Building and Calibrating a Country-Level Detailed Global Electricity Model Based on Public Data

Brinkerink, Maarten; Gallachóir, Brian P. Ó; Deane, Paul

doi:10.1016/j.esr.2020.100592

Cited by 129 publications

(229 citation statements)

References 30 publications

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“…The total power generation capacity in Zimbabwe is estimated at 1913.8 MW in 2018 [3,4,5,6]. The estimated existing power generation capacity is detailed in Table 1 below [3,4,5,6]. The methods used to calculate these estimates are described in more detail in Section 2.1.…”

Section: Existing Electricity Supply Systemmentioning

confidence: 99%

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

Cannone

Allington

Pappis

et al. 2021

Preprint

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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 Zimbabwe, 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 three stylized scenarios (Fossil Future, Least Cost and Net Zero by 2050) 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.

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Section: Existing Electricity Supply Systemmentioning

confidence: 99%

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

Cannone

Allington

Pappis

et al. 2021

Preprint

Self Cite

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“…The total power generation capacity in Lesotho is estimated at 72.3 MW in 2018 [3,4,5,6]. The estimated existing power generation capacity is detailed in Table 1 below [3,4,5,6]. The methods used to calculate these estimates are described in more detail in Section 2.1.…”

Section: Existing Electricity Supply Systemmentioning

confidence: 99%

“…Data on Lesotho's existing on-grid power generation capacity, presented in Table 1, were extracted from the PLEXOS World dataset [3,4,5] using scripts from OSeMOSYS global model generator [24]. PLEXOS World provides estimated capacities and commissioning dates by power plant, based on the World Resources Institute Global Power Plant database [5].…”

Section: Electricity Supply System Datamentioning

confidence: 99%

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

Allington¹,

Cannone²,

Pappis³

et al. 2021

Preprint

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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. This article therefore provides data that can be used to create a simple zero order energy system model for Lesotho, 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.

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“…Data on Sudan's existing on-grid power generation capacity, presented in Table 1, were extracted from the PLEXOS World dataset [3,4,5] using scripts from OSeMOSYS global model generator [24]. PLEXOS World provides estimated capacities and commissioning dates by power plant, based on the World Resources Institute Global Power Plant database [5].…”

Section: Electricity Supply System Datamentioning

confidence: 99%

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

Cannone

Pappis

Barron

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

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 Sudan, 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 three stylized scenarios (Fossil Future, Least Cost and Net Zero by 2050) 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.

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Building and Calibrating a Country-Level Detailed Global Electricity Model Based on Public Data

Cited by 129 publications

References 30 publications

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

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

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

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

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