Artículo
Wind Turbine Active Fault Tolerant Control Based on Backstepping Active Disturbance Rejection Control and a Neurofuzzy Detector
Autor/es | Assia, Hamza
Boulouiha, Houari Merabet Chicaiza Salazar, William David Escaño González, Juan Manuel Kacimi, Abderrahmane Martínez Ramos, José Luis |
Departamento | Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática Universidad de Sevilla. Departamento de Ingeniería Eléctrica |
Fecha de publicación | 2023-07 |
Fecha de depósito | 2023-09-05 |
Publicado en |
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Resumen | Wind energy conversion systems have become an important part of renewable energy history due to their accessibility and cost-effectiveness. Offshore wind farms are seen as the future of wind energy, but they can be very ... Wind energy conversion systems have become an important part of renewable energy history due to their accessibility and cost-effectiveness. Offshore wind farms are seen as the future of wind energy, but they can be very expensive to maintain if faults occur. To achieve a reliable and consistent performance, modern wind turbines require advanced fault detection and diagnosis methods. The current research introduces a proposed active fault-tolerant control (AFTC) system that uses backstepping active disturbance rejection theory (BADRC) and an adaptive neurofuzzy system (ANFIS) detector in combination with principal component analysis (PCA) to compensate for system disturbances and maintain performance even when a generator actuator fault occurs. The simulation outcomes demonstrate that the suggested method successfully addresses the actuator generator torque failure problem by isolating the faulty actuator, providing a reliable and robust solution to prevent further damage. The neurofuzzy detector demonstrates outstanding performance in detecting false data in torque, achieving a precision of 90.20% for real data and 100% for false data. With a recall of 100% , no false negatives were observed. The overall accuracy of 95.10% highlights the detector’s ability to reliably classify data as true or false. These findings underscore the robustness of the detector in detecting false data, ensuring the accuracy and reliability of the application presented. Overall, the study concludes that BADRC and ANFIS detection and isolation can improve the reliability of offshore wind farms and address the issue of actuator generator torque failure. |
Agencias financiadoras | European Union’s Horizon 2020 research and innovation program under grant agreement No 958339 |
Identificador del proyecto | EU H2020 958339 |
Cita | Assia, H., Boulouiha, H.M., Chicaiza Salazar, W.D., Escaño González, J.M., Kacimi, A. y Martínez Ramos, J.L. (2023). Wind Turbine Active Fault Tolerant Control Based on Backstepping Active Disturbance Rejection Control and a Neurofuzzy Detector. Energies, 16 (14), 5455. https://doi.org/10.3390/en16145455. |
Ficheros | Tamaño | Formato | Ver | Descripción |
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E_escaño-gonzalez_2023_wind.pdf | 3.993Mb | [PDF] | Ver/ | |