A new digital twin studio that will focus on advancing power grid research and resilience is being developed by the State University of New York at Stony Brook. As electric vehicles, renewable energy systems and connected technologies place new demands on the grid, utilities will need better ways to anticipate problems before they affect homes, businesses and critical infrastructure. Researchers also need safe environments to test new technologies and resilience strategies. 

Approximately $550,000 has been secured for the digital twin studio, which aims to provide this testing ground and will allow researchers, students, utilities and public agencies to model electrical distribution systems and examine how the grid may respond to outages, extreme weather, cyberattacks, equipment failures and changing energy demands. Another $300,000 is anticipated for the next stage.

Led by the Center for Grid Innovation Development and Deployment (GrIDD) at the Advanced Energy Research and Technology Center (AERTC), the initiative is moving toward implementation.

The team is targeting December 2026 for the studio’s initial minimum viable platform, the first operational milestone for a system that will continue expanding as new equipment, datasets, applications and partnerships are added.

“What excites me most about the digital twin studio is that it will bring research, workforce development, and industry engagement together in one place,” said Abdelrahim Brown of AERTC and GrIDD. “We are building something that students can learn from, researchers can use, and partners can help shape as the platform grows.”

The studio will create high-fidelity virtual representations of power distribution networks at the neighborhood scale. By incorporating operational, environmental and equipment data, the models will allow users to test how systems might perform before making changes to physical infrastructure.

The platform will combine physics-based simulation, artificial intelligence and data from sources such as geographic information systems, weather systems, advanced meters and distributed energy resources. Near-real-time modeling and hardware-in-the-loop capabilities will allow researchers to connect physical equipment and control systems to the virtual environment and evaluate their performance under realistic grid conditions.

The first phase will focus on vegetation risk analytics, outage and contingency forecasting, and asset-health monitoring.

The vegetation-management component will combine camera imagery, multispectral data, LiDAR, weather information and artificial intelligence to identify vegetation near electrical infrastructure and assess encroachment risks. The team is developing tools to classify vegetation and power lines, generate three-dimensional point clouds, identify tree species and map areas of greatest risk. These capabilities could help utilities prioritize maintenance and prepare for storms, wildfires and other hazards.

For outage and contingency forecasting, the studio will provide a controlled environment for testing power-flow scenarios, restoration strategies, distributed energy integration and changes in demand. Users could study equipment failures, electrification-driven load growth and the effects of extreme weather or cyber-physical threats.

Asset-health monitoring will extend the digital twin to individual devices. Sensors and connected equipment could provide information about building systems, energy use, air quality and equipment performance. Artificial intelligence could then help identify abnormal behavior, predict maintenance needs or determine more efficient operating schedules.

Major purchases include high-performance computing equipment, laboratory computers, networking infrastructure, sensors, data-acquisition equipment and backup power systems. The project has also acquired a drone equipped for LiDAR, thermal imaging and visual imaging. Its data could support vegetation-risk analysis, infrastructure monitoring and three-dimensional modeling.

Additional investments include software, cloud services, platform development and a student training laboratory in the Center of Excellence in Wireless and Information Technology (CEWIT), which remains under construction.