|
|
(3 intermediate revisions by one user not shown) |
Line 1: |
Line 1: |
| {{Model | | {{Model |
| |Full_Model_Name=Python for Power System Analysis | | |Full_Model_Name=Python for Power System Analysis |
| + | |Acronym=PyPSA |
| |author_institution=FIAS | | |author_institution=FIAS |
| |authors=Tom Brown, Jonas Hörsch, David Schlachtberger | | |authors=Tom Brown, Jonas Hörsch, David Schlachtberger |
| |contact_persons=Tom Brown | | |contact_persons=Tom Brown |
| |contact_email=brown@fias.uni-frankfurt.de | | |contact_email=brown@fias.uni-frankfurt.de |
− | |website=http://www.pypsa.org/ | + | |website=https://www.pypsa.org/ |
− | |source_download=https://github.com/FRESNA/PyPSA | + | |source_download=https://github.com/PyPSA/PyPSA |
| |text_description=PyPSA is a free software toolbox for simulating and optimising modern energy systems that include features such as variable wind and solar generation, storage units, sector coupling and mixed alternating and direct current networks. PyPSA is designed to scale well with large networks and long time series. | | |text_description=PyPSA is a free software toolbox for simulating and optimising modern energy systems that include features such as variable wind and solar generation, storage units, sector coupling and mixed alternating and direct current networks. PyPSA is designed to scale well with large networks and long time series. |
| + | |Support=https://groups.google.com/forum/#!forum/pypsa |
| + | |User documentation=https://pypsa.org/doc/ |
| + | |Source of funding=BMBF |
| |open_source_licensed=Yes | | |open_source_licensed=Yes |
| |license=GNU General Public License version 3.0 (GPL-3.0) | | |license=GNU General Public License version 3.0 (GPL-3.0) |
| |model_source_public=Yes | | |model_source_public=Yes |
| + | |Link to source=https://github.com/PyPSA/PyPSA |
| |data_availability=all | | |data_availability=all |
| |open_future=No | | |open_future=No |
| |modelling_software=Python, Pyomo | | |modelling_software=Python, Pyomo |
| |processing_software=Pandas | | |processing_software=Pandas |
− | |model_class=Energy System Model, | + | |External optimizer=All those supported by Pyomo |
| + | |GUI=No |
| + | |model_class=Energy System Model, |
| |sectors=Electricity, Heat, Transport, User-defined | | |sectors=Electricity, Heat, Transport, User-defined |
| |technologies=Renewables, Conventional Generation, CHP | | |technologies=Renewables, Conventional Generation, CHP |
| + | |Storage (Gas)=No |
| + | |Storage (Heat)=No |
| |decisions=dispatch, investment | | |decisions=dispatch, investment |
− | |georegions=Germany (later Europe) | + | |georegions=Europe, China, South Africa |
| |georesolution=User dependent | | |georesolution=User dependent |
| |timeresolution=Hour | | |timeresolution=Hour |
Line 28: |
Line 37: |
| |deterministic=Not explicitly covered, but stochastic optimisation possible | | |deterministic=Not explicitly covered, but stochastic optimisation possible |
| |is_suited_for_many_scenarios=Yes | | |is_suited_for_many_scenarios=Yes |
| + | |montecarlo=No |
| + | |citation_references=Journal of Open Research Software, 2018, 6 (1) |
| + | |citation_doi=https://doi.org/10.5334/jors.188 |
| + | |report_references=https://pypsa.org/publications/ |
| |example_research_questions=Power flow analysis, market analysis, total system investment optimisation, contingency analysis, sector coupling | | |example_research_questions=Power flow analysis, market analysis, total system investment optimisation, contingency analysis, sector coupling |
| + | |Model input file format=No |
| + | |Model file format=No |
| + | |Model output file format=No |
| }} | | }} |
Power flow analysis, market analysis, total system investment optimisation, contingency analysis, sector coupling