NEURAL NETWORK BASED WIDE AREA COORDINATION AND LOCAL CONTROL OF ELEMENTS IN A LARGE COMPLEX SYSTEM

大型复杂系统中基于神经网络的广域协调和局部控制

• 批准号: 0400657
• 负责人: Mariesa Crow
• 金额: $ 23万
• 依托单位: Missouri University of Science and Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-08-01 至 2007-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0400657&HistoricalAwards=false
• 关键词: NEURAL; NETWORK; BASED; WIDE; AREA

Many, many researchers have called out for new systems to manage the nation's infrastructure networks which would be adaptive, self-healing, integrated and intelligent. This project is a unique effort to make those words literally true, by scaling up new approaches to computational intelligence so as to provide greater performance, robustness and foresight in the control of electric power grids. The work will build on prior successes of the PIs, as described, for example, in www.eas.asu.edu/~nsfadp, in which intelligent control allowed generators to stay up and running in the face of disturbances three times as large as what forces a generator shutdown, under the previous best control schemes. It will explore new ways of scaling up to larger systems, involving multiple generators and advanced power switching components, to be managed in an integrated, optimal fashion. It will use power grids as a testbed for truly general concepts of intelligent systems, and of adaptive management of complex systems.

许多研究人员呼吁建立新的系统来管理国家的基础设施网络，这些系统将是自适应的、自我修复的、集成的和智能的。该项目是一项独特的努力，通过扩大计算智能的新方法，使这些话在字面上成为现实，从而在电网控制方面提供更好的性能、健壮性和前瞻性。这项工作将建立在PI以前的成功基础上，如www.eas.asuedu/~nsfadp中所述，在以前的最佳控制方案下，智能控制使发电机在面临三倍于迫使发电机关闭的扰动时保持正常运行。它将探索扩大到更大系统的新方法，涉及多台发电机和先进的电源开关组件，以集成、优化的方式进行管理。它将利用电网作为真正的一般智能系统概念的试验台，以及复杂系统的自适应管理。