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

许多、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，这些系统将具有适应性、自愈性、综合性和智能化。这个项目是一项独特的努力，通过扩大计算智能的新方法，在电网控制方面提供更高的性能、鲁棒性和前瞻性，使这些话从字面上成为现实。这项工作将建立在先前成功的pi的基础上，例如，在www.eas.asu.edu/~nsfadp中描述，在之前最好的控制方案下，智能控制允许发电机在面对三倍于迫使发电机关闭的干扰时保持正常运行。它将探索扩展到更大系统的新方法，包括多个发电机和先进的电源开关组件，以集成的、最佳的方式进行管理。它将把电网作为智能系统和复杂系统自适应管理真正通用概念的试验台。

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.