I-Corps: Translation Potential of a Supervisory Control and Data Acquisition (SCADA)-Integrated, Digital Twin for Real-Time Resilience Assessment of Power Infrastructure

This I-Corps project is based on the development of a digital twin for improving the resilience of power infrastructure. Electric utilities, datacenters, hospitals, military installations, and other critical operations face growing risks from equipment failures, cyber-physical disruptions, rapidly changing loads, and the increasing complexity of modern power systems. This technology uses real-time operational data to anticipate emerging problems, evaluate their potential consequences, and recommend actions that can prevent failures or reduce their impact. Designed to integrate with existing monitoring and control platforms, adoption may reduce outages, shorten recovery times, protect critical services, and improve the reliability of electricity delivery without requiring organizations to replace their existing infrastructure. This I-Corps project utilizes experiential learning coupled with first-hand investigation of the industry ecosystem to assess the translation potential of a Supervisory Control and Data Acquisition (SCADA)-integrated, measurement-driven resilience assessment and control platform. The technology combines machine learning with a data-driven digital twin that learns the behavior of an energy system directly from operational measurements rather than relying only on static or fully calibrated models. The digital twin operates in parallel with the physical system to predict disturbances and failures, estimate changing resilience conditions, conduct rapid what-if analyses, and evaluate corrective control actions before they are implemented. These capabilities distinguish the technology from conventional resilience tools that are primarily used for offline planning or post-event analysis. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.