The integration ofrotary-blades wind power installationsinto modern energy systems is becoming increasingly important due to the rapid growth of the share of renewable energy sources.At the same time, the operation of wind powerinstallationsis significantly different from traditional sources of generation, as their performance directly depends on the speed and direction of the wind,which are random in nature. This leads to significant fluctuations in the mechanical and electrical parameters of the system, complicates the process of regulating the frequency and active power of the generator, and creates increased requirements for the stability of the power system as a whole.The purpose of the study is to develop a mathematical model of a rotary-bladewind power installationtaking into account stochastic wind load for analyzing the dynamics of the installation and tuning the wind generator frequency control algorithms.Mathematical modeling is based on equations of rotational motion of the rotor and wind wheel, described through torque and moment of resistance forces, as well as on equations of air flow motion, taking into account turbulence and random changes in speed and direction. For the digital implementation of control algorithms, discretization of equations and recurrence relations for the rotor angular velocity and blade orientation angle are used. A simplified representation of torque and resistance in the form of polynomial dependencies provides sufficient accuracy with minimal computational costs and allows for effective testing of control algorithms in real time.The proposed model adequately reproduces the dynamic characteristics of the installation, takes into account stochastic wind factors, and allows for the implementation of digital control systems with high blade orientation accuracy. The use of the model ensures increased stability and efficiency of rotary-blade wind power installationsin real operating conditions, guarantees reliable electricity production under variable weather conditions, and preserves the key dynamic properties of the system with minimal resource consumption.Recieved2025-12-07Recieved2026-02-02Accepted2026-02-11
Ramsh et al. (2026) studied this question.