Techno-economic feasibility assessment for a standalone hybrid energy system integrating renewable energy sources

In this study, comprehensive techno-economic and environmental analyses are carried out on various combinations of hybrid renewable energy systems (HRES) intended to provide electricity to an off-grid location. The study investigates various scenarios integrating wind turbines (WT), photovoltaic (PV) panels, biogas generators (BG), batteries (BAT), and converters (CONV), and assesses their technical and economic performances. Economic analysis reveals that the system integrating PV/WT/BAT/CONV/BG demonstrates the lowest levelized cost of energy (LCOE) (0.278 $/kWh) and net present cost (NPC) (1.61 M$) of all the investigated systems. On the other hand, the system comprising BAT/CONV/BG has the highest LCOE (0.455 $/kWh) and NPC (2.63 M$) among all the configurations investigated. Machine learning techniques revealed that the Rational Quadratic Gaussian Process Regression model and the Wide Neural Network model achieved the highest accuracy in predicting the LCOE and CO₂ emissions, respectively. These results offer valuable insights into practical and reliable standalone HRES designs, particularly for regions without grid access.