A model predictive wind farm controller with linear parameter-varying models
Sjoerd Boersma (TU Delft - Mechanical Engineering)
Vahab Rostampour (TU Delft - Mechanical Engineering)
Bart Doekemeijer (TU Delft - Mechanical Engineering)
Jan-Willem van Wingerden (TU Delft - Mechanical Engineering)
Tamás Keviczky (TU Delft - Mechanical Engineering)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
In this paper, we present an implementation of a model predictive controller (MPC) for wind farm power tracking problem. The controller is evaluated in the high-fidelity PAral-lelized Large-eddy simulation Model (PALM). By taking measurements from PALM, we show that the closed-loop MPC can provide power reference tracking while reducing force variations on a farm level by solving a constrained optimization problem at each time step. A six turbine wind farm case study is presented in which the controller operates with yawed turbines that increases the potential power that can be harvested with the wind farm, and we show that it is possible to track a reference power signal that temporarily exceeds the power harvested when operating under the so-called greedy control settings.