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Considering the dynamic behavior of doubly‐fed induction generators (DFIGs) under the influence of random factors, this paper not only analyzes the phenomenon of stochastic instability and bifurcation of a DFIG dynamic variable in its random space when they are affected by environmental noise, but also proposes a method based on the Tkagi–Sugneo (T–S) fuzzy control strategy to control its stochastic bifurcation. First, a four‐dimensional stochastic dynamic DFIG model is established by using multiplicative white noise to simulate the influence of environmental noise on electrical variables, and stochastic central manifold theory is used to reduce the dimensionality of a planar model in the bifurcation neighborhood. Then, the stochastic stability of the model is investigated based on singular boundary theory, while the steady‐state probability density of the stochastic DFIG is determined using the Fokker–Plank–Kolmogorov equation to obtain the location and probability density of its stochastic P‐bifurcation. Finally, the influence of stochastic bifurcation behavior is eliminated by H∞‐fuzzy output feedback control. The numerical simulation results indicate that the location and probability of stochastic bifurcation in a DFIG will vary with the change in noise intensity, and the bifurcation parameter values and stochastic stability domain are obtained. The harm caused by random factors can be solved based on H∞‐fuzzy output feedback, which provides a theoretical basis for the stable operation of the DFIG system. [ABSTRACT FROM AUTHOR]

These days, the harmonic problem of wind power grid‐connected systems is becoming increasingly prominent due to the increase in the number of large‐scale centralized grid‐connected wind farms and the gradual trend of high‐proportion power electronics for source‐grid loads. The harmonic oscillation caused by power electronic equipment provides large‐scale propagating in the system, and the harmonic interaction makes the harmonic propagation more complex. First, the harmonic interaction of the system is simplified into the radiation relationship between the wind farm and each branch to solve the harmonic current propagation problem caused by the interaction in the multiple wind farms. Then, the branch harmonic current propagation analysis method is used to transfer harmonic impedance and generate the branch harmonic current decoupling. Second, a harmonic current propagation coefficient is proposed to quantitatively analyze the relationship between the harmonic current of the wind farm and the branch. Thereby, the quantitative analysis of the propagation characteristics for the wind farm harmonic current in the system branch is obtained. Finally, abundant simulations verify the effectiveness and feasibility of the proposed method. [ABSTRACT FROM AUTHOR]