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.

智力优点：基于较小系统的早期成功，该团队将使用类似脑的设计原理开发通用的集成控制系统，以处理比过去使用此类原理控制更大，更复杂的系统。他们将一起整合使用自适应动态编程（有时称为“强化学习”或“自适应批评家”），复发性神经网络（在近似非线性动力学系统中提供独特的功能），学习和适应性以及粒子群群优化技术。他们将在管理一个大型复杂的真实系统（最初是在计算机模拟中，然后在实验室中）来发展这种集成，以部分观察到的连续变量，非线性和随机扰动为主导。Boader好处：要控制的测试床代表使用最先进的，最先进的，负担得起的，有效的，有效的（但很难管理）的风力涡轮机和电子的功能（非常高级，有效地管理）'''''以低成本实现这种可靠的控制和效率的能力对于通过风提供全球20％的电能的目标至关重要。在理性的市场体系中，使像Wind这样的间歇力量更为有价值，这对于使Wind像Wind这样的断断续续的力量更有价值，因此将更大的付款从电网到风发电机，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，这可以为取得成功所需的一些先进的低成本事实提供技术 - 甚至还有一些其他测试台。该项目可能是将智能自适应电网理想带入现实世界的关键步骤。