RT info:eu-repo/semantics/article
T1 Deep learning and fuzzy logic to implement a hybrid wind turbine pitch control
A1 Sierra Garcia, Jesús Enrique
A1 Santos, Matilde
K1 Hybrid system
K1 Deep learning
K1 Fuzzy control
K1 Neural networks
K1 Pitch control
K1 Wind turbines
K1 Ingeniería mecánica
K1 Mechanical engineering
AB This work focuses on the control of the pitch angle of wind turbines. This is not an easy task due to the nonlinearity, the complex dynamics, and the coupling between the variables of these renewable energy systems. This control is even harder for floating offshore wind turbines, as they are subjected to extreme weather conditions and the disturbances of the waves. To solve it, we propose a hybrid system that combines fuzzy logic and deep learning. Deep learning techniques are used to estimate the current wind and to forecast the future wind. Estimation and forecasting are combined to obtain the effective wind which feeds the fuzzy controller. Simulation results show how including the effective wind improves the performance of the intelligent controller for different disturbances. For low and medium wind speeds, an improvement of 21% is obtained respect to the PID controller, and 7% respect to the standard fuzzy controller. In addition, an intensive analysis has been carried out on the influence of the deep learning configuration parameters in the training of the hybrid control system. It is shown how increasing the number of hidden units improves the training. However, increasing the number of cells while keeping the total number of hidden units decelerates the training.
PB Springer
SN 0941-0643
YR 2022
FD 2022-07
LK http://hdl.handle.net/10259/6157
UL http://hdl.handle.net/10259/6157
LA eng
NO Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work was partially supported by the Spanish Ministry of Science, Innovation and Universities under MCI/AEI/FEDER Project Number RTI2018-094902-B-C21.
DS Repositorio Institucional de la Universidad de Burgos
RD 04-dic-2024