Fuzzy Logic-Based Smart Control of Wind Energy Conversion System Using Cascaded Doubly Fed Induction Generator

Amar Maafa, Hacene Mellah, Karim Benaouicha, Badreddine Babes (), Abdelghani Yahiou and Hamza Sahraoui
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Amar Maafa: Electrical Engineering Department, Faculty of Sciences and Applied Sciences, University of Bouira, Bouira 10000, Algeria
Hacene Mellah: Electrical Engineering Department, Faculty of Sciences and Applied Sciences, University of Bouira, Bouira 10000, Algeria
Karim Benaouicha: Electrical Engineering Department, Faculty of Sciences and Applied Sciences, University of Bouira, Bouira 10000, Algeria
Badreddine Babes: Research Center in Industrial Technologies—CRTI, P.O. Box 64, Algiers 16014, Algeria
Abdelghani Yahiou: Electrical Engineering Department, Faculty of Sciences and Applied Sciences, University of Bouira, Bouira 10000, Algeria
Hamza Sahraoui: Department of Electrical Engineering, Hassiba Benbouali University, Chlef 02180, Algeria

Sustainability, 2024, vol. 16, issue 21, 1-21

Abstract: This paper introduces a robust system designed to effectively manage and enhance the electrical output of a Wind Energy Conversion System (WECS) using a Cascaded Doubly Fed Induction Generator (CDFIG) connected to a power grid. The solution that was investigated is the use of a CDFIG that is based on a variable-speed wind power conversion chain. It comprises the electrical and mechanical connection of two DFIGs through their rotors. The originality of this paper lies in the innovative application of a fuzzy logic controller (FLC) in combination with a CDFIG for a WECS. To demonstrate that this novel configuration enhances control precision and performance in WECSs, we conducted a comparison of three different controllers: a proportional–integral (PI) controller, a fractional PID (FPID) controller, and a fuzzy logic controller (FLC). The results highlight the potential of the proposed system in optimizing power generation and improving overall system stability. It turns out that, according to the first results, the FLC performed optimally in terms of tracking and rejecting disturbances. In terms of peak overshoot for power and torque, the findings indicate that the proposed FLC-based technique (3.8639% and 6.9401%) outperforms that of the FOPID (11.2458% and 10.9654%) and PI controllers (11.4219% and 11.0712%), respectively. These results demonstrate the superior performance of the FLC in reducing overshoot, providing better control stability for both power and torque. In terms of rise time, the findings show that all controllers perform similarly for both power and torque. However, the FLC demonstrates superior performance with a rise time of 0.0016 s for both power and torque, compared to the FOPID (1.9999 s and 1.9999 s) and PI (0.0250 s and 0.0247 s) controllers. This highlights the FLC’s enhanced responsiveness in controlling power and torque. In terms of settling time, all three controllers have almost the same performance of 1.9999. An examination of total harmonic distortion (THD) was also employed to validate the superiority of the FLC. In terms of power quality, the findings prove that a WECS based on an FLC (0.93%) has a smaller total harmonic distortion (THD) compared to that of the FOPID (1.21%) and PI (1.51%) controllers. This system solves the problem by removing the requirement for sliding ring–brush contact. Through the utilization of the MATLAB/Simulink environment, the effectiveness of this control and energy management approach was evaluated, thereby demonstrating its capacity to fulfill the objectives that were set.

Keywords: wind energy conversion system (WECS); cascaded doubly fed induction generator (CDFIG); fractional-order PID controller (FPID); fuzzy logic controller (FLC) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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