As electric vehicles, renewable energy systems and connected technologies place new demands on the power grid, utilities 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.
Stony Brook University is developing a new Digital Twin Studio to provide that testing ground. The platform 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.
Led by the Center for Grid Innovation Development and Deployment (GrIDD) at the Advanced Energy Research and Technology Center (AERTC), the initiative is moving into implementation. Approximately $550,000 has been secured for the current buildout, with another $300,000 anticipated for the next stage.
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.
Building a More Resilient Grid
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.
From Drone Imagery to High-Performance Computing
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.
Funding has come from university innovation funding and external project support, including support connected to Sunrise Wind and Ørsted.
Supporting Students, Research and Industry
For Stony Brook faculty and students, the studio will provide shared infrastructure for research spanning electrical engineering, computer science, data analytics and cybersecurity. Researchers will be able to develop and validate algorithms for load forecasting, distributed energy coordination, voltage optimization and network reconfiguration. They will also be able to simulate cyber intrusions and control-system vulnerabilities without placing operational infrastructure at risk.
The project team is developing a digital twin learning module for the CyberLearn workforce-development program, expected to reach its first group of Stony Brook students in Spring 2027. The studio could also support sponsored research and collaborations with utilities, public agencies, industry partners and other universities.
IotaComm, a technology company already collaborating with CEWIT on smart-building and sensing technologies, is beginning a related project with AERTC that will contribute data and capabilities to the studio. Its technologies are expected to support asset-health monitoring and device-level modeling by connecting data from physical environments with the platform’s simulation and analytics tools.
“IotaComm is proud to support Stony Brook University’s Digital Twin Studio by helping connect real-world sensing data, IotaWAVE-enabled infrastructure, and operational intelligence with advanced simulation, analytics, and research capabilities,” said Terrence DeFranco, chairman and CEO, IotaComm, Inc. “Building on our work with a LoRaWAN® testbed at CEWIT and our related project with AERTC, this collaboration helps create a living-lab environment where smart building systems, energy research, environmental sensing, asset-health monitoring, and device-level modeling can come together. For IotaComm, this initiative reflects the broader value of making physical environments more connected, measurable, adaptive, and actionable through our Delphi360 platform while supporting research, workforce development, and industry collaboration.”
The team is also exploring opportunities to incorporate data from Stony Brook’s utility infrastructure and deploy sensing devices on campus.
By bringing simulation, physical equipment, operational data and interdisciplinary expertise into one environment, the Digital Twin Studio is intended to move promising grid technologies toward implementation while preparing students to contribute to the future of the energy industry.