Investigating Wind Farm Wake Interactions by Leveraging a Viscous Vortex Particle Method

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One major impediment in the wind energy field is managing the power losses (10-30%) that occur in a wind farm because of wake interference. Mitigating these losses by even a few percent would have a major impact on our ability to abundantly produce clean energy and reduce greenhouse gas emissions. Reducing these losses requires untangling the complexities of wind farm flow behavior. Wind farms typically consist of 10s or 100s of turbines, with rotating blades creating wakes that mix and interact, affected by terrain and atmospheric behavior across many scales. Vortex particle methods have been demonstrated to be an effective approach for simulating wake-dominant flows in adjacent fields (e.g., rotorcraft) and can potentially offer insight into wind farm flow fields at much faster computational speeds compared to traditional methods. However, efficiently propagating vortex particles around viscous walls (e.g., terrain, other turbines) remains a challenge that is a focal point of this proposal. The fundamental methodology could potentially be useful in other wake-dominant flow fields like simulating aircraft, underwater vehicles, the motion of water or smoke around other objects, etc. The project will also facilitate the development of a learn-by-doing platform to introduce students to computational aerodynamics—like a Codecademy® for aerodynamics.The viscous vortex particle method is based on solving the vorticity form of the Navier-Stokes equations, and, using a meshless Lagrangian scheme, which can accurately preserve vortical structures and improve computational efficiency by placing particles only where needed. The first objective is to extend the methodology to allow for efficient propagation of particles around viscous walls. The second objective is to leverage the speed of the proposed methodology to create a new analytical wake model appropriate for mixed height wind farms. Recent work has demonstrated that mixed height wind farms have the potential for a significant increase in power production. Existing analytical wake models are often not appropriate for these scenarios as they do not include important coupling effects such as mixing and entrainment. So, the third objective is to conduct broad sensitivity studies to identify the most relevant parameters and strategies to mitigate the negative effects of partial waking. Wind turbines often encounter incoming wakes over just a portion of the rotor disk causing asymmetric loading and potentially increased fatigue damage and noise. The proposed methodology provides a good balance between capturing the fidelity in flow physics with prediction speed to enable a robust exploration of wake interactions.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.