Abstract
Autonomous micro-grids based on solar photovoltaic (PV) are one of the most promising solution to bring electricity access in many off-grid regions worldwide. Different storage/PV panel sizes can achieve the same level of service quality and an optimal design is typically identified by minimizing the levelized cost of electricity (LCOE). The cost optimization however relies on a number of economic hypothesis that come with large uncertainties. This work explores the robustness of the optimal sizing to variations of these hypotheses. Using SARAH2 irradiance data, we simulate the production of generic PV arrays for 200 locations in Africa. We then identify the configurations (storage, PV capacity) for which 95% of demand hours are satisfied. We then identify the configuration with the lowest LCOE for different PV/storage cost ratios. Our result show that the optimal configuration is highly dependent on the characteristics of the resource, and especially on its multi-scale co-variability with the electric demand. It is conversely relatively robust to changes in cost hypotheses. These results allow us to propose simple and robust sizing rules based on the characteristics of the solar resource and electrical demand that allow to guess the optimal configuration for different cost ratios with a good precision.
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