Martín Draper

As onshore wind turbines approach the end of their 20-year design lifetime, relative fatigue-based assessments are increasingly used to evaluate lifetime extension potential without requiring detailed design data. This study investigates the influence of wind turbine model selection on remaining useful life (RUL) estimations obtained using a relative assessment approach. Aero-servo-elastic simulations are performed in OpenFAST for two class IIIA reference turbines, the IEA 3.4 MW and the NREL 2.3 MW, considering standard design load cases and site-specific conditions derived from 10 years of meteorological mast data from a Uruguayan wind farm. Damage Equivalent Loads (DELs) are computed for key structural components and compared against design conditions. Results show consistently lower fatigue loads under site-specific conditions for both turbine models, with the blade edgewise moment identified as the life-limiting load channel. Estimated lifetimes of 23.2 and 22.9 years are obtained for the IEA 3.4 MW and NREL 2.3 MW turbines, respectively. Although the overall fatigue trends are similar for both models, differences observed in specific load channels highlight the sensitivity of relative lifetime estimations to the selected turbine model.

This paper presents a new approach based on the optimization of the blade pitching strategy of offshore wind turbines in order to maximize the global energy output considering the Gaussian wake model and including the effect of added turbulence. A genetic algorithm is proposed as an optimization tool in the process of finding the optimal setting of the wind turbines, which aims to determine the individual pitch of each turbine so that the overall losses due to the wake effect are minimised. The integration of the Gaussian model, including the added turbulence effect, for the evaluation of the wakes provides a step forward in the development of strategies for optimal operation of offshore wind farms, as it is one of the state-of-the-art analytical wake models that allow the evaluation of the energy output of the project in a more reliable way. The proposed methodology has been tested through the execution of a set of test cases that show the ability of the proposed tool to maximize the energy production of offshore wind farms, as well as highlights the importance of considering the effect of added turbulence in the evaluation of the wake.

As the size of wind turbines increases and their hub heights become higher, which partially explains the vertiginous increase of wind power worldwide in the last decade, the interaction of wind turbines with the atmospheric boundary layer (ABL) and between each other is becoming more complex. There are different approaches to model and compute the aerodynamic loads, and hence the power production, on wind turbines subject to ABL inflow conditions ranging from the classical Blade Element Momentum (BEM) method to Computational Fluid Dynamic (CFD) approaches. Also, modern multi-MW wind turbines have a torque controller and a collective pitch controller to manage power output, particularly in maximizing power production or when it is required to down-regulate their production. In this work the results of a validated numerical method, based on a Large Eddy Simulation-Actuator Line Model framework, was applied to simulate a real 7.7 MNW onshore wind farm on Uruguay under different wind conditions, and hence operational situations are shown with the aim to assess the capability of this approach to model actual wind farm dynamics. A description of the implementation of these controllers in the CFD solver Caffa3d, presenting the methodology applied to obtain the controller parameters, is included. For validation, the simulation results were compared with 1 Hz data obtained from the Supervisory Control and Data Acquisition System of the wind farm, focusing on the temporal evolution of the following variables: Wind velocity, rotor angular speed, pitch angle, and electric power. In addition to this, simulations applying active power control at the wind turbine level are presented under different de-rate signals, both constant and time-varying, and were subject to different wind speed profiles and wind directions where there was interaction between wind turbines and their wakes.

Recently, there has been an increasing interest in the academic community as well as in the industrial sector about the operation and control of a wind farm at a farm level. This new paradigm has different purposes, from maximizing power production through wake modulation to active power control. The former has been extensively analyzed with numerical or physical modelling, finding in general an improvement in the power production by yawing the wind turbine rotors. The aim of the present paper is to compare both approaches, by taking into account results from state of the art numerical simulations and wind tunnel campaigns. A case with three model wind turbines subject to an atmospheric boundary layer like inflow condition will be studied.

Recently, the Actuator Line Model (ALM) has been evaluated with coarser resolution and larger time steps than what is generally recommended, taking into account an atmospheric sheared and turbulent inflow condition. The aim of the present paper is to continue these studies, assessing the capability of the ALM to represent the wind turbines' interactions in an onshore wind farm. The 'Libertad' wind farm, which consists of four 1.9MW Vestas V100 wind turbines, was simulated considering different wind directions, and the results were compared with the wind farm SCADA data, finding good agreement between them. A sensitivity analysis was performed to evaluate the influence of the spatial resolution, finding acceptable agreement, although some differences were found. It is believed that these differences are due to the characteristics of the different Atmospheric Boundary Layer (ABL) simulations taken as inflow condition (precursor simulations).

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Actuator models have been used to represent the presence of wind turbines in a simulation in the past few years. The Actuator Line Model (ALM) has shown to reproduce with reasonable accuracy the wind flow through wind turbines under different operational conditions. Nevertheless, there are not many simulations of wind farms performed with the ALM mainly because of its computational cost. The aim of the present paper is to evaluate the ALM in spatial resolutions coarser than what is generally recommended, also using larger time steps, in a simulation of a real wind farm. To accomplish this, simulations of one row of Horns Rev wind farm are performed, for different wind directions. It is concluded that the ALM is able to capture the main features of the interaction between wind turbines relaxing its resolution requirements. A sensitivity analysis is performed to assess the influence of the smearing factor and the spatial resolution.

Wind energy has become cost competitive in recent years for several reasons. Among them, wind turbines have become more efficient, increasing its size, both rotor diameter and tower height. This growth in size makes the prediction of the wind flow through wind turbines more challenging. To avoid the computational cost related to resolve the blade boundary layer as well as the atmospheric boundary layer, actuator models have been proposed in the past few years. Among them, the Actuator Line Model (ALM) has shown to reproduce with reasonable accuracy the wind flow in the wake of a wind turbine with moderately computational cost. However, its use to simulate the flow through wind farms requires a spatial resolution and a time step that makes it unaffordable in some cases. The present paper aims to assess the ALM with coarser resolution and larger time step than what is generally recommended, taking into account an atmospheric sheared and turbulent inflow condition and comparing the results with the Actuator Disk Model with Rotation (ADM-R) and experimental data. To accomplish this, a well known wind tunnel campaign is considered as validation case.