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Selected ‘Starter kit’ energy system modelling data for selected countries in Africa, East Asia, and South America (#CCG, 2021)

Energy system modeling can be used to develop internally-consistent quantified scenarios. These provide key insights needed to mobilise finance, understand market development, infrastructure deployment and the associated role of institutions, and generally support improved policymaking. However, acc...

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Bibliographic Details
Published in:Data in brief 2022-06, Vol.42, p.108021, Article 108021
Main Authors: Allington, Lucy, Cannone, Carla, Pappis, Ioannis, Cervantes Barron, Karla, Usher, Will, Pye, Steve, Brown, Edward, Howells, Mark, Zachau Walker, Miriam, Ahsan, Aniq, Charbonnier, Flora, Halloran, Claire, Hirmer, Stephanie, Cronin, Jennifer, Taliotis, Constantinos, Sundin, Caroline, Sridharan, Vignesh, Ramos, Eunice, Brinkerink, Maarten, Deane, Paul, Gritsevskyi, Andrii, Moura, Gustavo, Rouget, Arnaud, Wogan, David, Barcelona, Edito, Niet, Taco, Rogner, Holger, Bock, Franziska, Quirós-Tortós, Jairo, Angulo-Paniagua, Jam, Krishnamurthy, Satheesh, Harrison, John, To, Long Seng
Format: Article
Language:English
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Summary:Energy system modeling can be used to develop internally-consistent quantified scenarios. These provide key insights needed to mobilise finance, understand market development, infrastructure deployment and the associated role of institutions, and generally support improved policymaking. However, access to data is often a barrier to starting energy system modeling, especially in developing countries, thereby causing delays to decision making. Therefore, this article provides data that can be used to create a simple zero-order energy system model for a range of developing countries in Africa, East Asia, and South America, which can act as a starting point for further model development and scenario analysis. The data are collected entirely from publicly available and accessible sources, including the websites and databases of international organisations, journal articles, and existing modeling studies. This means that the datasets can be easily updated based on the latest available information or more detailed and accurate local data. As an example, these data were also used to calibrate a simple energy system model for Kenya using the Open Source Energy Modeling System (OSeMOSYS) and three stylized scenarios (Fossil Future, Least Cost and Net Zero by 2050) for 2020–2050. The assumptions used and the results of these scenarios are presented in the appendix as an illustrative example of what can be done with these data. This simple model can be adapted and further developed by in-country analysts and academics, providing a platform for future work.
ISSN:2352-3409
2352-3409
DOI:10.1016/j.dib.2022.108021