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Nowadays, most of the doubly fed induction generators (DFIGs) are equipped with rotor crowbar for the requirement of low voltage ride through (LVRT). The crowbar resistance is an important parameter, and it is selected taking rotor overcurrent and dc link overvoltage limits into consideration. However, the impact of grid impedance on the LVRT performance of DFIG and crowbar resistance is not adequately researched. This paper proposed an improved method to analyze the LVRT performance of DFIG system with rotor crowbar taking the influence of the grid impedance to fill this gap. The impedance of the present grid would be decreased in the future due to the installation of more wind farms to the grid. As a consequence, the performance of DFIG under LVRT with rotor crowbar is degraded. So the design rules of the crowbar resistance need to be reconstructed. Additionally, the analytical expression of the crowbar resistance is derived considering the grid impedance. The effectiveness of the proposed method is validated through theoretical analysis and MATLAB simulations.INDEX TERMS DFIG, crowbar, grid impedance, wind energy, low voltage ride through.

Summary With the rapid development of wind power, the variability and uncertainty of wind power have brought new problems and challenges to the secure and stable operation of the power systems. In this paper, based on the deterministic power flow solution, the probability theory and fuzzy sets theory are employed to implement systematic and thorough studies on power system fuzzy power flow solution incorporating uncertainties of wind power from different types of wind turbines squirrel cage induction generator, doubly fed induction generator and permanent magnet synchronous generator. The Weibull distribution with specific parameters is adopted as wind speed probability density model. With the possibility/probability consistency principle, the probability distribution of wind speed can be transformed into the possibility distribution of wind speed. In accordance with the simplified power vs wind speed curve of wind turbine, and with consideration of wake effect of wind farm, the fuzzy modeling for power output of wind farm is then presented. The proposed fuzzy power flow model incorporating wind power variability and uncertainty is linearized further for simplicity. A sensitivity analysis based method is employed to solve the fuzzy power flow involving different power characteristics of wind turbines. Finally, simulations are carried out on a real‐sized China's Jiangxi power grid, and some meaningful and important conclusions and comments are drawn based on the simulation results. Copyright © 2014 John Wiley & Sons, Ltd.

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