A model predictive wind farm controller with linear parameter-varying models

Journal article (2018)

Authors

S. Boersma Team Jan-Willem van Wingerden - Mechanical, Maritime and Materials Engineering
Vahab Rostampour Team Tamas Keviczky - Mechanical, Maritime and Materials Engineering
B.M. Doekemeijer Team Jan-Willem van Wingerden - Mechanical, Maritime and Materials Engineering
J.W. van Wingerden Team Jan-Willem van Wingerden - Mechanical, Maritime and Materials Engineering
T. Keviczky Team Tamas Keviczky - Mechanical, Maritime and Materials Engineering
Research Group
Team Jan-Willem van Wingerden (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2018 S. Boersma, Vahab Rostampour, B.M. Doekemeijer, J.W. van Wingerden, T. Keviczky
DOI: https://doi.org/10.1016/j.ifacol.2018.11.020
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Published Date

2018

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Delft Center for Systems and Control

Research Group

Team Jan-Willem van Wingerden

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.