The basic technological framework used to manage the national electric power grid is several generations old and is not prepared to meet the increased pressures of a growing economy, especially with the reduced investment for transmission infrastructure in the past several decades. Experts recognize that blackouts similar to the Northeast US - Canadian blackout of August 2003 remain a reality. The Dynamic Data-Driven Applications (DDDAS) paradigm offers a unique framework for methodological innovations that can revolutionize the nation's energy infrastructure, alleviate the threat of blackouts, and assure the long term stability, reliability, and efficiency of the electric power grid. New technology designed for the national energy infrastructure would increase the total energy utilized by dynamically balancing power supply and demand, and by providing the ability to respond to potentially debilitating situations before they develop into a crisis. The proposed research will advance new methodologies for situation awareness, control flexibility, autonomic functionalities, and self-healing that will revolutionize the state of the art in energy management. The centerpiece of the research will be an integrated real time dynamic sensing and simulation capability for the electric power grid. DDDAS provides the framework for the methodological innovations to achieve seamless and robust integration of measurements and dynamic simulations across the multiple boundaries of timescales and spatial characteristics encountered in the power grid. To achieve its objectives the project will make advances along six integrated tasks (e.g. Simulation, Sensing, Integrative Methods, Visualization, Computer Security, and Demonstration). The advances of this research include 1) real time, high fidelity power grid simulation using integrated distributed heterogeneous simulation (DHS) and neural network techniques on high end computational platforms, 2) the integration of real time simulation and sensing using both high cost, high precision and low cost distributed sensor networks, 3) a new class of stable and robust mathematical algorithms for solving complex ill-posed problems such as the real time power grid simulation/sensing application, 4) new approaches to real time visualization and computer security. To demonstrate the intellectual merit and to achieve the broadest impact of this research, the team will take advantage of existing collaborations with the Midwest Systems Independent Operators (MISO), the first regional transmission organization approved in the United States, and technology transfer mechanisms are essentially already in place.
