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

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 resource for: Clear Definitions of OSeMOSYS Parameters Description of Parameter Effects Understanding Policy Relevance of Parameters Residual Capacity Corrected

Techno-economic dataset for long-term energy systems modelling in Morocco. This includes data on electricity capacity by source, power plants costs, fossil fuel reserves, renewable energy potential and green hydrogen export demand.

This dataset details a scenario simulated using the Open Source energy MOdelling SYStem for Greece (OSeMOSYS-GR). The scenario assumes that natural gas, coupled with carbon capture and storage (CCS), will remain part of the electricity mix until 2050. Please note that natural gas and lignite power plants are modelled in an aggregated manner due to the confidentiality of their specific technoeconomic data.

Visualization template designed to support analysis and plotting of scenarios using OSeMOSYS ClicSAND.

The attached dataset is a model file that needs to be used with the code available in this GitHub link. This file (in concurrence with the OSeMOSYS code) can be used to create a linear programming file (LP file) to be solved using any mathematical optimisation solver like GLPSOL/CPLEX/GURUBI/CBC.

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. Other cooking technologies, such as gas, kerosene, and electric stoves, are also included in the model. This model version incorporates crops that significantly impact the food value chain, such as wheat and maize.

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 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 https://www.sciencedirect.com/science/article/pii/S0973082615300065

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 slide deck helps you troubleshoot in OSeMOSYS. It goes through the main culprits behind failing models and how to fix them. These include 1) unintended edits to the SAND file during editing, 2) errors during model development, such as when adding technologies, changing time slices, etc., and 3) errors during scenario development which create logical contradictions, such as when adding and changing constraints.

This dataset refers to the modelling exercise (version01_210616RCLEWs). The dataset contains the OSeMOSYS code used to run the modelling exercise, the model input data, the scenarios model data files, and the results. The code for the results visualization is available at https://github.com/KTH-dESA/teaching-CLEWs_visualization.

This is an update of version 01_210827 available at: https://doi.org/10.5281/zenodo.5293834

Hands-on exercise 3 part of the Energy and Flexibility Modelling Course.

Hands-on exercise 9 part of the Energy and Flexibility Modelling Course.

This set of files consists of an OSeMOSYS model file and five separate scenarios exploring electricity trade across the Eastern Mediterranean and Middle East Region. Two sensitivity scenarios are also available.

This dataset underpins the report provided to the project JRC-TEMBA - African decarbonisation pathways.

The report 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.

The energy supply systems of forty-seven African countries are modelled individually and connected via gas and electricity trade links to identify the cost-optimal solution to satisfy each country´s total final energy demand for the period 2015-2065. In this analysis, The Electricity Model Base for Africa (TEMBA) was extended to include a simple representation of the full energy system. It was also updated to include new data. It is run using the medium- to long-term Open Source Energy Modelling System tool (OSeMOSYS).

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.

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

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

The 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.