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Stabilization of Constant Power Loads in DC Microgrid Systems Using an Adaptive Continuous Control Set Model Predictive Control

This paper represents an adaptive continuous control set model predictive control (CCS-MPC) to solve the disturbance-caused instability problems in a DC microgrid consisting of symmetrical parallel buck converters, constant voltage loads (CVL), and constant power loads (CPL). The symmetric model of the system is founded at first to describe and analyze the disturbance-caused instability problem. To mitigate the instability by taking the disturbances into consideration, the proposed adaptive controller is made from a double loop feedback controller and a feedforward estimation algorithm. In the voltage loop of the double loop controller, a capacitor dynamic-based voltage controller is developed, while in the current loop, a CCS-MPC algorithm is modified and applied. Meanwhile, a feedforward algorithm is developed to estimate the disturbance information and send it to the double loop controller to improve its robustness, so the composite controller can maintain the bus voltage fixed at its reference and the symmetrical equal current sharing. Finally, comparative MATLAB simulations and OPAL-RT hardware-in-the-loop experiments are conducted to verify the effectiveness and dynamic performance of the proposed algorithm towards other previous nonlinear controllers.