State Estimation for Synthetic Inertia Control System Using Kalman Filter

The growing penetration of wind power has deterio- rated the frequency response of power systems, and several meth- ods have been proposed for wind turbines to provide frequency response. Various proposals consider feedback controllers that require measurements of all state variables, and some of them are not physically measurable. This work develops a Kalman filter approach via LMI formulation to estimate immeasurable state variables for a wind power synthetic inertia algorithm. A simulation considering different wind speed and wind power penetration scenarios is presented to show numerical results. © 2021 IEEE.