PyPSA - Revision history

Tom Brown at 15:44, 28 January 2018

2018-01-28T15:44:22Z

Tom Brown at 15:43, 28 January 2018

2018-01-28T15:43:19Z

Tom Brown at 11:54, 19 October 2017

2017-10-19T11:54:59Z

Tom Brown at 11:53, 19 October 2017

2017-10-19T11:53:57Z

Tom Brown at 12:37, 24 August 2016

2016-08-24T12:37:48Z

Tom Brown at 20:19, 21 March 2016

2016-03-21T20:19:22Z

Tom Brown: Created page with "{{Model |Full_Model_Name=Python for Power System Analysis |author_institution=FIAS |authors=Tom Brown, Jonas Hörsch, David Schlachtberger |contact_persons=Tom Brown |contact_..."

2016-03-21T20:17:05Z

Created page with "{{Model |Full_Model_Name=Python for Power System Analysis |author_institution=FIAS |authors=Tom Brown, Jonas Hörsch, David Schlachtberger |contact_persons=Tom Brown |contact_..."

New page

{{Model
|Full_Model_Name=Python for Power System Analysis
|author_institution=FIAS
|authors=Tom Brown, Jonas Hörsch, David Schlachtberger
|contact_persons=Tom Brown
|contact_email=brown@fias.uni-frankfurt.de
|website=http://www.pypsa.org/
|source_download=https://github.com/FRESNA/PyPSA
|text_description=PyPSA is a free software toolbox for simulating and optimising modern electric power systems that include features such as variable wind and solar generation, storage units and mixed alternating and direct current networks. PyPSA is designed to scale well with large networks and long time series.
|open_source_licensed=Yes
|license=GNU General Public License version 3.0 (GPL-3.0)
|model_source_public=Yes
|data_availability=all
|open_future=No
|modelling_software=Python, Pyomo
|processing_software=Pandas
|model_class=Electricity System Model,
|sectors=Electricity,
|technologies=Renewables, Conventional Generation
|decisions=dispatch, investment
|georegions=Germany (later Europe)
|georesolution=User dependent
|timeresolution=Hour
|network_coverage=transmission, distribution, AC load flow, DC load flow, net transfer capacities
|math_modeltype=Optimization, Simulation
|math_modeltype_shortdesc=Non-linear power flow; linear optimal power flow / investment optimisation
|math_objective=Cost minimization
|deterministic=Not covered (yet)
|is_suited_for_many_scenarios=No
}}

@@ Line 1: / Line 1: @@
 {{Model
 |Full_Model_Name=Python for Power System Analysis
 |author_institution=FIAS
 |authors=Tom Brown, Jonas Hörsch, David Schlachtberger
@@ Line 36: / Line 37: @@
 |is_suited_for_many_scenarios=Yes
 |montecarlo=No
-|citation_references=https://arxiv.org/abs/1707.09913
+|citation_references=Journal of Open Research Software, 2018, 6 (1)
 |report_references=https://pypsa.org/publications/
 |example_research_questions=Power flow analysis, market analysis, total system investment optimisation, contingency analysis, sector coupling

@@ Line 5: / Line 5: @@
 |contact_persons=Tom Brown
 |contact_email=brown@fias.uni-frankfurt.de
-|website=http://www.pypsa.org/
+|website=https://www.pypsa.org/
 |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.
@@ Line 36: / Line 36: @@
 |is_suited_for_many_scenarios=Yes
 |montecarlo=No
 |example_research_questions=Power flow analysis, market analysis, total system investment optimisation, contingency analysis, sector coupling
 |Model input file format=No

@@ Line 6: / Line 6: @@
 |contact_email=brown@fias.uni-frankfurt.de
 |website=http://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.
 |open_source_licensed=Yes
 |license=GNU General Public License version 3.0 (GPL-3.0)
@@ Line 15: / Line 18: @@
 |modelling_software=Python, Pyomo
 |processing_software=Pandas
-|model_class=Energy System Model,
+|External optimizer=All those supported by Pyomo
 |sectors=Electricity, Heat, Transport, User-defined
 |technologies=Renewables, Conventional Generation, CHP
 |decisions=dispatch, investment
 |georegions=Germany (later Europe)
@@ Line 28: / Line 35: @@
 |deterministic=Not explicitly covered, but stochastic optimisation possible
 |is_suited_for_many_scenarios=Yes
 |example_research_questions=Power flow analysis, market analysis, total system investment optimisation, contingency analysis, sector coupling
 }}

@@ Line 15: / Line 15: @@
 |license=GNU General Public License version 3.0 (GPL-3.0)
 |model_source_public=Yes
 |data_availability=all
 |open_future=No
@@ Line 27: / Line 28: @@
 |Storage (Heat)=No
 |decisions=dispatch, investment
-|georegions=Germany (later Europe)
+|georegions=Europe, China, South Africa
 |georesolution=User dependent
 |timeresolution=Hour