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A fatigue-oriented cost function for optimal individual pitch control of wind turbines

Authors :
David Collet
Domenico Di Domenico
Guillaume Sabiron
Mazen Alamir
IFP Energies nouvelles (IFPEN)
GIPSA - Modelling and Optimal Decision for Uncertain Systems (GIPSA-MODUS)
GIPSA Pôle Automatique et Diagnostic (GIPSA-PAD)
Grenoble Images Parole Signal Automatique (GIPSA-lab)
Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )
Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )
Université Grenoble Alpes (UGA)-Grenoble Images Parole Signal Automatique (GIPSA-lab)
Université Grenoble Alpes (UGA)
ANR-19-P3IA-0003,MIAI,MIAI @ Grenoble Alpes(2019)
Source :
IFAC-Papers, IFAC-PapersOnLine, Elsevier, 2021, 53 (2), pp.12632-12637. ⟨10.1016/j.ifacol.2020.12.1835⟩
Publication Year :
2020
Publisher :
Elsevier BV, 2020.

Abstract

International audience; In a context of wind power production growth, it is necessary to optimize the levelized cost of energy by maximizing the profit of operating wind turbines, which is defined as the difference between gains (e.g. energy sold) and losses (e.g. operation and maintenance cost). Operation and maintenance cost is intimately related to fatigue damage. However, considering fatigue directly in an optimization needs to be carefully done because its faithful model does not fit standard forms. In this paper, it is first shown that the variance of a signal and its corresponding damage using fatigue theory are nonlinearly related. Therefore, this relationship is used to design a convex cost function approximating fatigue. Preliminary tests suggest promising results regarding the relevance of this formulation in optimizing fatigue trade-off when compared to a family of quadratic cost functions. The proposed formulation allows to directly consider economic parameters in the cost function, limiting thus the sensitivity to parameter tuning.

Details

ISSN :
24058963
Volume :
53
Database :
OpenAIRE
Journal :
IFAC-PapersOnLine
Accession number :
edsair.doi.dedup.....db7b712db8a97ada35c72c1a55fb3dd7