Short-term frequency regulation of power systems based on DFIG wind generation

Short-term frequency regulation is important for the safety and efficiency of power systems based on wind generation units. However, unmodeled dynamics and stochastic disturbances in wind speed and load present a challenge for frequency regulation. This paper offers a frequency regulation scheme that caters for doubly fed induction generator-based wind power units requiring short-term frequency regulation. To this end, a data-driven additive controller is cast into a stochastic framework. Since the survival information potential (SIP) of a random variable has some advantages over information potential, the SIP of frequency deviation is presented in order to simultaneously evaluate droop control and inertial control. Thereafter, the optimal additive control coefficient can be obtained using a particle swarm optimization technique and an arithmetic mean filter. Finally, simulation results demonstrate the effectiveness of the proposed approach over traditional additive control strategies.