Voltage and Power Control of PV Energy based AC Microgrids using Model Predictive Control Approach

The development of microgrids is an advantageous option for integrating rapidly growing renewable energies. However, the stochastic nature of renewable energies and variable power demand has created many challenges like unstable voltage/frequency and complicated power management and interaction with the utility grid. In existing control techniques, the droop control is commonly adopted as a decentralized power sharing method at the cost of voltage deviations. Besides, conventional cascaded control featuring relatively slow dynamic response shows difficulties in handling the fluctuation of renewable energy outputs, leading to further voltage quality deterioration. Recently, predictive control with its fast transient response and flexibility to accommodate different constraints has presented huge potentials in microgrid applications with better performance. In this work, a parallel-inverter based ac microgrid with solar Photovoltaics (PVs) and Battery Energy Storage Systems (BESSs) is presented. Based on this configuration, a universal model predictive control method is proposed. The BESS system is integrated through a Model Predictive Current Control (MPPC) based bidirectional buck- boost converter, aiming to stabilize the dc-bus voltage for PV output smoothing. Furthermore, the parallel inverters are controlled by incorporating a Model Predictive Voltage Control (MPVC) scheme with Artificial Bee Colony (ABC) algorithm to ensure stable ac voltage output and proper load sharing. The proposed control strategy is validated by MATLAB/Simulink simulation.