Optimal active power control based on MPC for DFIG-based wind farm equipped with distributed energy storage systems

Abstract

An optimal active power control scheme based on model predictive control (MPC) is proposed for a doubly-fed induction generator (DFIG)-based wind farm equipped with distributed energy storage systems (ESSs). A two-stage optimal control scheme is proposed. In the first stage, the power reference of each WT and the total power command of ESSs are generated, aiming to reduce the fatigue load of WTs by minimizing variations of thrust force and shaft torque. In the second stage, the charge/discharge power of ESSs are optimized to achieve the fair power sharing and maximize the capacity margin. An MPC based optimization problem is formulated for the constrained multiple input and multiple output (MIMO) wind farm system. The dynamics of converters and WTs are taken into account by the MPC. With the proposed control scheme, the active power references are optimized between WTs and ESSs according to their local wind conditions. Fatigue loads of WTs are reduced efficiently by coordinating the DFIG-based WTs and distributed ESSs. A wind farm with 10 DFIG-based WTs was used to validate the control performance of the proposed optimal active power control scheme.