Adaptive frequency control with variable speed wind turbines using data-driven method

Abstract

The increasing penetration of variable speed wind turbines which use the traditional controllers reduces the inertia of power systems. Consequently, the maintenance of the frequency stability of power systems would be an important challenge. Currently, droop and inertial control methods have been used in variable speed wind turbines to control the frequency of the power network. Adjusting the gains on the droop and inertia control loops is very influential on the performance of wind turbines. However, due to the variable wind speed and power system conditions, the adjustment of the control coefficients which produces the best response in all situations seems to be impossible. In this paper, a new method for the adaptive adjustment of droop and inertia control loop gains in the doubly fed induction generator is presented. In order to eliminate the defects and problems of the power system and wind turbine modeling, it is also proposed to use the data-driven method, which only operates based on the input and output of the system. The second derivative of the error can be used to provide the adaptive adjustment of the droop and inertia control loop gains. This is done to enable faster control and to prevent frequency drooping. In the proposed control method, through implementing the K-vector nearest neighborhood, the output of the next moment is estimated. Then, the coefficients of the frequency control loops are adjusted adaptively, using the Hessian matrix. Simulation results demonstrated the proper performance of a data-driven based adaptive approach to increase the frequency nadir and to decrease the frequency variations of the power system in a steady state and a transient state.