A multi-objective predictive control strategy for enhancing primary frequency support with wind farms

Conference Paper (2018)
Author(s)

S. Siniscalchi-Minna (Universitat Politecnica de Catalunya, Catalonia Institute for Energy Research IREC)

M. De-Prada-Gil (Catalonia Institute for Energy Research IREC)

F. D. Bianchi (Instituto Balseiro)

C. Ocampo-Martinez (Universitat Politecnica de Catalunya)

Bart De De Schutter (TU Delft - Team Bart De Schutter)

Research Group
Team Bart De Schutter
Copyright
© 2018 S. Siniscalchi-Minna, M. De-Prada-Gil, F. D. Bianchi, C. Ocampo-Martinez, B.H.K. De Schutter
DOI related publication
https://doi.org/10.1088/1742-6596/1037/3/032034
More Info
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Publication Year
2018
Language
English
Copyright
© 2018 S. Siniscalchi-Minna, M. De-Prada-Gil, F. D. Bianchi, C. Ocampo-Martinez, B.H.K. De Schutter
Research Group
Team Bart De Schutter
Volume number
1037
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Abstract

Nowadays, wind power plants (WPPs) should be able to dynamically change their power output to meet the power demanded by the transmission system operators. When the wind power generation exceeds the power demand, the WPP works in de-loading operation keeping some power reserve to be delivered into the grid to balance the frequency drop. This paper proposes to cast a model predictive control strategy as a multi-objective optimization problem which regulates the power set-points among the turbines in order to track the power demand profile, to maximize the power reserve, as well as to minimize the power losses in the inter-arrays connecting the wind turbines within the wind farm collection grid. The performance of the proposed control approach was evaluated for a wind farm of 12 turbines using a wind farm simulator to model the dynamic behavior of the wake propagation through the wind farm.