Published September 1, 2023

Leonardo Pagamonci Wins 2023 CONVERGE Academic Competition With Tandem Onshore Wind Turbine Study

Leonardo Pagamonci

We’re thrilled to announce Leonardo Pagamonci, graduate student at the University of Florence, as the winner of the 2023 CONVERGE Academic Competition. The competition challenged students to design and run a novel CONVERGE simulation that demonstrates significant engineering knowledge, accurately reflects the real world, and represents progress for the engineering community. 

Leonardo, who is pursuing a Ph.D. in industrial engineering, developed an interest in wind energy during his studies. “It strongly caught my attention because it’s a very interesting, modern field. The wind energy sector is relatively new, compared to other energy sectors.”

For his Ph.D., Leonardo is combining wind energy with another passion of his: computational fluid dynamics (CFD). He is developing a modeling approach to study the aeroelastic response of the wind turbine blades, i.e., the mutual interaction between the rotor structure and aerodynamics. When he learned about the CONVERGE Academic Competition, he thought it was the perfect opportunity to put his new modeling approach to the test. For his submission, he performed an aero-servo-elastic study of tandem onshore wind turbines operating in an atmospheric boundary layer (ABL), with the upwind turbine undergoing a yaw maneuver.

Visualization of Leonardo’s CONVERGE simulation showing tandem onshore wind turbines operating in an atmospheric boundary layer. At T=500, the upwind turbine maneuvers to a 25° yaw angle.

“The goal of this project was to simulate the operation of two turbines in an atmospheric boundary layer with realistic wind field conditions using a control technique that is common for wind farms,” said Leonardo.

The geometry for his study consists of two 5 MW onshore turbines separated by a distance of 7 rotor diameters (Figure 1). To simulate the rotor, Leonardo employed CONVERGE’s actuator line model (ALM), which is a cost-efficient method to model the aeroelastic response of the rotor blades without needing to solve the 3D geometry. He also included an actuator line for the wind turbine tower in his model to account for the aerodynamic effects of the tower and the aeroelastic interactions between the tower and the blades. 

Figure 1: Mesh resolution around the rotors and contour visualization of the turbulent flow field in the simulation domain.

To conduct the aero-servo-elastic study, Leonardo coupled CONVERGE with OpenFAST, a multi-physics tool for simulating the coupled dynamic response of wind turbines, through a user-defined function in CONVERGE. With this approach, CONVERGE solves the flow domain, predicting the inflow velocities. These data are passed to OpenFAST and used as inputs to solve for the aerodynamics of the structure and calculate the new positions of the ALM nodes. Furthermore, Leonardo used a synthetic turbulence generator developed at the University of Florence1 to generate the macro-structures of the turbulent wind conditions. 

The purpose of Leonardo’s study was to investigate the effects of a yaw misalignment on the tandem wind turbines. Initially, the two rotors operate with zero yaw angle. At a specified time, the upwind rotor (T1) is controlled to maneuver to a 25° yaw angle. The effects of this maneuver on the downwind turbine (T2), as well as on the system as a whole, are then quantified.

Table 1 shows the results for aerodynamic power both before (pre) and after (post) the yaw maneuver. The yaw maneuver caused a decrease in performance in T1 and an increase in performance in T2, although of a smaller magnitude. Overall, the yaw maneuver resulted in a 3.6% decrease in performance for the whole system. The decrease in total power is likely because the yaw angle is not optimal. Further simulation studies of different angles could help identify an optimal configuration.

Power_pre (kW)293512634198
Power_post (kW)237616724048
Delta-559 kW+409 kW-3.6%
Table 1: Aerodynamic power before (pre) and after (post) the yaw maneuver for the upwind turbine (T1), downwind turbine (T2), and tandem system.

Looking at the structural response of the blades, Leonardo found a substantial redistribution of the loads following the yaw maneuver, with significant changes in the mean displacements of the blade tips (Figure 2). 

Figure 2: Top – Blade span distribution of blade deformation in the flapwise direction (line indicates mean values; shading indicates the standard deviation of the time series data). Bottom – Power spectral density (PSD) of the time series trends of blade tip displacement.

“Aeroelasticity is a very important aspect of wind turbine analysis, especially because horizontal-axis wind turbines have very large rotors,” Leonardo explained. “With such long, slender, and flexible blades, it is important to analyze the mutual interaction of the aerodynamics and the structure, since each one interacts with and modifies the response of the other.”

Being able to accurately predict these interactions becomes even more important when looking at larger wind farms, where the wakes from the upwind rows propagate to the downwind ones, affecting the performance of the entire wind farm. In addition, the structural response of each individual turbine must be taken into account. These kinds of studies are exactly what Leonardo has planned for the future using this methodology.

“This tool is applicable to a very wide range of analyses,” said Leonardo. “You could analyze more yaw maneuver angles to see which is optimal, look at a broad range of operating conditions, investigate cases where the turbines aren’t aligned with the wind, study a greater number of turbines, or simulate much larger turbines. And because the controller is available with this tool, the studies have another degree of realism.”

Leonardo’s work is not only extending the modeling capabilities of CONVERGE, but also enabling more realistic studies of complex wind turbine dynamics, which will ultimately help the wind energy industry continue to grow to meet rising consumer demand. We look forward to seeing more of Leonardo’s impressive work in the future!

Learn more about the CONVERGE Academic Program here.


[1] Balduzzi, F., Zini, M., Ferrara, G., and Bianchini, A., “Development of a Computational Fluid Dynamics Methodology to Reproduce the Effects of Macroturbulence on Wind Turbines and Its Application to the Particular Case of a VAWT,” Journal of Engineering for Gas Turbines and Power, 141(11), 2019. DOI: 10.1115/1.4044231

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