DDDAS-TMRP: DDDAS for Autonomic Interconnected Systems: The National Energy Infrastructure

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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 reducedinvestment for transmission infrastructure in the past several decades. Experts recognize thatblackouts similar to the Northeast US - Canadian blackout of August 2003 remain a reality. TheDynamic Data-Driven Applications (DDDAS) paradigm offers a unique framework formethodological innovations that can revolutionize the nation's energy infrastructure, alleviate thethreat of blackouts, and assure the long term stability, reliability, and efficiency of the electric powergrid. New technology designed for the national energy infrastructure would increase the total energy utilized bydynamically balancing power supply and demand, and by providing the ability to respond topotentially debilitating situations before they develop into a crisis. The proposed research willadvance new methodologies for situation awareness, control flexibility, autonomic functionalities, andself-healing that will revolutionize the state of the art in energy management. The centerpiece of theresearch will be an integrated real time dynamic sensing and simulation capability for the electricpower grid. DDDAS provides the framework for the methodological innovations to achieveseamless and robust integration of measurements and dynamic simulations across the multipleboundaries 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) realtime, 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 timesimulation 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 problemssuch as the real time power grid simulation/sensing application, 4) new approaches to real timevisualization and computer security. To demonstrate the intellectual merit and to achieve thebroadest impact of this research, the team will take advantage of existing collaborations with theMidwest Systems Independent Operators (MISO), the first regional transmission organizationapproved in the United States, and technology transfer mechanisms are essentially already in place.