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Harmonized and Open Energy Dataset for Modeling a Highly Renewable Brazilian Power System.
Deng, Ying; Cao, Karl-Kiên; Hu, Wenxuan; Stegen, Ronald; von Krbek, Kai; Soria, Rafael; Rochedo, Pedro Rua Rodriguez; Jochem, Patrick.
Afiliação
  • Deng Y; German Aerospace Center (DLR), Institute of Networked Energy Systems, Curiestr. 4, 70563, Stuttgart, Germany. dengying8421@gmail.com.
  • Cao KK; German Aerospace Center (DLR), Institute of Networked Energy Systems, Curiestr. 4, 70563, Stuttgart, Germany.
  • Hu W; German Aerospace Center (DLR), Institute of Networked Energy Systems, Curiestr. 4, 70563, Stuttgart, Germany.
  • Stegen R; German Aerospace Center (DLR), Institute of Networked Energy Systems, Curiestr. 4, 70563, Stuttgart, Germany.
  • von Krbek K; German Aerospace Center (DLR), Institute of Networked Energy Systems, Curiestr. 4, 70563, Stuttgart, Germany.
  • Soria R; Department of Mechanical Engineering, Universidad San Francisco de Quito, Diego de Robles y Vía Interoceánica, Campus Cumbayá, 170901, Quito, Ecuador.
  • Rochedo PRR; Energy Planning Program, Graduate School of Engineering (COPPE), Universidade Federal do Rio de Janeiro, Centro de Tecnologia, Bloco C, Sala 211, Cidade Universitaria, Ilha do Fundão, 21941-972, Rio de Janeiro, Brazil.
  • Jochem P; German Aerospace Center (DLR), Institute of Networked Energy Systems, Curiestr. 4, 70563, Stuttgart, Germany.
Sci Data ; 10(1): 103, 2023 02 22.
Article em En | MEDLINE | ID: mdl-36813797
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.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies País/Região como assunto: America do sul / Brasil Idioma: En Revista: Sci Data Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Alemanha País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies País/Região como assunto: America do sul / Brasil Idioma: En Revista: Sci Data Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Alemanha País de publicação: Reino Unido