Umberto Ciri

Large Eddy Simulation for an array of turbines with Extremum Seeking Control

Large Eddy Simulations of the flow past an array of three aligned turbines have been performed using two different control strategies: constant torque gain and the Extremum Seeking Control. An off-design tip speed ratio has been chosen as initial condition for each turbine. It is shown that the turbines controlled with constant torque gain do not reach their optimum tip speed ratio. On the other hand, turbines controlled with ESC reach, to a close approximation, the tip speed ratio which maximizes their power production. The power produced by the array controlled with ESC is about 10% larger than that obtained with constant torque gain. Power spectral densities of the wind velocity in the wake of the turbines are presented to discuss how to select the proper dithering frequency.

Development of a high fidelity CFD code for wind farm control

In this paper we describe an effort recently completed at UT Dallas to develop a high-fidelity computational fluid dynamics code to test and develop control algorithms aimed at maximizing power production and load mitigation. Preliminary results of three aligned turbines operating at different tip speed ratios (TSRs) are discussed to show the wealth of details available from the present code. The finer solution of the flow physics allows to gain a better understanding of how control algorithms should be designed and implemented in practical configurations. The paper includes a detailed analysis of the power and loads for optimal TSRs obtained by applying dynamic programming to a low-fidelity analytical model.

Data-driven RANS for simulations of large wind farms

In the wind energy industry there is a growing need for real-time predictions of wind turbine wake flows in order to optimize power plant control and inhibit detrimental wake interactions. To this aim, a data-driven RANS approach is proposed in order to achieve very low computational costs and adequate accuracy through the data assimilation procedure. The RANS simulations are implemented with a classical Boussinesq hypothesis and a mixing length turbulence closure model, which is calibrated through the available data. High-fidelity LES simulations of a utility-scale wind turbine operating with different tip speed ratios are used as database. It is shown that the mixing length model for the RANS simulations can be calibrated accurately through the Reynolds stress of the axial and radial velocity components, and the gradient of the axial velocity in the radial direction. It is found that the mixing length is roughly invariant in the very near wake, then it increases linearly with the downstream distance in the diffusive region. The variation rate of the mixing length in the downstream direction is proposed as a criterion to detect the transition between near wake and transition region of a wind turbine wake. Finally, RANS simulations were performed with the calibrated mixing length model, and a good agreement with the LES simulations is observed.

Reduced order model for optimization of power production from a wind farm

This paper focuses on the optimization of power production from a column of wind turbines aligned with the mean wind direction. Optimal settings of the wind turbines are estimated through dynamic programming. The optimization is conducted using a reduced order model that estimates the downstream evolution of wind turbine wakes with high level of accuracy and low computational costs. The model, which is the main contribution of this paper, consists in a data-driven Reynolds-averaged Navier-Stokes (RANS) algorithm calibrated through Large Eddy Simulation (LES) data. The RANS model is first assessed against LES data for a single turbine operating with different tip speed ratios. Then, the optimal settings of a column of four wind turbines are estimated from this model through dynamic programming. Finally, the cumulative power curve of the wind turbine column is obtained.

Dependence of leukocyte capture on instantaneous pulsatile flow

Atherosclerosis, an artery disease, is currently the leading cause of death in the United States in both men and women. The first step in the development of atherosclerosis involves leukocyte adhesion to the arterial endothelium. It is broadly accepted that blood flow, more specifically wall shear stress (WSS), plays an important role in leukocyte capture and subsequent development of an atherosclerotic plaque. What is less known is how instantaneous WSS, which can vary by up to 5 Pa over one cardiac cycle, influences leukocyte capture. In this paper we use direct numerical simulations (DNS), performed using an in-house code, to illustrate that leukocyte capture is different whether as a function of instantaneous or time-averaged blood flow. Specifically, a stenotic plaque is modeled using a computational fluid dynamics (CFD) solver through fully three-dimensional Navier-Stokes equations and the immersed boundary method. Pulsatile triphasic inflow is used to simulate the cardiac cycle. The CFD is coupled with an agent-based leukocyte capture model to assess the impact of instantaneous hemodynamics on stenosis growth. The computed wall shear stress agrees well with the results obtained with a commercial software, as well as with theoretical results in the healthy region of the artery. The analysis emphasizes the importance of the instantaneous flow conditions in evaluating the leukocyte rate of capture. That is, the capture rate computed from mean flow field is generally underpredicted compared to the actual rate of capture. Thus, in order to obtain a reliable estimate, the flow unsteadiness during a cardiac cycle should be taken into account.

Nested extremum seeking control for wind farm power optimization

Large-Eddy Simulations (LES) of an array of wind turbines have been carried out to design and evaluate a model-free approach, extremum-seeking control (ESC), for power maximization. This paper shows how to coordinate the action of the extremum seeking controllers (at each turbine) by nesting the objective functions used for optimization so that the power of the overall array is maximized. The paper illustrates how to select the frequencies of the dither signals (used by the ESCs) to reduce the sensitivity to turbulent wind fluctuations in the estimation of the gradients used for real-time power maximization. The results are compared with the results from a baseline configuration where each turbine is set to operate at its individual optimum tip speed ratio; i.e., at the nominal design condition. The comparison shows that a properly designed nested ESC can yield nontrivial improvements in power production relative to the baseline.