diff --git a/paper/paper.md b/paper/paper.md index 485b373..d5d978c 100644 --- a/paper/paper.md +++ b/paper/paper.md @@ -44,7 +44,7 @@ Costa Rica has excelled for nature protection and leadership to fight climate ch ``OSeMOSYS-CR`` is an Energy System Optimization Model (ESOM) based on the Open Source energy Modelling System (OSeMOSYS) [@HOWELLS20115850] that follows a bottom-up approach, from energy sources to demands, to establishing the most cost-effective technological transitions towards a deep decarbonisation in the energy sector of Costa Rica. The model focuses on the transport sector (passenger and freight) and its relationship with the electricity system. Alternatives energy carriers such as hydrogen and biofuels are also considered. The use of these fuels leads to the inclusion of technologies such as electric vehicles, hydrogen-fueled heavy freight and the electric train. ``OSeMOSYS-CR`` was built on a countrywide scale using available national data. Annual weather patterns were also incorporated in the analysis by considering the effect of rainy and dry months. -The modelling framework is executed using Python. The process starts with the scenario building, which is done through a data structure that quantifies the information generated by stakeholders as inputs for the model. The modelling process begins with comma-separated values (CSV) files containing the parameters of the model (editable if needed). A first module translates the CSV files to a text file (txt) suitable to GNU MathProg versions, which should then be executed with the OSeMOSYS code. A second module executes the linear optimisation process using the GLPK package and generates a CSV output file that allows the visualisation of the results. The results provide inputs for the generation of actions, government laws, executive orders or international commitments. Figure 1 presents a simplified representation of the general process. The release of ``OSeMOSYS-CR`` pursues to support the transparency of the model and the collaboration through knowledge transfer with other teams. The model can serve as a framework for future developers, interested in the implementation of ESOMs. +The modelling framework is executed using Python. The process starts with the scenario building, which is done through a data structure that quantifies the information generated by stakeholders as inputs for the model. The modelling process begins with comma-separated values (CSV) files containing the parameters of the model (editable if needed). A first module translates the CSV files to a text file (txt) suitable to GNU MathProg versions, which should then be executed with the [OSeMOSYS code](http://github.com/OSeMOSYS/OSeMOSYS). A second module executes the linear optimisation process using the GLPK package and generates a CSV output file that allows the visualisation of the results. The results provide inputs for the generation of actions, government laws, executive orders or international commitments. Figure 1 presents a simplified representation of the general process. The release of ``OSeMOSYS-CR`` pursues to support the transparency of the model and the collaboration through knowledge transfer with other teams. The model can serve as a framework for future developers, interested in the implementation of ESOMs. ![General Framework for support national energy-relate policy, with OSeMOSYS-CR.](Framework.PNG) @@ -52,7 +52,7 @@ The modelling framework is executed using Python. The process starts with the sc The model combines more than one hundred commodities and two hundred technologies. A simple representation of the model, including primary energy supply (i.e., renewable, fossil fuel imports, biomass, and electricity imports), groups of technologies (i.e., power plants, vehicles, and distribution systems), energy demands by sector (i.e., industrial, residential, commercial and agricultural) and transport requirements (i.e., passenger and cargo) is shown in Figures 2 and 3. The model includes a module for co-benefits related to the consumption of fossil fuels in transport which was used to calculate the effects on health, congestion, and the number of accidents in a cost-benefit assessment of the NDP [SRRN_2020]. The parametrisation of technologies includes costs, emissions, activity level, and capacities, according to their characteristics. -![Simple energy resource system of the electriciy sector in OSeMOSYS-CR.](ElectricityModel.png) +![Simple energy resource system of the electricity sector in OSeMOSYS-CR.](ElectricityModel.png) ![Simple energy resource system of the transport sector in OSeMOSYS-CR.](TransportModel.png) @@ -62,6 +62,6 @@ Ongoing projects, which aim at further exploring the use and applicability of th # Acknowledgements -This work was funded by the Interamerican Development Bank and the University of Costa Rica. The authors want to recognise the contribution from many stakeholders in Costa Rica in providing valuable data and discussing different aspects of the model that led to a robust model currently available in the country. +This work was funded by the Inter-American Development Bank and the University of Costa Rica. The authors want to recognise the contribution from many stakeholders in Costa Rica in providing valuable data and discussing different aspects of the model that led to a robust model currently available in the country. # References