In this work, the authors have assessed the robustness of an Economic Nonlinear Model-Predictive Controller (ENMPC) aimed at maximizing the power production of wind turbines. The scope of the paper is to quantify the sensitivity of this type of controller concerning wind conditions, climate, wind speed prediction unavailability, and aerodynamic performance degradation. A power production controller’s robustness is crucial for the wind turbine industry due to the extreme variability of external conditions and the wear caused by long-term continuous operativity. Model-Predictive controllers are, in principle, more prone to robustness issues concerning standard controllers, a fact that limits their adoption on actual wind turbines. The analysis is performed with the fully-aeroelastic solver OpenFAST considering a wide set of realistic load cases. It is demonstrated that the ENMPC previously developed is robust to wind prediction unavailability and change in wind turbulence intensity. Conversely, it is not robust to the modelling error due to aerodynamic degradation. Indeed, a reduction in generated power concerning the reference controller is observed, especially for operating region two and end-life blades. Finally, a significant increase in power production is achieved considering the external temperature variation thanks to the ENMPC’s direct handling of the generator temperature constraint. IEEE

Robustness of an Economic Nonlinear model predictive control for wind turbines under changing environmental and wear conditions / Pustina, Luca; Serafini, Jacopo; Biral, Francesco. - In: IEEE CONTROL SYSTEMS LETTERS. - ISSN 2475-1456. - 7:(2023), pp. 769-774. [10.1109/LCSYS.2022.3225757]

Robustness of an Economic Nonlinear model predictive control for wind turbines under changing environmental and wear conditions

Biral, Francesco
Ultimo
2023-01-01

Abstract

In this work, the authors have assessed the robustness of an Economic Nonlinear Model-Predictive Controller (ENMPC) aimed at maximizing the power production of wind turbines. The scope of the paper is to quantify the sensitivity of this type of controller concerning wind conditions, climate, wind speed prediction unavailability, and aerodynamic performance degradation. A power production controller’s robustness is crucial for the wind turbine industry due to the extreme variability of external conditions and the wear caused by long-term continuous operativity. Model-Predictive controllers are, in principle, more prone to robustness issues concerning standard controllers, a fact that limits their adoption on actual wind turbines. The analysis is performed with the fully-aeroelastic solver OpenFAST considering a wide set of realistic load cases. It is demonstrated that the ENMPC previously developed is robust to wind prediction unavailability and change in wind turbulence intensity. Conversely, it is not robust to the modelling error due to aerodynamic degradation. Indeed, a reduction in generated power concerning the reference controller is observed, especially for operating region two and end-life blades. Finally, a significant increase in power production is achieved considering the external temperature variation thanks to the ENMPC’s direct handling of the generator temperature constraint. IEEE
2023
Pustina, Luca; Serafini, Jacopo; Biral, Francesco
Robustness of an Economic Nonlinear model predictive control for wind turbines under changing environmental and wear conditions / Pustina, Luca; Serafini, Jacopo; Biral, Francesco. - In: IEEE CONTROL SYSTEMS LETTERS. - ISSN 2475-1456. - 7:(2023), pp. 769-774. [10.1109/LCSYS.2022.3225757]
File in questo prodotto:
File Dimensione Formato  
Robustness_of_an_Economic_Nonlinear_model_predictive_control_for_wind_turbines_under_changing_environmental_and_wear_conditions.pdf

accesso aperto

Tipologia: Post-print referato (Refereed author’s manuscript)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 564.87 kB
Formato Adobe PDF
564.87 kB Adobe PDF Visualizza/Apri
Robustness_of_an_Economic_Nonlinear_Model_Predictive_Control_for_Wind_Turbines_Under_Changing_Environmental_and_Wear_Conditions.pdf

Solo gestori archivio

Tipologia: Versione editoriale (Publisher’s layout)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 1.56 MB
Formato Adobe PDF
1.56 MB Adobe PDF   Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/364165
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 2
social impact