The openENTRANCE H2020 project develops an open, transparent and integrated modelling platform for assessing low-carbon transition pathways in line with the European climate and energy targets. We are pleased to announce that the Open Platform is now open for third party users – that is to say modellers that are not part of the consortium.
The Open Platform consists of:
Click on the titles above to jump to the section that interests you, or go directly to the Open Platform website.
Datasets per European country for 4 low emission scenarios towards 2050 are available via the scenario explorer. The datasets are built upon statistical data for 2018 ad decarbonisation solutions for each fifth year from 2025 to 2050. The Scenario explorer also includes data about macro-economic consequences of the energy transition, and input and output data for the Open ENTRANCE case studies.
The scenarios published so far have been made publicly available under an open-source license on the openENTRANCE Scenario Explorer hosted by IIASA. More scenario results will be released in this resource as the project continues.
A key requirement for effective linking of models and consistent analysis is a common “nomenclature” as well as a shared and widely used data format.
openENTRANCE has extended the data format template developed by the Integrated Assessment Modeling Consortium (IAMC). Following an in-depth assessment of the data exchange requirements within the consortium for scenario data at a high spatial and temporal resolution, the IAMC format was further developed to cover sub-annual time resolution in both continuous-time formats (hourly data) and representative-timeslice formats (e.g., typical summer day).
As a complementary step, a shared list of variables, regions and units used across the entire project was implemented. Clear definitions and easy comparability to previous model comparison studies and parallel Horizon 2020 projects are of paramount importance to facilitate reusability of scenario results across modelling teams.
The development of the common nomenclature is conducted under an open-source license on GitHub so that the wider community can engage and benefit from this work. This repository makes available the nomenclature used within the consortium and serves as a discussion platform for extending the lists of terms. To facilitate the adoption of the common nomenclature across modelling teams, we also implemented several Python utility tools for validation and data migration.
See https://github.com/openENTRANCE/nomenclature for more information.
As one of the project’s milestones, openENTRANCE has successfully linked all models of the project’s modelling suite to the Scenario Explorer on the Open Platform.
The modelling suite covers the many dimensions of the clean energy transition and allows users to undertake integrated analyses going beyond the much more limited scope that each model offers separately. Early this year, a subset of the models in the suite were made fully open to allow researchers and policy makers in the scientific community and the industry not only to use the models for their own analyses, but also to modify them to better suit their needs.
The set of models made open allows their users to undertake a wide variety of analyses. There are both macro-economic models (REMES and EXIOMOD), multi-energy-carrier models (GUSTO, and GENESYS-MOD) and models focused on the electricity sector (EMPIRE, OPENTEPES, PLAN4EU, FRESH:COM). Most of the models can cover the entire EU, but there are also models focused on local energy needs (GUSTO, and FRESH:COM). The majority of the open energy models deal with the planning of the expansion and operation of the system, while GUSTO and FRESH:COM are focused on the operation. You will find on this website links to all the models in the suite that have been made open. User guides have been developed and are available for these models as well. Open licenses chosen for different models may differ to account for specific conditions for reuse of the code, defined by the corresponding modelling group.
Modelling and sharing scenario results requires substantial data wrangling and utility functions for unit conversion and aggregation/downscaling across sectoral, spatial and temporal scales. Rather than starting a new solution, the openENTRANCE project adopted the open-source Python package pyam for scenario processing and visualization.
As part of the model integration and scenario processing efforts conducted in openENTRANCE, the package was extended to include features for spatial and temporal aggregation and downscaling of scenario timeseries data.
By deciding to contribute to a well-established package that is already used by many other research teams in the energy modelling and integrated-assessment community, we avoid further fragmentation of resources and ensure an efficient, collaborative development of modelling tools.
Please see https://pyam-iamc.readthedocs.io for more information.
Open ENTRANCE developed a common entrance point for the different elements of The Open Platform.
openENTRANCE
open ENergy TRanstion ANalyses for a low-Carbon Economy
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 835896. The sole responsibility for the content of this website lies with the authors. It does not necessarily reflect the opinion of the European Union.
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