Summary This article proposes an adaptive and modified Perturb and Observe (P&O) maximum power point tracking (MPPT) algorithm, using fuzzy logic step size controller, for a wind energy conversion system (WECS) based on wound rotor synchronous generator. The modified P&O controller uses additional current information of the dc‐link, to decrease power oscillation around MPP, and choose the correct direction of the perturbation, while wind speed increase condition, depending on the sign of dc‐link current change. So, in this contribution, a modified drift‐free P&O algorithm was chosen because it gives better results, but the duty cycle step size in the proposed MPPT controller has been varied adaptively, using a fuzzy logic inference system based on the variation of the rectifier output power and the previous change of the duty cycle to get fast convergence until the MPP is reached in increasing and decreasing wind speed conditions. Performances and robustness of the proposed speed sensorless MPPT controller are evaluated in an experiment implementation, using a WECS emulator and dSpace DS1104 controller board, where experimental results show that the proposed method guarantees fast convergence with better energy quality and high robustness against speed or load change conditions.

<p>Electrical energy production based on wind power is gaining area as renewable resources in the recent years because it gets clean energy with minimum cost. The major challenge for wind turbines is the electrical and the mechanical failures which can occur at any time causing damages and therefore it leads to machine downtimes and to energy production loss. To avoid this problem, several methods have been developed and used. In this paper, we proposed an expert system based on fuzzy logic which can detect and diagnosis DFIG’s faults via the Stator current’s signatures. The fuzzy inference system exploits the root mean square values of the stator’s currents according to expert’s rules to diagnosis the DFIG’s state. The smart proposed expert system is verified using simulations done under Matlab/Simulink. The obtained results are very interesting and show the efficiency of the proposed strategy.</p>

The diagnosis of wind energy conversion systems (WECS) turns out to be necessary because of their relatively high cost of operation and maintenance. Wind turbines are hard-to-access structures, and they are often located in remote areas. Therefore, a remote diagnosis (e-diagnosis) is required. This paper proposes an alternative approach for the e-diagnosis of a WECS based on the discrete wavelet transform (DWT) and frequency analysis of the aero generator stator currents. To validate this approach, real-time hardware in the loop (HIL) is used to simulate in real-time the mathematical model of the induction generator on the OPAL-RT OP5600 platform to generate the stator currents and the rotor speed. The DWT is applied to the current signal, to generate the DWT signal, which has a huge number of points that are not supported for direct transmission by the Arduino Mega RobotDyn because of its limited sample time. The absolute values of the DWT peak points (MDWT) are sent as point’s packages form to the diagnosis station via the ESP8266 integrated Wi-Fi board of the Arduino Mega RobotDyn to monitor the SCIG states and determine the number of broken bars.

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Summary Wind turbine emulators (WTE) have become a necessity for testing, developing, and improving design and control strategies in the renewable energy domain. The aim of this paper is to realize an experimental standalone wind energy conversion system emulator (WECSE) with improved torque and current control strategy using a nonlinear PI controller. The prototype was developed with a separately excited DC motor to simulate the wind turbine by providing the required speed and torque for power generation using a directly driven wound‐rotor synchronous generator and a power conversion system controlled by a modified drift‐free Perturb and Observe (P&O) Maximum Power Point Tracking algorithm (MPPT). The DC motor torque is controlled by an nonlinear PI controller regulator for an estimated current reference through a chopper driven by a dSPACE control board where the MATLAB/Simulink platform is used for wind turbine simulation. The proposed method was validated by experimental tests for different wind speeds and was compared with the conventional method. The experimental results have demonstrated that the control, emulation, and MPPT performances of the proposed method are significantly better.