## 1 Introduction
A chopper circuit and parallel capacitors are used to smooth the DC-link voltage by dissipating the excessive power in the DC-link circuit [15; 16]. Dynamic braking resistors connected to the stator [17] and a bridge type fault current limiter [18] are used to limit the stator and rotor overcurrents. A series-connected converter [19] and a dynamic voltage restorer [20] are used to keep the stator voltage constant under grid faults. In previous studies [21; 22], static VAR compensators or STATCOMs were used to supply extra reactive power to the grid during grid faults. Although the LVRT capability is enhanced through various types of equipment [13; 14; 15; 16; 17; 18; 19; 20; 21], this equipment requires additional converters or equipment, which increases the complexity and cost of the wind turbine system and decreases its reliability. The cascaded control system for the RSC described in [23] is also used to improve LVRT capability, where several PI controllers are used in the inner and outer loops. However, due to changes in the parameters of the grid during fault conditions, the conventional PI controller with a fixed gain is not sufficient to ensure the system stability of a large power system. The setting of the parameters of the PI controllers used in cascaded control is cumbersome, especially in power system applications that are difficult to express as a mathematical model or a transfer function. In [23], a Taguchi approach for optimum design of PI controllers in a cascaded control scheme was presented. However, this cascaded control strategy with the conventional PI controller in the inner loop cannot provide a large amount of reactive power. Thus, the strategy can stabilize only lower ratings of the SCIG. Therefore, using an fuzzy logic controller (FLC) in the inner loop of the rotor-side controller to more efficiently provide reactive power during fault periods is convenient. The FLC can handle nonlinear systems very effectively because it offers variable gain during transient conditions. Thus, the DFIG controlled by the FLC can stabilize a larger amount of SCIG. Moreover, the overall system cost can be decreased by incorporating a lower rating of the DFIG along with a higher rating of the SCIG. This is one of the novel features of the present paper. Therefore, the main contribution of the present paper is the design of a new control strategy based on fuzzy logic in the inner loop of the rotor-side controller for the DFIG to improve the LVRT capability and increase the capacity of the SCIG-based WF. Detailed modeling and control strategies of the overall system are presented. In order to evaluate the effectiveness of the proposed controller, transient and dynamic analyses are performed. Real wind-speed data measured on Rishiri Island, Hokkaido, Japan are considered in the dynamic analysis. The transient performance of the overall system composed of SGs, an FLC-controlled DFIG, and an SCIG is compared with that composed of a DFIG with the conventional PI-controlled RSC presented in [23]. Finally, the proposed control strategy is found to be very effective for ensuring the stability of a large power system. Moreover, the capacity of the installed SCIG can be increased. The remainder of the present paper is organized as follows. Section 2 presents the wind turbine model. Section 3 presents the DFIG model, and the design procedure of the proposed FLC is introduced in Section 4. Section 5 deals with the power system model. Section 6 briefly describes the LVRT requirements for wind power. The simulation results and a discussion of the performance of the proposed and conventional methods are presented in Section 7. Finally, Section 8 summarizes the findings and concludes the paper.