| Name | PyPSA-Earth: An Python-based Open Optimisation Model of the Earth Energy System |
| Acronym | PyPSA-Earth |
| Methodical Focus | Optimization |
| Institution(s) | |
| Author(s) (institution, working field, active time period) | |
| Current contact person | Davide Fioriti |
| Contact (e-mail) | dummi@mail.de |
| Website | https://pypsa-meets-earth.github.io/projects.html |
| Logo |
|
|---|---|
| Primary Purpose | The PyPSA meets Earth initiative works on open modelling, open data, open source solver support and open communities for energy system planning. Many of the data, model, solver activities are neutral to the model framework, opening the door for collaboration also outside of the PyPSA space. The tools are developed and maintained by members of the multi-organizational PyPSA developer team https://pypsa.org/. |
| Primary Outputs | PyPSA-Earth is the first open-source global energy system model with data in high spatial and temporal resolution. It enables large-scale collaboration by providing a tool that can model the world energy system or any subset of it. This work is derived from the European PyPSA-Eur model using new data and functions. It is suitable for operational as well as combined generation, storage and transmission expansion studies. We work hard to extend the PyPSA-Earth model by end of this year to include sector-coupling, myopic and perfect pathway expansion capabilities. |
| Support / Community / Forum | |
| Framework | PyPSA |
| Link to User Documentation | https://pypsa-earth.readthedocs.io/en/latest/ |
| Link to Developer/Code Documentation | https://pypsa.readthedocs.io/en/latest/ |
| Documentation quality | excellent |
| Source of funding | Research and Industry |
| Number of developers | less than 50 |
| Number of users | less than 100 |
| Open Source | |
| License | GNU Affero General Public License v3.0 |
| Source code available | |
| GitHub | |
| Access to source code | https://github.com/pypsa-meets-earth/pypsa-earth |
| Data provided | all data |
| Collaborative programming |
| GitHub Organisation |
| Modelling software | Python |
| Internal data processing software | |
| External optimizer | Linopy |
| Additional software | |
| GUI |
| Modeled energy sectors (final energy) |
|
||||||
| Modeled demand sectors |
|
||||||
| Modeled technologies: components for power generation or conversion |
|
||||||
| Modeled technologies: components for transfer, infrastructure or grid |
|
||||||
| Properties electrical grid |
|
||||||
| Modeled technologies: components for storage |
|
||||||
| User behaviour and demand side management | |||||||
| Changes in efficiency | |||||||
| Market models | - | ||||||
| Geographical coverage | |||||||
| Geographic (spatial) resolution |
|
||||||
| Time resolution | hour, Flexible. But per default larger than hourly | ||||||
| Comment on geographic (spatial) resolution | Flexible | ||||||
| Observation period | 1 year, >1 year, Single period or multi-period possible | ||||||
| Additional dimensions (sector) |
|
| Model class (optimisation) | LP, MILP |
| Model class (simulation) | Bottom up, Top down |
| Other | |
| Short description of mathematical model class | |
| Mathematical objective | costs |
| Approach to uncertainty | Deterministic |
| Suited for many scenarios / monte-carlo | |
| typical computation time | less than a day |
| Typical computation hardware | Depends on complexity. Between 8 GB RAM - 250 GB RAM |
| Technical data anchored in the model | Yes, but can be swapped out |
| Interfaces | - PyPSA - Atlite - Linopy - Powerplantmatching - Earth-osm |
| Model file format | .py |
| Input data file format | csv, json, geojson, yaml, netCDF |
| Output data file format | csv, json, geojson, yaml, netCDF |
| Integration with other models | PyPSA-Earth-Sec |
| Integration of other models |
| Citation reference | - |
| Citation DOI | https://doi.org/10.1016/j.apenergy.2023.121096 |
| Reference Studies/Models | - |
| Example research questions | - |
| Model usage | Industry, NGOs, Research Institutes and Universities |
| Model validation |
|
| Example research questions | - |
| further properties | |
| Model specific properties | - |