In a deregulated power system, increasingly dynamic, and potentially more vulnerable, the need for multiple scenario analysis has become critical. This research will develop computing techniques for large-scale power system dynamics based on current mixed-signal VLSI emulation technology. Intellectual merit: Research on obtaining readily available explanations of the true causes of failures in the grid based on real-time analyses of actual conditions is of fundamental importance. The PIs will address both hardware and software considerations. The main tasks of the work are to develop: 1) deep sub-micron mixed-signal models (chip-level) of very large systems incorporating a multitude of time scales; and 2) analytical methods best equipped for large-scale parameter acquisition and actuation for real-time quantifying and qualifying behavior of complex large systems. Broader impacts: The creation of new, power system computing techniques requires the interaction and learning across multiple fields within engineering and science. New computation engines to be developed within the scope of this project will be demonstrated to power industry and vendors with the potential for commercial development. There are potentially far reaching impacts from the proposed study that can be applied to other critical infrastructures, including, communication and transportation systems, or indeed any system dependent on the interactions among large numbers of relatively simple objects or elements.
