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

RENEWABLE ENERGY

卷:156

Article

Doekemeijer, Bart M.^1,2  van der Hoek, Daan^1,2  van Wingerden, Jan-Willem^1,2 

[1] Delft Univ Technol, Mekelweg 2, NL-2628 CD Delft, Netherlands

[2] Delft Ctr Syst & Control DCSC, Data Driven Control DDC Res Grp, Delft, Netherlands

关键词: Closed-loop wind farm control;    Time-varying inflow;    Wake steering;    Ambient condition estimation;    FLORIS;    Large-eddy simulation;   

DOI  :  10.1016/j.renene.2020.04.007

来源: Elsevier

【 摘 要 】

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. (C) 2020 The Authors. Published by Elsevier Ltd.

【 授权许可】

Free