Dual Alternative Iteration Algorithm-Based Hierarchical MPC Strategy for Frequency Regulation Control and Active Power Allocation of Wind-storage Coupling System

This paper proposes a dual alternative iteration algorithm-based hierarchical MPC (DAMPC) strategy to realize frequency regulation control and active power allocation of wind-storage coupling system. The proposed DAMPC strategy involves a top-level grid frequency model predictive control (FMPC) strategy and a bottom-level multi-objective model predictive control (MMPC) strategy. In the FMPC strategy, to improve the frequency regulation performance, the active power reference of the wind-storage coupling system is generated by minimizing the frequency deviation, where the frequency reference is calculated by considering the active power deviation and its integral. In the MMPC strategy, the active power reference is optimally allocated to the wind turbine generators (WTGs) and battery energy storage system (BESS) by raising the minimum rotor speed, minimizing the pitch angle deviation and state of charge (SOC) deviation. To solve the multi-objective allocation optimization problem with high efficiency, a dual alternative iteration algorithm (DAIA) is proposed to update the global and local control vectors with the dual vector. Extensive simulations validate the effectiveness of the proposed DAMPC strategy in frequency regulation and active power allocation.