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: $ 24万
• 依托单位: Georgia Tech Research Corporation
• 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
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0524183&HistoricalAwards=false
• 关键词: Integrated; Control; Wind; Farms; Facts

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。