Toward Real-Time Predictive Modeling of Wind Turbine Wakes: From Multiscale Methods to Reduced-Order Simulation of Complex Atmospheric Flows

This plenary session is part of the Artificial Intelligence and Digital Twins for Earth Systems workshop co-hosted by USACM and the Oden Institute for Computational Engineering and Sciences at UT Austin. 

Abstract: As wind energy continues to scale, accurate and efficient modeling of wind turbine wakes becomes essential for optimizing performance, layout, and control of utility-scale wind farms. This talk presents reduced-order modeling (ROM) framework developed by the CFSMgroup at the University of Calgary, built on the Proper Orthogonal Decomposition (POD)-Galerkin projection and variational multiscale (VMS) turbulence modeling framework. Coupled with the Actuator Line Method (ALM) and mesh-based hyper-reduction strategies, the framework enables accurate, cost-efficient simulations of full-scale turbine wakes under realistic operating conditions. Recent extensions of this framework have incorporated stratified atmospheric flows and wake interactions among multiple turbines. We will present new results on the ALM-VMS-ROM’s application to large turbine arrays, showing its ability to capture long-range wake interactions and their impact on power losses and structural loads. Simulations of stratified flows reveal critical influences of thermal layering on wake recovery and turbine performance, highlighting the importance of coupling physical insight with scalable computation. We will also discuss challenges in translating high-fidelity modeling into real-time predictive tools for wind energy. The broader goal is to bridge the gap between simulation accuracy and operational practicality, bringing us closer to physics-aware digital twins for atmospheric flows and renewable energy systems.

[1] S. Dave and A. Korobenko, “Consistent reduced order modeling for wind turbine wakes using variational multiscale method and actuator line model”, Computer Methods in Applied Mechanics and Engineering, 2025, under review.

Speaker Bio: Dr. Artem Korobenko is an Associate Professor in the Department of Mechanical and Manufacturing Engineering at the University of Calgary. He holds a Schulich Research Chair and leads the Computational Fluids and Structural Mechanics Group (CFSMgroup). Dr. Korobenko earned his PhD in 2014, followed by a postdoctoral position (2015-2016), both at the University of California San Diego. His research focuses on the development of multi-fidelity computational methods for the analysis and design of complex systems in aerospace, wind and marine engineering using large-scale computing. A Fulbright Alumni and Alexander von Humboldt Fellowship recipient, Dr. Korobenko is a founding member and current president of the Canadian Association for Computational Science and Engineering, as well as a Member-at-Large of the USACM Technical Thrust Area on Computational Fluid Dynamics and Fluid-Structure Interaction. He is also a founding member and co-director of the University of Calgary Aerospace Network.