In this study, a single sensor‐based maximum power point tracking (MPPT) algorithm is presented for permanent magnet synchronous generator‐based wind energy conversion system (WECS). The MPPT method used in this study uses only the wind speed sensor to generate the reference point required for the maximum power. A discrete‐time controller is proposed to bring the system to the reference point determined by the MPPT algorithm. The designed MPPT controller consisting of a new discrete‐time reaching‐law approach and a discrete‐time integral sliding mode control (SMC). The designed discrete‐time SMC‐based controller is implemented by using an Acorn RISC Machine (ARM)‐based LM4F120 microcontroller, and its performance is examined on a WECS emulator prepared in the laboratory. The results got from the real‐time studies prove that the proposed controller has the satisfactory performance to bring the system to the MPP. The performance of the proposed controller is also compared with the conventional sliding mode controller and perturb and observe method. The obtained results proved that the proposed controller has a better performance than the other controllers in terms of the settling time and output voltage's ripple.

This study proposes a discrete‐time integral terminal sliding mode controller (DITSMC) integrated with a sensorless maximum power point tracking (MPPT) method for a permanent magnet synchronous generator (PMSG)‐based wind energy conversion system (WECS). The effects of the parameters of the proposed DITSMC on the convergence‐time and the error‐bound are investigated by the simulation studies. The dynamic performance of the DITSMC has been evaluated experimentally on a test bench for step‐type wind changes. The optimum coefficient between the output voltage of the generator and the extracted power from the WECS is determined only for a wind speed by offline studies. Then, the MPPT can be provided using this coefficient for all wind speeds in the operating range of the WECS without any mechanical sensor. Additionally, the experimental studies show that DITSMC has better performance than the PI controller in terms of the settling time and thus the efficiency of the WECS.

This research presents a combination of artificial neural network (ANN) with the grey wolf optimizer (GWO) to improve the power quality of a grid-connected distributed power generation system (DPGS). To assess the effectiveness of the proposed algorithm, a grid-tied of small-scale wind energy...

In this paper, a new maximum power point tracking (MPPT) method based on the Fibonacci search algorithm (FSA) is proposed for the wind energy conversion system (WECS). The conventional FSA is modified according to the requirements of the WECS to improve its performance as an MPPT algorithm. The performance of the proposed method is investigated for different wind-speed profiles such as step-type and stochastically varied wind speed. Also, the modified FSA based MPPT algorithm is compared with the conventional perturb and observe (CPO) and variable-step PO (VSPO) algorithms. The simulation results approve the superior performance of the proposed method over the CPO and VSPO in terms of maximum power extracted from the system. The real-time performance of the proposed method is also investigated for varying wind conditions in the form of step-up and step-down.

In this paper, a double integrator sliding mode controller (DISMC) via the mechanical sensorless maximum power point tracking (MPPT) method is suggested to extract maximum power from a wind energy conversion system (WECS). The controller is required to bring the system to the maximum power point reference generated by the MPPT method. However, the controller design for the WECS operated in a wide wind speed range is a challenging task due to its highly nonlinear behavior. In this study, to enhance the performance of the WECS, a voltage mode DISMC, which is not used before for the WECS, is offered. The dynamic performance of the proposed method, considering the different wind speed scenarios, is proved with the simulation studies. Additionally, the performance of the DISMC is compared with that of the conventional sliding mode controller for the same wind speed scenarios.