Adaptive Control Strategy for Time-Varying Power System Based on Continuous Markov Model

Concerning the variation of power system operating condition caused by time-varying factors such as wind generator output power fluctuation and load change, an adaptive control strategy for time-varying power system based on continuous Markov model is proposed in this paper. First, the Lyapunov functional containing the continuous Markov time-varying power system model is constructed, and the robust stochastic stability theorem with H infinity norm bound gamma is derived using the Dynkin lemma. On this basis, according to the Schur complement theorem, the robust stochastic stability LMI (linear matrix inequality) which satisfies the disturbance attenuation degree gamma and the minimum variance constraint is derived considering the system operating conditions steady-state variance constraint. And then, through transforming the LMI to the minimization problem of linear objective function, the matching controller of each operating condition is solved. Finally, the stochastic gradient method is used to identify the system operating condition and determine the weighting coefficient of each controller, thus the adaptive control strategy is established. Time-domain simulation tests show that, the proposed control strategy could effectively suppress cascading disturbances as well as avoid the problem of mismatch between current operating condition and the fixed fault set. Besides, the impact on power system caused by controller switching is reduced.