Selected ‘Starter Kit’ energy system modelling data for Nigeria (#CCG)

Author:

Allington Lucy1ORCID,Cannone Carla1ORCID,Pappis Ioannis2ORCID,Barron Karla Cervantes3ORCID,Usher Will2ORCID,Pye Steve4ORCID,Brown Edward1ORCID,Howells Mark5ORCID,Walker Miriam Zachau6ORCID,Ahsan Aniq6ORCID,Charbonnier Flora6ORCID,Halloran Claire6ORCID,Hirmer Stephanie6ORCID,Taliotis Constantinos7ORCID,Sundin Caroline2,Sridha Vignesh2ORCID,Ramos Eunice2ORCID,Brinkerink Maarten8ORCID,Deane Paul8ORCID,Gritsevskyi Andrii9,Moura Gustavo10,Rouget Arnaud11,Wogan David12,Barcelona Edito12,Rogner Holger2ORCID

Affiliation:

1. STEER Centre, Department of Geography, Loughborough University

2. KTH Royal Institute of Technology

3. University of Cambridge

4. University College London

5. STEER Centre, Department of Geography, Loughborough University; Imperial College London

6. University of Oxford

7. KTH Royal Institute of Technology; Cyprus Institute, Nicosia

8. University College Cork

9. International Atomic Energy Agency

10. Federal University of Ouro Preto

11. International Energy Agency

12. Asia Pacific Energy Research Centre

Abstract

Abstract Energy system modelling can be used to assess the implications of different scenarios and support improved policymaking. However, access to data is often a barrier to starting energy system modelling in developing countries, thereby causing delays. Therefore, this article provides data that can be used to create a simple zero order energy system model for Nigeria, 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 organizations, journal articles, and existing modelling studies. This means that the dataset can be easily updated based on the latest available information or more detailed and accurate local data. These data were also used to calibrate a simple energy system model using the Open Source Energy Modelling System (OSeMOSYS) and two stylized scenarios (Fossil Future and Least Cost) for 2020-2050. The assumptions used and 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.

Publisher

Research Square Platform LLC

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