Feasibility design, comparative evaluation, and energy consumption prediction of standalone hybrid energy system for rural electrification in Ghana using machine learning models

This study investigated the feasibility and sustainability of standalone hybrid energy systems for rural electrification in Ghana. The problem addressed was the lack of electricity access in rural areas of Ghana, despite progress in increasing access rates in urban areas. The importance of this study lies in identifying a reliable, affordable, and environmentally sustainable solution to bridge the electrification gap. This study employed a comprehensive analysis of different system configurations, including Solar Photovoltaic (SPV), Diesel Generators (DG), and Battery Storage (BS), using the Hybrid Optimization of Multiple Electric Resources (HOMER) software. The integration of machine learning models into the design process was also explored to enhance the accuracy of energy consumption predictions. The economic, technical, and environmental aspects of each alternative are evaluated. The significant results obtained from the analysis showed that the optimal design for the standalone hybrid energy system consisted of a 112 kW SPV array, 80 kW DG, 342 kWh BS, and a 54-kW converter. The Levelized Cost of Energy (LCOE) obtained from this configuration was $0.0263/kWh, with a renewable fraction of 91.5 %. The Net Present Cost (NPC) of the system was also the lowest among the alternatives, amounting to $244,937. Further investigation of the Electric Distance Limit (EDL) of the optimal solution is 7.5 km which depicts that, although grid-connected electricity may seem more affordable, the proposed standalone hybrid energy system is a more viable option for remote communities that are far from the grid and makes it a suitable solution for addressing the electricity access gap in Ghana's rural areas.