Stochastic Modeling and Stability Analysis of Wind Power System Based on Markov Theory

Abstract

With the scale of wind power integration expanding continuously, the random characteristic of power system is more and more prominent due to the volatility and intermittency of wind energy. Because of the fluctuations brought by wind power integration, the traditional deterministic analysis methods and the conventional stochastic differential equations are difficult to accurately analyze wind power system. In this paper, Markov theory is utilized to establish a stochastic Markov dynamic model for wind power systems by considering various uncertainties. Then, based on the developed model, Lyapunov energy function and M matrix are combined together to present the analytical method of stochastic mean stability and stochastic mean square stability of wind power system. Compared with the conventional stochastic differential equation analysis method, the proposed method can overcome the shortcomings that the stochastic stability cannot be analyzed when the system operating conditions change. Finally, simulation results are provided to verify the validity and correctness of the proposed method.