An Enhanced Voltage Profile for Solar PV Following Converters in Microgrid Using Data-driven FCS-MPC

This paper proposes a data-driven finite control set model predictive control (FCS-MPC) to enhance the performance of solar photovoltaic (PV) systems in low-voltage microgrids. Reverse power flow can cause voltage violations, and to address this, reactive power control of PV inverters has gained significant attention as a potential solution. A comparative analysis of four reactive power control techniques was conducted: fixed power factor, scheduled power factor control, power factor control dependent on the injected active power, and FCS-MPC combined with Volt-Var control. The efficacy of the various control techniques was evaluated through high-resolution power-flow simulations, which were carried out using a three-phase time-series approach. The results show that combining data-driven FCS-MPC with the Volt-Var control technique outperformed the other control techniques. Furthermore, the proposed strategy provides effective voltage regulation, requiring less extensive trial-and-error testing than traditional proportional integrator (PI) control. The study highlights the importance of incorporating reactive power controls of solar PV converters with FCS-MPC to mitigate overvoltage issues and improve microgrid performance utilizing the MATLAB/Simulink platform.