Techno-economic dataset and assumptions for long-term energy systems modelling in the Dominican Republic (2024-2050).

The land transport sector, impacting fossil fuel consumption, has been selected as one of the sectors to apply decarbonization strategies. Energy systems modelling is an applied tool to evaluate scenarios and strategies that can be implemented in the transport sector to achieve energy transitions. These energy modelling tools need a dataset that allows the simulation of alternative scenarios of the systems. For this purpose, a collection and processing of technical-economic data is needed to ensure a quality input for simulation tools. This article presents a set of open data to create a model of the energy system of the Dominican Republic to assess alternative scenarios and develop strategies to achieve the energy transition in the land transport sector. This exercise is performed to support the energy planning policies of the country. Although the dataset is presented for the conditions of the Dominican Republic, the insight regarding data gathering and processing can be applied to other island countries. The data obtained are an open-access database of energy regulators, generation agents, and representatives of the generation, transmission, and distribution sector, as well as websites, databases of international organizations, scientific journals, and standards. Therefore, the data presented can be updated as the technical-economic information becomes public.

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.

Techno-economic data and assumptions for long-term energy systems modelling in Viet Nam.

Viet Nam is at a critical juncture in planning for its future energy mix due to its fast-growing economy and recent climate commitments. Robust modelling analyses examining the potential and practical energy mix alternatives are therefore key in providing key stakeholders with critical information on energy policy decision-making. The challenge is that a large volume of data is required to accurately model various energy pathways at the national scale. This data note, therefore, aims to bridge the current data gap by providing key information on input data and assumptions for long-term energy planning in Viet Nam. Historical and/or projected data regarding electricity generation and consumption, electricity imports and exports, fuel prices, emissions, refineries, power transmission and distribution, electricity generation technologies, and renewable energy potential and reserves for the years 2015 to 2050 are described in this article.

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.

Population cluster data to assess the urban-rural split and electrification in Sub-Saharan Africa.

Human settlements are usually nucleated around manmade central points or distinctive natural features, forming clusters that vary in shape and size. However, population distribution in geo-sciences is often represented in the form of pixelated rasters. Rasters indicate population density at predefined spatial resolutions, but are unable to capture the actual shape or size of settlements. Here we suggest a methodology that translates high-resolution raster population data into vector-based population clusters. We use open-source data and develop an open-access algorithm tailored for low and middle-income countries with data scarcity issues. Each cluster includes unique characteristics indicating population, electrification rate and urban-rural categorization. Results are validated against national electrification rates provided by the World Bank and data from selected Demographic and Health Surveys (DHS). We find that our modeled national electrification rates are consistent with the rates reported by the World Bank, while the modeled urban/rural classification has 88% accuracy. By delineating settlements, this dataset can complement existing raster population data in studies such as energy planning, urban planning and disease response.

Technoeconomic data adopted for the development of a long-term electricity supply model for the Hashmite Kingdome of Jordan.

Electrical generation in Jordan currently relies on imported fossil fuels. In the past, most imported fossil fuels were subsidised by neighbouring countries through grants and aid. This has led to a regulated market, with subsidised low-cost electrical energy consumers, and the government being the sole buyer and seller of electricity. With the ageing of the national electrical infrastructure, political instability in the region, and lack of funds for direct investment, other options needed to be pursued. Long term Power Purchase Agreements (PPA) were granted to Independent Power Producers (IPP) to encourage investment in capacity and infrastructure. In addition, long-term fuel contracts were signed to secure steady flow of primary fuel sources. Over the past few years, renewable energy penetration has increased rapidly, but without proper planning or taking into consideration long term PPA and fuel contracts. Data in regard to the current infrastructure, renewable energy technology, signed energy commitments and system operation assumptions are described in this article, which may be used for modelling and analysis. The Data were collected from annual reports from the different energy related entities in Jordan.

Resilience of the Eastern African electricity sector to climate driven changes in hydropower generation.

Notwithstanding current heavy dependence on gas-fired electricity generation in the Eastern African Power Pool (EAPP), hydropower is expected to play an essential role in improving electricity access in the region. Expansion planning of electricity infrastructure is critical to support investment and maintaining balanced consumer electricity prices. Variations in water availability due to a changing climate could leave hydro infrastructure stranded or result in underutilization of available resources. In this study, we develop a framework consisting of long-term models for electricity supply and water systems management, to assess the vulnerability of potential expansion plans to the effects of climate change. We find that the most resilient EAPP rollout strategy corresponds to a plan optimised for a slightly wetter climate compared to historical trends. This study demonstrates that failing to climate-proof infrastructure investments can result in significant electricity price fluctuations in selected countries (Uganda & Tanzania) while others, such as Egypt, are less vulnerable.

Technoeconomic assumptions adopted for the development of a long-term electricity supply model for Cyprus.

The generation mix of Cyprus has been dominated by oil products for decades. In order to conform with European Union and international legislation, a transformation of the supply system is called for. Energy system models can facilitate energy planning into the future, but a large volume of data is required to populate such models. The present data article provides information on key modelling assumptions and input data adopted with the aim of representing the electricity supply system of Cyprus in a separate research article. Data in regards to renewable energy technoeconomic characteristics and investment cost projections, fossil fuel price projections, storage technology characteristics and system operation assumptions are described in this article.

Discovery of phosphoric acid mono-{2-[(E/Z)-4-(3,3-dimethyl-butyrylamino)-3,5-difluoro-benzoylimino]-thiazol-3-ylmethyl} ester (Lu AA47070): a phosphonooxymethylene prodrug of a potent and selective hA(2A) receptor antagonist.

The discovery and structure-activity relationship of a series of hA(2A) receptor antagonists is described. Compound 28 was selected from the series as a potent and selective compound and was shown to be efficacious in an in vivo model of Parkinson's disease. It had acceptable ADME properties; however, the low intrinsic solubility of this compound was limiting for its developability, because the oral bioavailability from dosing in suspension was significantly lower than the oral bioavailability from solution dosage. As a consequence, prodrugs of 28 were prepared with dramatically increased aqueous solubility. The prodrugs efficiently delivered 28 into systemic circulation, with no detectable levels of prodrug in plasma samples. From this investigation, we selected 32 (Lu AA47070), a phosphonooxymethylene prodrug of 28, as a drug candidate.