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, 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

Changes in Cooling Degree Days (CDD) between the 1.5ºC and 2.0ºC IPCC Scenarios.

Ensembles of 2100 climate simulations were generated using the HadAM4P Atmosphere-only General Circulation Model (AGCM) from the UK Met Office Hadley Centre. Three scenarios (with 700 simulations each) were used: historical (2006-16), 1.5ºC and 2ºC. The simulations output were mean temperatures with a 6 hours timestep and a horizontal resolution of 0.833 longitude and 0.556 latitude. Simulations took place within climateprediction.net (CPDN) climate simulation which uses the Berkeley Open Infrastructure for Network Computing (BOINC) framework. Biases in simulated temperature data were identified and corrected through statistical downscaling using a quantile Mapping approach. Cooling degree days (CDDS) were calculated for the ensemble members (700 runs per scenario) using 18ºC temperature threshold. Then, annual mean CDDs and standard deviation per coordinate was obtained for the 1.5ºC and 2ºC scenarios

Designing a zero-order energy transition model: How to create a new Starter Data Kit

The Paris Agreement was signed by 192 Parties, who committed to reducing emissions. Reaching such commitments by developing national decarbonisation strategies requires significant analyses and investment. Analyses for such strategies are often delayed due to a lack of accurate and up-to-date data for creating energy transition models. The Starter Data Kits address this issue by providing open-source, zero-level country datasets to accelerate the energy planning process. There is a strong demand for replicating the process of creating Starter Data Kits because they are currently only available for 69 countries in Africa, Asia, and South America. Using an African country as an example, this paper presents the methodology to create a Starter Data Kit made of tool-agnostic data repositories and OSeMOSYS-specific data files. The paper illustrates the steps involved, provides additional information for conducting similar work in Asia and South America, and highlights the limitations of the current version of the Starter Data Kits. Future development is proposed to expand the datasets, including new and more accurate data and new energy sectors. Therefore, this document provides instructions on the steps and materials required to develop a Starter Data Kit. • The methodology presented here is intended to encourage practitioners to apply it to new countries and expand the current Starter Data Kits library. • It is a novel process that creates data pipelines that feed into a single Data Collection and Manipulation Tool (DaCoMaTool). • It allows for tool-agnostic data creation in a consistent format ready for a modelling analysis using one of the available tools

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, 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