**1. Introduction**

Due to fluctuations in the price of fossil fuels, the interest in renewable energy sources is increasing day by day [1]. There are many methods of generating electricity from renewable sources, such as the wind turbine and solar panel. Wind turbines are among the most important of these methods. Wind turbines convert wind energy into electrical energy. Many types of generators are used in wind turbines [2]. A permanent magnet synchronous generator (PMSG) has recently begun to attract the attention of wind turbine manufacturers, due to its superior features. The PMSG is supplied to the electrical grid system by means of the grid side converter (GSC), machine side converter (MSC), and control systems [3,4]. The fault ride-through (FRT) capability is one of the important issues for the operation system of the wind turbine. The grid connection requirements (GCRs) involve the operational condition control of the distributed power system [5]. The GCRs have to provide efficiency and reliability to the electrical grid system. The wind turbine (WT) must remain connected to the electrical grid system during grid faults [6]. The fault ride-through is depicted in three stages [7]:


All these requirements must be considered in the design of the controller and power converter of the WT. This design increases the stability of the WT during a grid fault [8]. Therefore, many methods are proposed in the literature for the FRT capability enhancement of the PMSG.

A braking chopper (BC) system has been implemented to enhance the FRT capability of a PMSG based on a wind energy conversion system (WECS) during a grid fault [9–12]. This method has some advantages, such as low cost and a simple control structure, but BC does not enhance the power quality in the WT's output. The static synchronous compensator (STATCOM) has been implemented to analyze a dynamic mechanism for a wind farm [13]. A coordinating control system for wind turbines was presented in Reference [13]. However, STATCOM has disadvantages, such as high cost and additional hardware needs. The peak current limitation for a high-power PMSG was realized in Reference [14]. Maximum power point tracking (MPPT) was implemented in the GSC and MSC. An active crowbar is kept the DC link voltage value by using this method. A superconducting fault current limiter (SFCL) was implemented for the FRT enhancement of a PMSG in Reference [15]. The presented method achieved reductions in the fault currents in DC systems.

Recently, soft computing methods have started to develop rapidly with the development of computer technology. Soft computing methods are applied in real-world applications, such as renewable energy and automotive and motor control. Soft computing methods are widely implemented in wind power applications, such as for MPPT control, pitch control, fault diagnosis, wind power generation, wind turbine power control, and prediction of wind speed and power. Soft computing methods consist of four computing algorithms such as predictive method, genetic algorithm, artificial neural networks, and fuzzy logic controllers (Type 1 and Type 2).

Interval type-2 fuzzy logic control (IT-2 FLC) is a type of soft computing method that overcomes the uncertainties of any system [16]. Uncertainty is a natural part of intelligent systems in many applications. Fuzzy Type 1 does not fully deal with the uncertainties of intelligent systems. An IT-2 FLC system is designed to minimize the uncertainties of any system. The IT-2 FLC system has been implemented in industrial applications. For example, interval type-2 hesitant fuzzy sets (IT2HFSs) have been implemented to cope with the underground hydrogen storage site selection problem in Romania [17]. The IT-2 FLC system has been applied in wind power system applications, such as diagnosis, pattern recognition decision, classification, control, and time series prediction.

Mokryani et al. [18] introduced a fault ride-through method using the FLC algorithm for several wind turbines. The presented method was applied to adjust the reactive and active power generated by the generator during grid faults. The proposed algorithm was utilized for all grid fault cases and different locations. Tahir et al. [19] developed a low voltage ride-through (LVRT) method using an adaptive FLC algorithm for wind turbines based on a wound field synchronous generator (WFSG). The proposed method was applied to both power converters of a WT. The proposed control system improved the reactive power of the grid system and regulated the current of the grid side converter. Morshed and Fekih [20] presented a design and analysis of the FRT method for a wind turbine. A new fuzzy second order integral terminal sliding mode control was developed for the power electronic converters. The proposed system was employed in a wind turbine. The overcurrents of the rotor and the stator with the presented control system did not exceed 10%. Therefore, the voltage and current values of the generator were within acceptable ranges. Rashid and Ali [21] proposed to achieve an improved FRT capability based on a fuzzy logic controlled parallel resonance fault current limiter (FLC-PRFCL) for doubly fed induction generator (DFIG)-based wind farms. The effectiveness of the presented protecting control system was compared with conventional proportional-integral (PI) control, the bridge-type fault current limiter, and the crowbar circuit system. Bechkaoui et al. [22] introduced online monitoring of grid faults based on the FLC method for wind plants. The proposed method provided a diagnosis of two grid faults. These faults were open phase and short-circuit. The proposed method was implemented to define the stator condition with high certainty. The data of the whole system were generated under both faulty and healthy conditions. The authors indicate that the proposed method is quite efficient. However, Fuzzy Type 1 does not fully cope with the

uncertainties of complex systems, such as wind turbines. Several methods have been applied to deal with the uncertainties of complex systems in the literature [23–25]. In addition, in the literature, the interval type-2 FLC has started to be implemented to cope with the uncertainties of complex systems.

Yassin et al. [26] implemented a low voltage ride-through (LVRT) method using an interval type-2 FLC technique for a wind turbine. The input variables of the interval type-2 FLC technique were selected as the DC link voltage and rotor speed. There was irregularity between the delivered to the grid power and the generated active power. To protect from this harmful effect, the proposed method kept the DC link voltage constant. The authors indicate that the proposed algorithm is quite efficient. However, the interval type-2 FLC was implemented only to the MSC control during grid faults. In the normal operational condition, the system was controlled by a traditional control system (PI). The PI control system did not perform better than the IT-2 FLC in any aspect.

This paper proposes a new control approach using the IT-2 FLC method in the WT based on a PMSG to improve the transient stability during grid faults. An IT-2 FLC is designed to enhance the FRT performance of the PMSG. Unlike other studies in the literature, an IT-2 FLC was implemented to control the MSC and GSC of a PMSG during grid faults and normal operational conditions. The aim of the proposed control system is to maintain the generator connected with the grid system and to prevent the harmful effect of an overcurrent occurring during grid faults. The proposed IT-2 FLC is very simple, cost effective, and easy to implement in comparison to the conventional control system. All simulation results proved that the presented IT-2 FLC scheme has the capability to improve the FRT capability of a PMSG.

The rest of the paper is organized as follows: the wind energy conversion system is introduced in Section 2, the proposed protection control system of a PMSG is presented in Section 3, a review of the interval type-2 fuzzy logic system is given in Section 4, the simulation results validating the proposed methodology are presented in Section 5, and, finally, concluding remarks are provided in Section 6.
