Ensemble Kalman Filter based Dynamic State Estimation of PMSG-based Wind Turbine

Abstract

Permanent magnet synchronous generators (PMSGs) are commonly used in wind power generation because of less maintenance cost and flexible speed control. Dynamic state estimation is beneficial in wide area monitoring and control (WAMAC). Because, it enables the access to non-measurable variables. This paper proposes a nonlinear dynamic state estimation based on ensemble Kalman filter (EnKF) for PMSG-based wind turbines. The results of the proposed method are evaluated by comparing with extended Kalman filter (EKF) and unscented Kalman filter (UKF).