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Maximum power point tracking (MPPT) techniques for wind turbines have a significant effect on renewable energy production. Therefore, the association of the indirect torque control of the switched reluctance generator (SRG) with the wind turbine considering the MPPT technique has been developed in this work. The proposed strategy has a great impact on the production of renewable energy using an SRG machine. The main steps to achieve the object of this work are: First, the wind turbine was modeled and simulated according to the MPPT. In the second step, the indirect torque control strategy, based on the hysteresis current control for SRG 12/8, was realized. This was undertaken using a proportional integral regulator and the hysteresis controller for the torque in order to obtain the appropriate switching based on an asymmetric bridge converter. Moreover, the SRG has high nonlinear characteristics. Thus, the modeling results of this kind of machine are obtained by the use of the finite element method, with its dynamic study performed by the unique estimation of the electromagnetic torque in its generator mode functioning. Finally, the indirect torque control technique of the SRG has also been associated with the MPPT technique to maximize the efficiency power coefficient. The obtained results approve and validate the efficiency of a proposed MPPT of the wind turbine associated with the SRG. This illustrates, simultaneously, the remarkable effects of the turn-switching angles on the operating performances and the high quality of the produced energy. The importance of the effect of varying the turn-switching angles is also presented and discussed.

The optimization of energy production in renewable energy systems is crucial to improve energy efficiency. In this context, the aim of this study focuses on maximizing the efficiency of a switched reluctance generator. This paper presents a novel approach to enhance the electrical power and efficiency of a switched reluctance generator by determining the optimal operating parameters based on the mechanical input power of the system. The proposed strategy consists of the following steps: First, an algorithm was developed that provides machine data for different power modes based on control parameters, including electrical and mechanical powers such as speed, torque, and turn-on and turn-off angles. In the next step, the obtained data were analyzed to identify the optimum points corresponding to the states with maximum power and efficiency for various scenarios. An algorithm for maximum power point tracking was also developed to determine the optimal parameters as a function of mechanical energy. Finally, the data and algorithms were integrated into the switched reluctance generator control system. Simulations were conducted to compare the proposed MPPT technique with other techniques. This comparison is essential to validate the effectiveness of the proposed strategy in achieving enhanced electrical power generation efficiency.