Harmonized and Open Energy Dataset for Modeling a Highly Renewable Brazilian Power System

Ying Deng, Karl Kiên Cao, Wenxuan Hu, Ronald Stegen, Kai von Krbek, Rafael Soria, Pedro Rua Rodriguez Rochedo, Patrick Jochem

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

3 Citas (Scopus)


Improvements in modelling energy systems of populous emerging economies are highly decisive for a successful global energy transition. The models used–increasingly open source–still need more appropriate open data. As an illustrative example, we take the Brazilian energy system, which has great potential for renewable energy resources but still relies heavily on fossil fuels. We provide a comprehensive open dataset for scenario analyses, which can be directly used with the popular open energy system model PyPSA and other modelling frameworks. It includes three categories: (1) time series data of variable renewable potentials, electricity load profiles, inflows for the hydropower plants, and cross-border electricity exchanges; (2) geospatial data on the administrative division of the Brazilian federal states; (3) tabular data, which contains power plant data with installed and planned generation capacities, aggregated grid network topology, biomass thermal plant potential, as well as scenarios of energy demand. Our dataset could enable further global or country-specific energy system studies based on open data relevant to decarbonizing Brazil’s energy system.

Idioma originalInglés
Número de artículo103
PublicaciónScientific Data
EstadoPublicada - 22 feb. 2023


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