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Título:
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Health-aware model predictive control of wind turbines using fatigue prognosis
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Autor/a:
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Sánchez Sardi, Héctor Eloy; Escobet Canal, Teresa; Puig Cayuela, Vicenç; Fogh Odgaard, Peter
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Otros autores:
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Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial; Universitat Politècnica de Catalunya. Departament d'Enginyeria Minera, Industrial i TIC; Universitat Politècnica de Catalunya. SIC - Sistemes Intel·ligents de Control; Universitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control |
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Abstract:
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Wind turbines components are subject to considerable fatigue due to extreme environmental conditions to which are exposed, especially those located offshore. Interest in the integration of control with fatigue load minimization has increased in recent years. The integration of a system health management module with the control provides a mechanism for the wind turbine to operate safely and optimize the trade-off between components life and energy production.
The research presented in this paper explores the integration of model predictive control (MPC) with fatigue-based prognosis approach to minimize the damage of wind turbine components (the blades). The controller objective is modified by adding an extra criterion that takes into account the accumulated damage. The scheme is implemented and tested using a high fidelity simulator of a utility scale wind turbine. |
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Abstract:
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Peer Reviewed |
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Materia(s):
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-Àrees temàtiques de la UPC::Informàtica::Automàtica i control
-Wind turbines--Automatic control
-Fault tolerance (Engineering)
-Aerogeneradors -- Control automàtic
-Tolerància als errors (Enginyeria) |
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Derechos:
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Tipo de documento:
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Artículo - Versión presentada
Objeto de conferencia |
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Editor:
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International Federation of Automatic Control (IFAC)
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Compartir:
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