Abstract

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.

Highlights

  • Wind energy has expanded worldwide in the last decade

  • We present the results of the simulations, focusing on the dynamic of the variables involved in the power controller

  • The power output was not reached mainly because WT3 did not reach its required power as it was strongly affected by WT4 wake. These results show the need to implement a global wind farm controller, with the purpose of assigning de-rate commands based on the available power of each wind turbine, when there are wind turbines operating in the wake of others

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Summary

Introduction

Wind energy has expanded worldwide in the last decade. The installed capacity of wind power has increased close to 10% in 2017 [1], multiplying by almost 4.5 times between 2008 and 2017. Wind energy has become one of the main energy sources in some countries, achieving penetration levels in power generation of more than 30% in countries like Denmark [2] and Uruguay [3]. This development has been possible because of technological improvements making wind turbines more efficient, larger in size (rotor diameter, hub height, and rated power), and more capable of contributing to the electric grid regulation by supplying ancillary services [4,5,6]. In [5], Energies 2019, 12, 3508; doi:10.3390/en12183508 www.mdpi.com/journal/energies

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