Journal
IEEE ACCESS
Volume 9, Issue -, Pages 26512-26522Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2021.3057123
Keywords
Stators; Wind power generation; Rotors; Doubly fed induction generators; Backstepping; Mathematical model; Production; Wind turbine; energy; backstepping control; adaptive control; MATLAB; simulink; wind turbine; dSPACE
Categories
Funding
- Taif University Researchers Supporting Project, Taif University, Saudi Arabia [TURSP-2020/98]
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A new nonlinear adaptive backstepping control technique applied to DFIG wind systems, along with an optimization strategy utilizing the RTO algorithm, has been proposed to ensure system stability and robustness. Validation through simulation on MATLAB/Simulink and real-time implementation in a laboratory setting demonstrates superior performance compared to other control techniques.
With the development of wind power generation in recent years, several studies have dealt with the active and reactive power control of wind power systems, along with the quality of energy produced and the connection to distribution networks. In this context, this research proposes a new contribution to the field. The major objective of this work is the development of a nonlinear adaptive backstepping control technique applied to a DFIG based wind system and an optimization technique that uses the rooted tree optimization (RTO) algorithm. The backstepping control strategy is based on the Lyapunov nonlinear technique to guarantee the stability of the system. It is applied to the two converters (i.e., machine and network sides) and subsequently improved with estimators to make the proposed system robust to parametric variation. The RTO technique is based on monitoring the behavior of the underlying foundation of trees in search of underground water in accordance with the level of underground control. The solution proposed for the control is validated using two methods: (1) a simulation on MATLAB/Simulink to test the continuation of the reference (real wind speed) and the robustness of the system and (2) a real-time implementation on a dSPACE-DS1104 board connected to an experimental bench in a laboratory. Simulation and experimental results highlight the validation of the proposed model with better performance compared with other control techniques, such as sliding mode control, direct power control, and field-oriented control.
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