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

MethodsX. 2023 Mar 12:10:102120. doi: 10.1016/j.mex.2023.102120. eCollection 2023.

Abstract

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.

Keywords: Climate Compatible Growth; Data Collection and Manipulation Method for Starter Data Kits models; Data collection tool; Data2Deal; Energy system modelling; OSeMOSYS; U4RIA; clicSAND; data pipeline; open-access model; open-source; workflow.