Power coordination control strategy for AC-DC hybrid microgrids based on distributed economic model predictive control

AC-DC hybrid microgrids face challenges in dynamic power stability and economic collaborative optimization due to their heterogeneous AC-DC interconnection structure and the coupling characteristics of multiple power electronic devices. This paper proposes a distributed economic model predictive control strategy. By constructing a high-precision wind-solar-storage dynamic model that integrates the dynamic response of wind turbine pitch angles, converter switching characteristics, and energy storage power fluctuation penalties, a distributed predictive controller based on dynamic economic objectives is designed. This controller integrates stability objectives (voltage/frequency regulation) and economic objectives (minimizing switching losses, pitch angle adjustment losses, and energy storage power fluctuation penalties) into a unified framework, enabling collaborative power distribution between AC and DC subgrids. Simulations show that compared with the traditional distributed model predictive control strategy, the proposed strategy significantly improves total power smoothing capability, DC bus voltage stability, and AC bus frequency stability. Meanwhile, it reduces converter switching losses by 36.53% and wind turbine pitch angle adjustment losses by 25.81%. By reducing the depth of energy storage operation, the penalty cost of power fluctuations is reduced by 2.31%, thereby verifying its outstanding advantage in balancing stability and dynamic economy.