<![CDATA[Access to electricity remains a major challenge in sub-Saharan Africa, particularly in rural areas where grid extension is often costly and unviable. Standalone photovoltaic (PV) and/or wind power systems with battery storage represent a promising solution, yet they still face technical and economic barriers, especially related to sizing and storage costs. This paper proposes an innovative methodology for the selection and optimal sizing of such systems, integrating a predictive battery aging model based on the analysis of real charge/discharge cycles using the Rainflow algorithm and Miner’s rule. The methodology relies on four main techno-economic performance indicators: the Loss of Power Supply Probability (LPSP), the Levelized Cost of Energy (LCOE), the Capacity Factor (CF) of a wind turbine, and the Weighted Index of Complementarity and Productivity (WICP). It accounts for available resources, the user’s hourly consumption profile, and local climatic conditions. The methodology is applied to a rural site in Nagréongo, Burkina Faso. The results show that only a PV/battery system is technically and economically viable, while wind and hybrid configurations are excluded due to low wind potential, as indicated by CF and WICP values below acceptable thresholds. Furthermore, the analysis demonstrates that the optimal system configuration strongly depends on the hourly consumption profile, even for identical daily energy demands. Finally, comparison with the classical intuitive sizing method and the widely used HOMER Pro software shows that the proposed approach reduces the LCOE by more than 50% and about 20%, respectively, by accurately accounting for real battery aging, demand variability, and system idle periods.]]>
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