These are files with the outputs for each scenario in the paper "Analyzing Carbon Emissions Policies for the Bolivian Electric Sector" submitted to the journal Renewable and Sustainable Energy Transition.

A starter data kit for Tunisia

The Kenya-CLEWS model involves a model developed in the Open Source Energy Modeling System, OSeMOSYS. The use of GIS data to have an approximation of different land uses such as artificial surfaces, cropland, grassland, and tree covers, among others. Sectors include the cooking sector for urban and rural areas since its direct interconnection with forest land, i.e., wood and charcoal for cooking. The cooking sector is included because 55.1 percent of households in Kenya still use wood as their primary fuel for cooking. Firewood and charcoal supply 80 percent of the 6.2 million households that use a single fuel source [2]. Other cooking technologies such as gas, kerosene, and electric stoves are also included in the model. Regarding crops, this model version incorporates crops that significantly impact the food value chain, such as wheat and maize.

An open-source lite techno-economic dataset for long term energy systems modelling in the Republic of South Africa. Includes data on electricity generation and demand, electricity imports and exports, power transmission and distribution, residual capacity, capacity factor, operational lifetime, and fixed, variable and capital costs of electricity generation technologies. It also contains estimates for renewable potential and fossil fuel reserves in South Africa.

{"Six clicSAND files for OSeMOSYS Modelling in Viet Nam. The six files depict six different scenarios: 1. Power Development Plan 7-based scenario 2. Power Development Plan 8-based scenario 3. Renewable Energy Development Strategy-based scenario 4. Renewables-Led Pathway-based scenario 5. Net Zero 6. Clean Efficient Transition A Reference Energy System (RES) is also included to represent the relationship between estimated energy demands, energy conversion technologies, fuel mixes, and the resources required to satisfy the demands in the study."}

This dataset has been developed by KTH Division of Energy Systems Analysis in the Open Source Energy Modelling System (OSeMOSYS) , as further research of the existing TEMBA- model (The Electricity Model Base for Africa). A universal electricity access across the African continent is achieved by 2030 at a specific electricity consumption level. Several generation options are allowed in each nation, while cross-border electricity trade is enabled at existing and future planned levels. An indicative analysis of investment opportunities in the African electricity supply sector — Using TEMBA (The Electricity Model Base for Africa),2016. URL http://www.sciencedirect.com/science/article/pii/S0973082615300065.

