Closed-loop model-based wind farm control using FLORIS under time-varying inflow conditions

Bart M. Doekemeijer, Daan van der Hoek and Jan-Willem van Wingerden

Renewable Energy, 2020, vol. 156, issue C, 719-730

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.

Keywords: Closed-loop wind farm control; Time-varying inflow; Wake steering; Ambient condition estimation; FLORIS; Large-eddy simulation (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (15)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:156:y:2020:i:c:p:719-730

DOI: 10.1016/j.renene.2020.04.007

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