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| Hauptseite > Publikationsdatenbank > Kilometer-scale Atmospheric Simulations Indicate the Potential for Lower Cost Renewable Energy Systems in Southern Africa |
| Hauptseite > Publikationsdatenbank > Kilometer-scale Atmospheric Simulations Indicate the Potential for Lower Cost Renewable Energy Systems in Southern Africa |
| Conference Presentation (After Call) | FZJ-2026-05346 |
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2026
Abstract: Increasing the proportion of renewable energy in African energy systems is crucial for expanding access to electricity, and to support the global energy systems transition towards net-zero emissions. However, reliable energy system planning is often hindered by a lack of suitable, high-resolution meteorological information to adequately assess the renewable energy potential. Most assessments in Africa still rely on coarse-resolution reanalysis data products, such as ERA5 or MERRA-2. In this interdisciplinary case study, kilometer-scale meteorological data from an ICON regional atmospheric model simulation for southern Africa from 2017 to 2019, are used to design cost-optimised renewable energy systems across the model domain. Evaluation studies demonstrate that ICON accurately represents near-surface wind and solar irradiance, and more accurately reproduces the observed wind speeds at turbine hub height, as well as the corresponding wind power calculated with a state-of-the-art renewable energy simulation model, when compared with commonly used datasets. In a comparison of renewable energy potentials estimated with ERA5 and statistically downscaled data products, our ICON simulations revealed on average a 50% higher wind energy potential, while solar resource estimates were largely in agreement. These differences translate into a 14% reduction in total annual system costs for the cost-optimized energy systems designed on the basis of ICON. This is primarily due to a 13% reduction in required battery storage capacity compared to using the ERA5 reanalysis. This suggests that the costs of renewable energy systems in the region may be systematically overestimated in the past when based on coarse-resolution reanalysis input data to assess wind energy potential, which in turn may lead to suboptimal planning and investment decisions. Hence, the study emphasises the importance of kilometre-scale atmospheric simulations for reliable renewable energy resource assessment and energy system design, showcased here by novel ICON simulations for southern Africa, which arguably allow for a more realistic representation of the regional renewable energy potentials.
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