A starter data kit for Egypt

OSMOSE WP1 DATASET This dataset has been compiled within the OSMOSE project, from the European Union’s Horizon 2020 research and innovation program, to support adequacy studies performed in Work-Package 1. Original data originate from two main sources : Plan4Res EU project and ENTSOE Pan European Common Database. ## Content The dataset contains 35 weather years (1982-2016) of data for 33 EU countries. General data granularity is country level. Some RES data are provided at the granularity of the 99-clusters of the e-Highway2050 project. - non-thermosensitive load profile (1 profile per country). Profiles sum to 1. (Source: Plan4Res and OSMOSE) - electric heating profiles (1 profile per country, 1 file per weather year). Profiles sum to 1 on average but not individually. (Source: Plan4Res and OSMOSE) - electric vehicles profiles (1 profile per country, 1 file per weather year). Profiles sum to slightly more than 1, depending on the weather scenario used. The difference to 1 corresponds to the thermo-sensitive effect due to the heating and the air-conditioning necessary for the well-functioning of the motor and the comfort of the passengers in this weather scenario. Its varies from country to country. (Source : OSMOSE, JRC for daily profiles, CS3 for weather and annual vehicle usage profiles) - onshore wind power-factor profiles (1 profile per country, 1 file per weather year and 1 profile per cluster, 1 file per weather year). (Source: PECD) - offshore wind power-factor profiles (1 profile per country per weather year and 1 profile per cluster per weather year). (Source: PECD) - solar pv power-factor profiles (1 profile per country, 1 file per weather year and 1 profile per cluster, 1 file per weather year). (Source: PECD) - hydro data (installed capacities (Run-of-River - ror, reservoir, Pump Storage Plants - PSP), volumes of the reservoirs and PSP, annual energies (ror and reservoir), per country and per cluster. Source: (OSMOSE based on MAF2018 and MAF2019) - hydro energies in GWh (ror - daily, reservoir - weekly, per country, 1 file per weather year). (Source: OSMOSE based on PECD) Full details of data processing performed by OSMOSE WP1 can be found in appendix B of OSMOSE deliverable D1.3 (available at https://www.osmose-h2020.eu/resource-center). ## AntaresSimulator studies The dataset also contains 2 study skeletons (country and cluster granulariry) and R scripts allowing to build studies to be run with AntaresSimulator (https://antares-simulator.org). To run these studies, unzip the archives "OSMOSE_DATASET" (which actually contains the dataset) and "ANTARES_R" (which contains R scripts) and follow the instructions in "ANTARES_R/README.md". ## Forecast data The dataset also comprises 10 weather years (1982-1991) of AntaresSimulator imput time-series corresponding to day-ahead forecast data for demand, solar and wind for 2030 and 2050. These forecast data have been computed based on the installed capacities defined in OSMOSE CGA scenario. Details of the computation process can be found in the report included in this distribution. ## OSeMOSYS dataset This file contains the OSeMOSYS parameter values (costs, demand, potentials, emission limits...) used in the study "Comparing the relative impacts of investment constraints and temporal detail on the outcomes of capacity expansion models applied to power systems". ## Licences Data is published under the terms of the "Creative Commons Attribution 4.0 International" licence (https://creativecommons.org/licenses/by/4.0) R code is published under the terms of the "MIT" licence (https://opensource.org/licenses/MIT) ## Acknowledgements The OSMOSE project(https://www.osmose-h2020.eu) received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 773406. Plan4Res EU project (https://zenodo.org/record/3802550) C3S (https://cds.climate.copernicus.eu) ENTSOE Pan European Common Database (https://zenodo.org/record/3702418 and https://zenodo.org/record/3985078) and MAF (https://www.entsoe.eu/outlooks/midterm/previous-maf-versions) e-Highway2050 project (https://cordis.europa.eu/project/id/308908/reporting)

A starter data kit for Cote D'Ivoire

A starter data kit for Niger

Scenario discovery SAMBA data files:

1) The folder SAMBA_324_datafiles.zip contains all 324 data files for the OSeMOSYS run.
Each of these files has a code on top referring to the combination that it represents.
The key to the levers is in the Excel file "Metafile". There the naming convention of technologies as well as corresponding combination for scenario are also available.
2) The Access database Scenario_discovery_database.mbd contans results from the 324 runs.
The key to the scenarios are in the Excel file "Metafile" tab "Scenario_key".
3) The file OSeMOSYS_SAMBA_161130.txt is the version OSeMOSYS that was used to run all scenarios.
4) The PRIM analysis is available on the GitHub repository: https://github.com/NMoksnes/Scenario_discovery

Description

Complexity science methods applied for policies provide a means of exploring the effects of various types of spatial and temporal drivers and constraints on the behavior of society and help scenario-forming and the development of sound policies through stakeholder consultations. In the context of policy-making following a five-component Nexus approach that includes Water, Energy, Food, Land Use, and Climate, System Dynamics Modelling is used for the holistic approach, since it presents various advantages, such as integrating different model outputs and handling system complexity via a building-block approach. To this end, the Nexus System Dynamics Model (Nexus_SDM) that establishes and quantifies the interlinkages among all five Nexus components for the national case study of Greece has been built in STELLA Professional (ISEE Systems--https://www.iseesystems.com/store/products/stella-professional.aspx). The methodology of data mapping and linking Nexus components in a complex system is followed, while outputs from thematic models are integrated producing an extensive multi-sectorial data set for the year 2010 that includes an exhaustive list of Water and Energy demands, Agricultural production and resulting agricultural value for 14 different crop types and 8 different animal types and their associated products. Green House Gas emissions from all sectors are presented as well. Data originate from open databases and national sources, such as Eurostat, the Greek National Statistical Authority (ELSTAT), the Hellenic Ministry of the Environment and Climate Change, the Association of Greek Tourism Enterprises, and the Independent Power Transmission Operator of Greece are collected. Additional data from thematic models E3ME (https://www.camecon.com/how/e3me-model/) and OSeMOSYS (http://www.osemosys.org/) are also integrated. Advanced disaggregation algorithms are employed in order to disaggregate annual national-scale data to fourteen River Basin Districts in Greece and 12 months of the year 2010. The data are used to map and quantify all interlinkages, identifying Nexus hotspots, i.e., which Nexus dimensions strongly affect others and threaten their security and which interlinkages are relatively weak. Mapping multiple Water-Energy-Food-Land Use-Climate Nexus data, and analyzing and quantifying all interlinkages among its Nexus components is critical in order to assess the Nexus, prioritize expenses, and set the agenda for achieving sustainability. Such data sets are necessary to make the Nexus concept operational for policymakers and stakeholders in a participatory process and it is an important step towards achieving the United Nations Sustainable Development Goals.

