Stochastic model predictive control: Uncertainty impact on wind farm power tracking

S. Boersma, B. M. Doekemeijer, T. Keviczky, Jan-Willem van Wingerden

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

6 Citations (Scopus)
14 Downloads (Pure)


Active power control for wind farms is needed to provide ancillary services. One of these services is to track a power reference signal with a wind farm by dynamically de- and uprating the turbines. Due to the stochastic nature of the wind, it is necessary to take this stochastic behavior into account when evaluating control signals. In this paper we present a closed-loop stochastic wind farm controller that evaluates thrust coefficients providing power tracking under uncertain wind speed measurements. The controller is evaluated in a high-fidelity wind farm model simulating a 9-turbine wind farm to demonstrate the stochastic controller under different uncertainty levels on the wind speed measurement and different controller settings. Results illustrate that a stochastic controller provides better tracking performance with respect to its deterministic variant.

Original languageEnglish
Title of host publicationProceedings of the 2019 American Control Conference (ACC 2019)
Place of PublicationPiscataway, NJ, USA
ISBN (Electronic)978-1-5386-7926-5
Publication statusPublished - 2019
Event2019 American Control Conference, ACC 2019 - Philadelphia, United States
Duration: 10 Jul 201912 Jul 2019


Conference2019 American Control Conference, ACC 2019
Country/TerritoryUnited States

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

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