Model Predictive Control of SEIG coupled Micro-Hydro and PV-BSS-based remote Microgrid

This paper presents an extensive study on the application of model predictive control (MPC) for enhancing the performance of a self-excited induction generator (SEIG)-based micro-hydro system integrated with a photovoltaic (PV) array and battery storage system (BSS) in a remote microgrid. The hybrid energy system aims to provide reliable and sustainable power to isolated regions with limited or unavailable grid access. The proposed MPC strategy actively manages the power distribution between the micro-hydro generator, PV array, and battery storage system (BSS), ensuring voltage and frequency regulation of the microgrid. A power quality enhancement feature has also been incorporated in the developed MPC to mitigate the current harmonics generated by nonlinear loads and maintain better voltage at the point of common coupling (PCC). A laboratory prototype of the microgrid is developed and tested for various loads and operating conditions. Experimental results demonstrate the effectiveness of the developed MPC approach in maintaining stable microgrid voltage and frequency even under fluctuating load demands and PV power generation.