Following the Northeast blackout of 2003 tremendous efforts have been made to modernize the electric power infrastructure of the United States by installing sophisticated, digital sensors called Phasor Measurement Units. These sensors continuously track the health of large, complex power grids with high accuracy. However, as the number of these sensors increases up into the thousands, grid operators are struggling to understand how the gigantic volumes of data can be efficiently communicated to control centers for taking timely control actions, especially in face of critical grid disturbances. Developing a reliable wide-area communication network that guarantees just-in-time data delivery is the greatest challenge. Unfortunately, neither the architecture of such networks nor the impacts of delays and data losses on control actions are well understood. This project will address this gap, and develop a highly resilient, fault-tolerant, and reliable distributed network control system for tomorrow's power grids using cutting-edge emerging technologies, such as cloud computing and software defined networks. Power systems are a critical infrastructural component in modern society. Therefore, results of this research will have a tremendous scientific impact on the smart grid and smart city research communities. The proposed multidisciplinary approach, test bed prototyping, and industry collaborations will help in educating next-generation workforce in the fields of smart grids and cyber-physical systems.

Overcoming network-induced latencies, data losses, and bandwidth limitations is the key for successful deployment of at-scale wide-area control of power systems. The merit of this research lies in the development of a distributed networked control system infrastructure that addresses all of these concerns. The approach encompasses multiple disciplines, ranging from power systems to control systems to advanced networking and cloud computing technologies. The proposed architecture will be realized via three interactive layers. Layer 1 will consist of physics-based controllers for power oscillation damping. Layer 2 will contain delay control rules for the communication network that work in tandem with the grid controllers. Layer 3 will consist of a supervisory controller realized through embedding and reconfiguration rules in a distributed cloud environment that continuously monitors the system status, and ensures fault-tolerance, resilience, and reliability of the overall closed-loop control system. The project team will also develop an integrated software and hardware testbed with open interfaces that can be used by other educational institutions.