%的电力来自风能的目标至关重要。在一个合理的市场体系中,让风能等间歇性电力对电网更有价值,从而更值得从电网向风力发电机支付更大的费用,这将是至关重要的。该团队还与非洲和巴西建立了积极的合作伙伴关系,巴西可以提供取得成功所需的一些先进的低成本FACTS技术--或许还会提供一些额外的试验床。该项目可能是将智能自适应电网的理想带入现实世界的关键一步。
英文摘要
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.
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Collaborative Research: Planning Grant: I/UCRC for Real-Time Intelligence for Smart Electric Grid Operations (RISE)
  • 批准号:
    1464603
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.15万
  • 财政年份:
    2015
  • 负责人:
    Ronald Harley
  • 依托单位:
Student Support for IEMDC 2013 Conference Participation. To be Held May 12-15,2013 in Chicago, IL.
  • 批准号:
    1338551
  • 项目类别:
    Standard Grant
  • 资助金额:
    $0.9万
  • 财政年份:
    2013
  • 负责人:
    Ronald Harley
  • 依托单位:
Collaborative Research: Computational Intelligence Methods For Dynamic Stochastic Optimization Of Smart Grid Operation With High Penetration Of Renewable Energy
  • 批准号:
    1232031
  • 项目类别:
    Standard Grant
  • 资助金额:
    $18.0万
  • 财政年份:
    2012
  • 负责人:
    Ronald Harley
  • 依托单位:
Sequence component models to calculate fault current contributions from wind generators
  • 批准号:
    1028546
  • 项目类别:
    Standard Grant
  • 资助金额:
    $15.32万
  • 财政年份:
    2010
  • 负责人:
    Ronald Harley
  • 依托单位:
国内基金
海外基金
Cortical control of internal state in the insular cortex-claustrum region