DFIG is generally used in wind turbines because of its many advantages. However, DFIGs are sensitive to the network faults. When a fault occurs, the DFIG rotor current is increased and its converters may be damaged. A general solution to protect the DFIG converters is crowbar protection. However, when the crowbar is activated, the rotor‐side‐converter is disconnected and DFIG control may be lost. Therefore, reducing the crowbar operation time is essential. The SFCL can present an efficient protection against severe faults. However, recovery time of SFCL has undesirable effects. In this study the impacts of SFCL on fault‐ride‐through capability of DFIG are investigated in detail by considering the thermal model of resistive‐type SFCL. The simulation results illustrate that by applying the SFCL, the rotor current is decreased and fault‐ride‐through capability of DFIG is enhanced. Finally, a novel approach to suppress unpleasant influences of nonzero recovery time of the SFCL is proposed.
Doubly fed induction generator (DFIG) based wind turbines are very sensitive to grid voltage variations. Therefore, low-voltage-ride-through (LVRT) and high-voltage-ride-through (HVRT) capabilities are employed to improve DFIG performance during grid faults and voltage swell events. In this paper, a superconducting magnetic energy storage (SMES) device with a PWM voltage source converter and a DC-DC chopper is proposed to enhance the DFIG LVRT and HVRT capabilities in an islanded microgrid simultaneously. The simulation results demonstrate that the SMES absorbs or releases energy from/to the microgrid during voltage swell events and fault condition respectively and consequently, improves the DFIG performance and enhances the DFIG LVRT and HVRT capabilities. The effectiveness of the proposed method is validated through detailed simulations in PSCAD/EMTDC.
In this paper, a new two-step optimization algorithm is introduced for optimal placement of a Wind Turbine Generator (WTG) in a distribution network. The locations and the maximum capacities of WTGs, as well as their optimum power factor, are determined simultaneously in two different steps. In the first step, the locations and power factors of the WTGs are considered as solutions of a meta-heuristic optimization algorithm and in the next step, the optimal capacities of the WTGs are determined analytically. A recently introduced optimization algorithm known as the Lightning Attachment Procedure Optimization algorithm is employed for the first step, and a fast analytical method is used for the second one. The objective function of the optimization problem is considered for annual energy loss minimization. The proposed approach is applied on 85-bus test system, and the results are discussed. Fast convergence, best global answer finding, and robustness are the characteristics of the proposed method, which are concluded from the results and discussion.
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