Categories

Sustainability, Water-Energy Nexus, Groundwater-Energy-Food-Ecosystems-Climate Nexus

Acknowledgments:

The data presented herein have been collected and processed within the project SIM4NEXUS. This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 689150.

Nikolaos Mellios, Chrysi Laspidou

Institutions: University of Thessaly

Data Source

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Image Source: Frontiers|Climate-Land-Energy-Water Nexus Models

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Technoeconomic data and assumptions for energy systems modelling in Ghana, including capital cost, fixed cost, variable cost, power plants' characteristics (e.g. list of existing power plants in Ghana, operational life, efficiency, capacity factors), fuels' prices and emission intensities, power demand/consumption/generation, residual capacity, fossil fuels' reserves, and renewable energy potentials in 2015-2065. This document is complementary to CCG Starter Data Kit for Ghana (Allington et al., 2023) as it updates it to ensure the OSeMOSYS models are closer to the Ghanaian context.

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

Seven clicSAND scenario files for Beyond the Dams: Combatting Hydropower Over-reliance & Securing Pathways for a Low-carbon Future for Laos' Electricity Sector using OSeMOSYS (Open-Source Energy Modelling System).

How to Visualise Results Online and Offline outline the steps required to re-run the scenarios on OSeMOSYS Cloud

Scenario Short Note outlines the steps to replicate the analysis and rebuild the scenarios

Annex - Input Data and Assumptions listing the data sources and assumptions in the scenarios

{"This dataset underpins the study "Conflicting objectives of energy development and water security in Africa". The study provides insights into energy supply and demand, power generation, investments and total system costs, water consumption and withdrawal as well as carbon dioxide emissions for the African continent. We developed a model to evaluate energy supply and water requirements to cover the energy needs of the African continent during the period 2015-2065. The model was developed using the open-source modeling system for long-term energy planning OSeMOSYS. The objective function is to minimise total energy system costs, rather than, for example, co-optimise the energy and water sectors. Other energy resources were also included in the model except for adding the water analysis, and the dataset was updated based on the latest available information. The OSeMOSYS model developed to conduct the study “Energy projections for African countries”, itself extended from the Electricity Model Base for Africa (TEMBA), was further extended, included exports for all fuels and water loss due to evaporation in hydropower plants. Furthermore, the latest available data on the energy system of Africa was also updated. The TEMBA model produces aggregate energy, and detailed power system results in each country in the African continent. The power sector results are also reported with power pool aggregation. The OSeMOSYS model and input data used to produce these results can be found at https://github.com/KTH-dESA/jrc_temba/tree/version1.4 The initial study was funded by the Joint Research Centre of the European Commission (contract number C936531 - JRC/PTT/2018/C.7/0038/NC)."}

This dataset contains the LEAP and OSeMOSYS output data for the manuscript Karamaneas et al., submitted to Renewable & Sustainable Energy Transition in September 2022.

This dataset presents the input and results for the study on the increase of Solar and Wind energy generation in the Brazilian Power System, as a way to achieve the NetZero by 2050. This study was conducted using the OSeMOSYS and Flextool as a deliverable of the Energy Modelling Platform for Latin America and The Caribbean Course - EMP-LAC 2023.

This file is the Base Data Collection File.

This is published as part of the MethodsX paper titled How to put together a Starter Data Kit from scratch? An extensive methodology to compile zero-order energy transition models. The main goal of the files published for this paper is to develop a set of credible data and an initial investment model for several developing countries.