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This article provides a large-scale dataset for South African energy system modeling intended to aid long-term energy planning. The dataset, which is accessible on Zenodo, contains comprehensive data on installed capacity, resource potentials, historical and projected electricity production and consumption, capacity factors, and capital, fixed, and variable costs. The data was rigorously collected from national institutions, international organizations, and scholarly journals and organized into an easy-to-use Excel workbook. This dataset is compatible with the open-source energy modeling system (OSeMOSYS) framework but can also be used in other energy modeling applications [1]. Following the U4RIA (ubuntu, retrievability, repeatability, reconstructability, interoperability, and auditability) principles [2], this dataset attempts to improve energy modeling efforts, supporting analysts, policy makers, and the scientific community in creating robust energy strategies. By lowering the complexity and time needed for data collection, this tool helps South Africa, and other comparable regions achieve more effective and efficient energy planning., (© 2024 Published by Elsevier Inc.)

This article introduces an openly accessible dataset aimed at supporting energy system modelling of decarbonisation pathways in the Philippines. The dataset was compiled through an extensive literature review, incorporating information from various sources such as the Philippines Department of Energy, academic publications, and international organisations. To ensure compatibility with OSeMOSYS modelling requirements, the data underwent processing and standardisation. It includes power plant data covering existing capacity from classified by grid, off-grid, and planned additions, as well as historical generation data. Additionally, the dataset provides historical and projected electricity demand from 2015 to 2050 segmented by sectors. It also offers technical potential estimates for fossil fuels and renewable energy sources, along with key techno-economic parameters for emerging technologies like floating solar PV, in-stream tidal, and offshore wind. The dataset is freely available on Zenodo, empowering researchers, policymakers, and private-sector actors to conduct independent energy modelling and analyses aligned with the U4RIA framework principles. Its open access encourages collaboration and facilitates informed decision-making to advance a sustainable energy future not only for the Philippines but also for broader global contexts., (© 2024 The Author(s).)

Indonesia's emission reduction commitment and clean energy transition target emphasises the importance of energy system modelling for analysing and projecting Indonesia's capacity, resource availability, and future conditions in achieving these objectives. Utilising energy systems modelling based on adequate and reliable data enables policymakers to select the most optimal alternatives in energy planning. Aligned with the U4RIA (Ubuntu, Retrievability, Repeatability, Reconstructability, Interoperability, Auditability) concept, this database may facilitate various related stakeholders in obtaining this comprehensive and detailed energy data, while the data gathering and processing can also be applied to other developing countries. This country-specific dataset covers the historical data of electricity generation, demand, installed capacity, capacity factor, technical lifetime, renewable energy potentials, costs, and its projections up to 2050. The data in this article is ready to be used for energy system and modelling research., (© 2024 The Author(s).)

Hydrogen is globally acknowledged as a versatile energy carrier crucial for decarbonization in multiple sectors. Many countries have initiated the development of national hydrogen roadmaps and strategies, recognizing hydrogen as a strategic resource for achieving sustainable energy transitions. Formulating these guidelines for future action demands a solid technical foundation to facilitate well-informed decision-making. Energy system modelling has emerged as a significant scientific tool to assist governments and ministries in designing hydrogen pathways assessments based on scientific outcomes. The first step in the modelling process involves gathering, curating, and managing techno-economic data, a process that is often time-consuming and hindered by the unavailability and inaccessibility of data sources. This paper introduces an open techno-economic dataset encompassing key technologies within the hydrogen supply chain, spanning from production to end-use applications. Energy modelers, researchers, policymakers, and stakeholders can leverage this dataset for energy planning models, with a specific focus on hydrogen pathways. The presented data is designed to promote modelling studies that are retrievable, reusable, repeatable, reconstructable, interoperable, and auditable (U4RIA). This enhanced transparency aims to foster greater public trust, scientific reproducibility, and increased collaboration amongst academia, industry, and government in producing technical reports that underpin national hydrogen roadmaps and strategies., (© 2023 The Author(s).)

Decarbonization pathways have emerged as a pivotal element of global climate change mitigation strategies. Energy system modelling is widely recognized as a tool to support the design of informed energy decarbonization policies. However, the development of energy models heavily relies on high-quality input data, which may pose significant challenges in developing countries where data accessibility is limited, incomplete, outdated, or inadequate. Moreover, while models may exist in countries, these are not publicly available; therefore, details cannot be retrieved, repeated, reconstructed, interoperable or auditable (U4RIA). This paper presents an open techno-economic energy dataset for Colombia that is U4RIA-compliant as it can be used transparently to model decarbonization pathways and support energy planning in the country. Despite being country-specific, most of the data is technology-based and thus applicable to other countries. Diverse sources, assumptions, and modelling guidelines are described to facilitate the creation of new datasets. The dataset enhances the availability of energy data for policymakers, stakeholders, and researchers, not only in Colombia but also in other developing countries., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors. Published by Elsevier Inc.)