Optimizing Hybrid Renewable Energy Systems for Enhanced Sustainability and Efficiency in Rural Communities

This research examines a Hybrid Renewable Energy System (HRES) that integrates different renewable and conventional energy sources, specifically combining photovoltaic, wind and fuel generators. The main objective is to optimize energy supply while minimizing fuel consumption through dynamic management of these different sources. Nonlinear optimization techniques, implemented through the CasADi library, effectively manage the intricate interactions between various energy sources. The developed algorithm determines optimal operating setpoints for each generator, carefully balancing system constraints while ensuring uninterrupted power delivery to meet load demands. The importance of this work lies in its practical applications, particularly for remote areas and islands with limited access to traditional electricity grids. The system demonstrates how HRES can effectively reduce dependence on fossil fuels, improve environmental sustainability, provide continuous and reliable energy supply, support local development in rural communities and promote energy independence.