2021
DOI: 10.21203/rs.3.rs-479263/v2
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Selected ‘Starter Kit’ energy system modelling data for Egypt (#CCG)

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 Egypt, which can act as a starting point for further model development and scenario analysis. The data are collected entirely from publicly available and acc… Show more

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Cited by 4 publications
(10 citation statements)
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“…Due to the model's open-source nature, the input data are ideally free and publicly available. This overcomes a significant barrier when modelling the energy systems of countries with developing economies, as access to data has previously been proven to delay the decision-making process [30]. OSeMOSYS has a user-friendly Excel-based graphical user interface: the parameters are inputted via Climate Compatible Growth's (CCG) Simple and Nearly Done (clicSAND) interface to generate a *csv Excel output file.…”
Section: Methodsmentioning
confidence: 99%
“…Due to the model's open-source nature, the input data are ideally free and publicly available. This overcomes a significant barrier when modelling the energy systems of countries with developing economies, as access to data has previously been proven to delay the decision-making process [30]. OSeMOSYS has a user-friendly Excel-based graphical user interface: the parameters are inputted via Climate Compatible Growth's (CCG) Simple and Nearly Done (clicSAND) interface to generate a *csv Excel output file.…”
Section: Methodsmentioning
confidence: 99%
“…Due to the model's open-source nature, the input data is ideally free and publicly available. This overcomes a significant barrier when modelling the energy systems of countries with developing economies, as access to data has previously been proven to delay the decision-making process (Allington et al, 2021). OSeMOSYS has a user-friendly Excel-based graphical user interface: the parameters are inputted via Climate Compatible Growth's (CCG) Simple and Nearly Done (clicSAND) interface to generate a *csv Excel output file.…”
Section: Methodsmentioning
confidence: 99%
“…If specific input data could not be sourced at the national level, parameters, such as the capacity factors for power plants, were assumed to be similar to other Northern African countries and sourced from international organisations such as the International Energy Agency (IEA) and IRENA. The current energy system data, fuel costs, and transmission and distribution data were sourced from Climate Compatible Growth's (CCG) Starter Data Kit (SDK) (Allington et al, 2021) et al, 2023). Renewable constraints in the scenarios were based on policies from the New and Renewable Energy Authority (NREA) (2020) and IRENA (2018a).…”
Section: Model Data Sourcesmentioning
confidence: 99%
“…Due to the model's open-source nature, the input data is ideally free and publicly available. This overcomes a signi cant barrier when modelling the energy systems of countries with developing economies, as access to data has previously been proven to delay the decision-making process (Allington et al, 2021). OSeMOSYS has a user-friendly Excel-based graphical user interface: the parameters are inputted via Climate Compatible Growth's (CCG) Simple and…”
Section: Methodsmentioning
confidence: 99%
“…If speci c input data could not be sourced at the national level, parameters, such as the capacity factors for power plants, were assumed to be similar to other Northern African countries and sourced from international organisations such as the International Energy Agency (IEA) and IRENA. The current energy system data, fuel costs, and transmission and distribution data were sourced from Climate Compatible Growth's (CCG) Starter Data Kit (SDK) (Allington et al, 2021) (Allington et al, 2023). Renewable constraints in the scenarios were based on policies from the New and Renewable Energy Authority (NREA) (2020) and IRENA (2018a).…”
Section: Model Data Sourcesmentioning
confidence: 99%