Improving power quality in mini-grid by integration with solar power system using predictive control: a case study of Nyankorogoma hydro mini-grid

Abstract

The growing need for sustainable and reliable electricity in rural areas has led to the integration of renewable energy sources into mini-grids. However, power quality challenges arise due to fluctuations in solar irradiance and hydro resource availability. This study addresses these challenges by implementing Model Predictive Control (MPC) to optimize energy flow in the Nyankorogoma hydro mini-grid, enhancing voltage stability and reducing power losses. A mathematical model of the hybrid solar-hydro system was developed and simulated in MATLAB/Simulink, incorporating real operational data from Nyankorogoma. The MPC algorithm was applied to control a boost converter, ensuring smooth solar power integration. Simulation results demonstrate that MPC effectively mitigates voltage fluctuations and reduces Total Harmonic Distortion (THD), improving overall power quality. FFT analysis revealed a reduction in THD from 12.07% to 4.02% after implementing MPC, indicating a significant improvement in waveform quality. Additionally, energy previously lost in dump loads was redirected for productive use, increasing system efficiency. The findings confirm that MPC-based solar integration enhances mini-grid stability, making it a viable solution for renewable energy-based rural electrification. Further research should explore real-world implementation, battery storage integration, and artificial Neural network driven predictive control for improved energy management.