Development of a Wind Turbine Digital-Twin for failure prognosis: First Results

Nuñez-Montoya, Bolivar; Naranjo-Riofrío, Carlos; López-Estrada, Luis; Tutivén, Christian; Vidal, Yolanda; Fajardo-Pruna, Marcelo

Keywords: neural networks, wind turbine, Fault prognosis, Digital Twin, actual SCADA data

Abstract

Wind turbines are increasing their generation energy capacity, which requires an increase in reliability. One of the most relevant failures that occur in wind turbines is the one in the main bearing. The study of methods that allows predicting the behavior of Wind Turbines under different operation conditions will permit a forecast of any possible failure in the elements of the device. The current work presents the first results in developing a wind turbine digital twin using SCADA data. This DT should allow to estimate and simulate the behavior of the WT and be an additional tool in the prediction of failures. The used platform is MATLAB and its Simulink and Simscape modules.

Más información

Editorial: IEEE
Fecha de publicación: 2022
Año de Inicio/Término: 22 March 2022 through 25 March 2022
Página de inicio: 29
Página final: 33
Idioma: English
URL: https://ieeexplore.ieee.org/document/9765858