Robust Predictive Control of Parametric Uncertainties in Islanded DC-Microgrids

This work proposes a robust predictive control strategy against inductive parametric uncertainties through model predictive control with integral action in islanded Direct current microgrid systems (DCMS). DCMS consist of numbers of parallel power converters to share load currents through the inductance of DC/DC converters. However, the inductance parameters are dependent on the physical implementation of the system, and their values may not match their nameplate. Such disparities may lead to unequal responses of the system, which can potentially reduce the performance of the DCMS operation.. First, the system model is generated based on the nominal values of the system. The model is transformed into parametric unmatch uncertainty to form a robust control problem, which is then translated into a model predictive control problem. The inductance variations are stabilized with the uncertainty dynamic algebraic Riccati equation through control law. The close-loop was generated with integral action to eliminate an error on DC-grid voltage for a wide range of parameter variations. The proposed approach not only eliminates an error on DC-grid voltage also ensures equal sharing load. Fast response and better performance were observed in the simulation results.