Abstract
Wind farm (WF) controllers adjust the control settings of individual turbines to enhance the total performance of a wind farm. Most WF controllers proposed in the literature assume a time-invariant inflow, whereas important quantities such as the wind direction and speed continuously change over time in reality. Furthermore, properties of the inflow are often assumed known, which is a fundamentally compromising assumption to make. This paper presents a novel, closed-loop WF controller that continuously estimates the inflow and maximizes the energy yield of the farm through yaw-based wake steering. The controller is tested in a high-fidelity simulation of a 6-turbine wind farm. The WF controller is stress-tested by subjecting it to strongly-time-varying inflow conditions over 5000 s of simulation. A time-averaged improvement in energy yield of 1.4% is achieved compared to a baseline, greedy controller. Moreover, the instantaneous energy gain is up to 11% for wake-loss-heavy situations. Note that this is the first closed-loop and model-based WF controller tested for time-varying inflow conditions (i.e., where the mean wind direction and wind speed change over time) at such fidelity. This solidifies the WF controller as the first realistic closed-loop control solution for yaw-based wake steering.
Highlights
In the ‘‘Klimaatakkoord’’ [1], the Dutch government pledges to significantly reduce carbon-dioxide emissions over the decade, lowering emissions to 49% of the levels measured in 1990
To the best of the authors’ knowledge, there is no literature on the assessment of closed-loop model-based wind farm control solutions in a high-fidelity environment with time-varying inflow conditions
The optimal model parameters U+ are found by minimizing the root-mean-square error (RMSE) of the timeaveraged flow field from Simulator for Wind Farm Applications (SOWFA), USOWFA2RNu, and the flow field predicted by FLOw Redirection and Induction in Steady-state (FLORIS), UFLORIS2RNu, as
Summary
In the ‘‘Klimaatakkoord’’ [1], the Dutch government pledges to significantly reduce carbon-dioxide emissions over the decade, lowering emissions to 49% of the levels measured in 1990. Ciri et al [21] presents a closed-loop and model-free control algorithm that improves the performance of turbines inside a wind farm, demonstrated in high-fidelity simulations under a time-varying inflow. To the best of the authors’ knowledge, there is no literature on the assessment of closed-loop model-based wind farm control solutions in a high-fidelity environment (i.e., field experiment, wind tunnel experiment, large-eddy simulation) with time-varying inflow conditions.
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