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Conference paper

Model based active power control of a wind turbine

From

Department of Applied Mathematics and Computer Science, Technical University of Denmark1

Department of Wind Energy, Technical University of Denmark2

Aeroelastic Design, Department of Wind Energy, Technical University of Denmark3

Aalborg University4

Dynamical Systems, Department of Applied Mathematics and Computer Science, Technical University of Denmark5

Department of Electrical Engineering, Technical University of Denmark6

Automation and Control, Department of Electrical Engineering, Technical University of Denmark7

In recent decades there has been increasing interest in green energies, of which wind energy is one of the most important. Wind turbines are the most common wind energy conversion systems and are hoped to be able to compete with traditional power plants in near future. This demands better technology to increase competitiveness of the wind power plants.

One way to increase competitiveness of wind power plants is to offer grid services (also called ancillary services) that are normally offered by traditional power plants. One of the ancillary services is called reserve power. There are instants in the electricity market that selling the reserve power is more profitable than producing with the full capacity.

Therefore wind turbines can be down-regulated and sell the differential capacity as the reserve power. In this paper we suggest a model based approach to control wind turbines for active power reference tracking. We use model predictive control (MPC) as our control method. We compare three different control strategies, namely Max-Ω, Constant-Ω and Constant-λ and discuss their drawbacks and benefits by presenting analysis of the steady state operating points and simulations on a high fidelity wind turbine model.

Language: English
Publisher: IEEE
Year: 2014
Pages: 5037-5042
Proceedings: 2014 American Control Conference
ISBN: 147993271X , 1479932728 , 1479932744 , 1479932752 , 9781479932719 , 9781479932726 , 9781479932740 and 9781479932757
ISSN: 23785861 and 07431619
Types: Conference paper
DOI: 10.1109/ACC.2014.6859055
ORCIDs: Poulsen, Niels Kjølstad and Niemann, Hans Henrik

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