The expansion of renewable energies (RE) is progressing worldwide, but in many places there is a lack of reliable data and suitable modelling tools. This shortage also hinders the utilization of enormous RE potential in African countries. As part of the OASES research project, the Fraunhofer Institute for Energy Economics and Energy System Technology IEE and its partners have therefore established an open AU-EU ecosystem for energy system modelling. Alongside a tool for the automated detection of RE plants in satellite imagery, high-resolution RE time series were generated and can be seamlessly integrated into the enhanced and user-friendly IRENA FlexTool.
Transparent energy data and models are key to the successful transformation of energy systems and to the necessary security of supply. OASES therefore relies on open-source software and freely accessible data. The combination of satellite-based infrastructure detection, machine learning, high-resolution time series modelling, and user-friendly energy system analysis is innovative. This approach enables simple mapping and analysis of energy systems and promotes practical applications. In this way, the project contributes to reducing fossil fuel dependencies, expanding renewable capacities, and promoting international cooperation.
“With OASES, we have shown how open data and open-source software can advance the planning of the energy transition in Africa and Europe alike. We are particularly proud of the comprehensive capacity-building approach, which enables our partners to further develop and disseminate the tools we have developed,” says Malte Lindenmeyer, project coordinator at Fraunhofer IEE.
Partner network and open modelling solutions
Fraunhofer IEE coordinated the EU project “OASES – Development and Demonstration of a Sustainable Open Access AU-EU Ecosystem for Energy System Modelling,” contributing its expertise in potential analyses and capacity expansion modelling. Together with the University of Kassel, the VTT Technical Research Centre of Finland, the Council for Scientific and Industrial Research (South Africa), the Renewable Energies Development Center CDER (Algeria), Helwan University (Egypt), and the University of Venda (South Africa), the institute worked on practical solutions for open and user-friendly energy system modelling. The project was part of the EU's Horizon 2020 funding program, embedded in a subprogram for the establishment of long-term renewable energy partnerships between European and African countries (LEAP-RE). In addition to the European Union, the German Federal Ministry of Research, Technology, and Space (BMFTR) funded the project with a total volume of around 1.1 million euros. Work on OASES was completed in June 2025.
"By combining various Earth observation data, modern AI methods, and open modelling environments, we have succeeded in developing powerful tools that can be used directly even without programming knowledge,” says Maximilian Kleebauer, project manager at the University of Kassel.
Specifically, the project focused on machine learning models for the automated detection of photovoltaic and wind energy plants from satellite data. High-resolution time series for wind and solar are provided on an hourly basis in a 1 km × 1 km grid. In addition, the partners improved the existing IRENA FlexTool for energy system modelling and conducted six case studies from local to continental level. The key advance lies in a completely open and reproducible modelling system that can be applied with low thresholds in Africa and Europe and does not require proprietary software.
Practical validation in Africa and Europe
The suitability for use was validated in practical examples, such as PV and wind potential analyses in Algeria and grid expansion planning in South Africa. An important component was workshops with the IRENA FlexTool, the results of which are documented and can be directly incorporated into scenarios for the integration of renewable energies. "The OASES workshop in Algiers showed that renewable energy stakeholders in Algeria can use open-source software to conduct their own grid integration studies. At CDER, we support such work, thereby opening up a field that was previously largely reserved for electricity companies. At the same time, the event enabled us to promote exchange between industry, research, and government institutions by connecting private companies, universities, and research centers," explains Salim Bouchakour, project manager at CDER.
Ultimately, energy planners, grid operators, authorities, science, and politics all benefit equally: they gain access to precise and transparent analyses. These facilitate the expansion of renewable energies, enable well-founded scenarios for climate protection strategies, and promote efficient grid expansion.
As part of possible follow-up funding through the LEAP-SE follow-up program, the partners want to deepen the approaches developed and build additional case studies. The aim is to integrate the results more closely into national energy and climate strategies, thereby increasing their practical usefulness for policy and planning. In addition, the visualization of data and models via a user-friendly WebGIS tool is to be further expanded in order to make it even easier for decision-makers to access the information.
https://www.iee.fraunhofer.de/en/presse-infothek/press-media/2025/energyplanning...
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