The objective of this research is to apply the latest computational algorithms and parallelization techniques to enable faster than real-time power system dynamic simulations.
This project is to develop the data down sampling system, stream the data to the PI system at Center for Ultra-Wide-Area Resilient Electric Energy Transmission Networks (ORNL) and build up the data pipeline between the PI system at NERC and the PI system at ORNL to transmit and visualize the data.
The proposed project extends the LPT resilience scenario to consider additional impacts to loads and equipment, as well as the full portfolio of recovery options.
NYPA has concerns of potential very low damping oscillations in their system. The interarea oscillation with inadequate damping is one of the major factors leading to power system separation and even blackout, e.g. WECC in 1996. Oscillation damping controllers are usually designed and tuned based on the power system circuit model. The limitations of this approach are errors in the models and unable to reflect constant change in operating conditions.
This study intends to investigate a novel Quantum Computing application, where a QPU is the computational engine for large-scale electric power grid modeling to enable real-time, large interconnect-sized dynamic modeling.
The growing role of sensors in the distribution networks for realizing transmission level effects via, for example, automatic distributed load shedding and automated load shaping to track renewable generation requires a fundamentally new type of model that can accurately capture the view of the power system as inferred by these sensors.
This research will expand on the existing dynamic protection planning simulation tools to demonstrate a real-time protection coordination hardware simulation platform.