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


Reference:

S. Siniscalchi-Minna, M. De-Prada-Gil, F.D. Bianchi, C. Ocampo-Martinez, and B. De Schutter, "A multi-objective predictive control strategy for enhancing primary frequency support with wind farms," The Science of Making Torque from Wind (TORQUE 2018) - Journal of Physics: Conference Series, vol. 1037, Milan, Italy, 10 pp., June 2018. Paper 032034.

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.

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Bibtex entry:

@inproceedings{SinDeP:18-031,
author={S. Siniscalchi-Minna and M. {D}e-Prada-Gil and F.D. Bianchi and C. Ocampo-Martinez and B. {D}e Schutter},
title={A multi-objective predictive control strategy for enhancing primary frequency support with wind farms},
booktitle={The Science of Making Torque from Wind (TORQUE 2018) -- Journal of Physics: Conference Series, vol.\ 1037},
address={Milan, Italy},
month=jun,
year={2018},
note={Paper 032034},
doi={10.1088/1742-6596/1037/3/032034}
}


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