Hierarchical Distributed MPC for Optimal Active Power Control of DFIG Wind Farms

Abstract

This paper proposes an optimal active power control (OAPC) scheme based on hierarchical distributed model predictive control (HDMPC) for doubly fed induction generator (DFIG) wind farms. With the OAPC, the fatigue loads of WT are minimized in the wind farm controller while tracking the active power dispatch command. A hierarchical distributed optimization framework based on the alternating direction method of multipliers (ADMM) algorithm is developed to solve the MPC problem, reducing the computational burdens of the central controller. In the higher-level MPC (HMPC), the computation task involves calculating a simple objective function with equality constraints. In the lower-level MPC (LMPC) controller (individual WT controller), the computation task involves solving a local small-scale constrained optimization problem. A wind farm model with 10 DFIG WTs was built to verify the proposed OAPC scheme.