Release Notes#

Upcoming Release#

  • Important: The configuration files are now located in the config directory. This counts for config.default.yaml, config.yaml as well as the test configuration files which are now located in config/test. Config files that are still in the root directory will be ignored.

  • Bugfix: Correct typo in the CPLEX solver configuration in config.default.yaml.

  • Renamed script file from PyPSA-EUR build_load_data to build_electricity_demand and retrieve_load_data to retrieve_electricity_demand.

  • Fix docs readthedocs built

  • Add plain hydrogen turbine as additional re-electrification option besides hydrogen fuel cell. Add switches for both re-electrification options under sector: hydrogen_turbine: and sector: hydrogen_fuel_cell:.

  • Remove vresutils dependency.

  • Add option to include a piecewise linear approximation of transmission losses, e.g. by setting solving: options: transmission_losses: 2 for an approximation with two tangents.

PyPSA-Eur 0.8.0 (18th March 2023)#

Note

This is the first release of PyPSA-Eur which incorporates its sector-coupled extension PyPSA-Eur-Sec (v0.7.0). PyPSA-Eur can now directly be used for high-resolution energy system modelling with sector-coupling including industry, transport, buildings, biomass, and detailed carbon management. The PyPSA-Eur-Sec repository is now deprecated.

  • The solve_network script now uses the linopy backend of PyPSA and is applied for both electricity-only and sector-coupled models. This requires an adjustment of custom extra_functionality. See the migration guide in the PyPSA documentation.

  • The configuration file config.default.yaml now also includes settings for sector-coupled models, which will be ignored when the user runs electricity-only studies. Common settings have been aligned.

  • Unified handling of scenario runs. Users can name their scenarios in run: name:, which will encapsulate results in a correspondingly named folder under results. Additionally, users can select to encapsulate the resources folder in the same way, through the setting run: shared_resources:.

  • The solver configurations in config.default.yaml are now modularized. To change the set of solver options, change to value in solving: solver: options: to one of the keys in solving: solver_options:.

  • The Snakefile has been modularised. Rules are now organised in the rules directory.

  • Unified wildcard for transmission line expansion from {lv} and {ll} to {ll}.

  • Renamed collection rules to distinguish between sector-coupled and electricity-only runs: cluster_networks, extra_components_networks, prepare_elec_networks, prepare_sector_networks, solve_elec_networks, solve_sector_networks, plot_networks, all.

  • Some rules with a small computational footprint have been declared as localrules.

  • Added new utility rules purge for clearing workflow outputs from the directory, doc to build the documentation, and dag to create a workflow graph.

  • The workflow can now be used with the snakemake --use-conda directive. In this way, Snakemake can automatically handle the installation of dependencies.

  • Data retrieval rules now retry download twice in case of connection problems.

  • The cutouts are now marked as protected() in the workflow to avoid accidental recomputation.

  • The files contained in data/bundle are now marked as ancient() as they are not expected to be altered by workflow changes.

  • Preparation scripts for sector-coupled models have been improved to only run for the subset of selected countries rather than all European countries.

  • Added largely automated country code conversion using country_converter..

  • Test coverage extended to an electricity-only run and sector-coupled runs for overnight and myopic foresight scenarios for Ubuntu, MacOS and Windows.

  • Apply black and snakefmt code formatting.

  • Implemented REUSE compatibility for merged code.

  • Merged documentations of PyPSA-Eur and PyPSA-Eur-Sec.

  • Added a tutorial for running sector-coupled models to the documentation (Tutorial: Sector-Coupled).

  • Deleted config.tutorial.yaml, which is superseded by test/config.electricity.yaml.

  • The mock_snakemake function now also takes configuration files as inputs.

  • The helper scripts helper.py and _helpers.py have been merged into _helpers.py.

  • The unused rule plot_p_nom_max has been removed.

  • The rule solve_network from PyPSA-Eur-Sec was renamed to solve_sector_network.

  • The plotting scripts from PyPSA-Eur (electricity-only) have been removed and are superseded by those from PyPSA-Eur-Sec (sector-coupled).

PyPSA-Eur Releases (pre-merge)#

PyPSA-Eur 0.7.0 (16th February 2023)#

New Features

  • Carriers of generators can now be excluded from aggregation in clustering network and simplify network (see exclude_carriers).

  • Added control for removing stubs in simplify_network with options remove_stubs and remove_stubs_across_countries.

  • Add control for showing a progressbar in atlite processes (show_progress). Disabling the progressbar saves a lot of time.

  • Added control for resolution of land eligibility analysis (see excluder_resolution).

Breaking Changes

  • The config entry snapshots: closed: was renamed to snapshots: inclusive: to address the upstream deprecation with pandas=1.4. The previous setting None is no longer supported and replaced by both, see the pandas documentation. Minimum version is now pandas>=1.4.

  • The configuration setting summary_dir was removed.

Changes

  • Configuration defaults to new technology-data version 0.5.0.

  • Fixed CRS warnings when projection of datasets was not specified.

  • Cleaned shape unary unions.

  • Increased resource requirements for some rules.

  • Updated documentation.

  • The documentation now uses the sphinx_book_theme.

Bugs and Compatibility

  • Bugfix: Corrected extent of natural protection areas in build_natura_raster.

  • Bugfix: Use correct load variables for formulating reserve constraints.

  • Bugfix: Use all available energy-to-power ratios for hydropower plants.

  • Bugfix: The most recent processing of the entsoegridkit extract required further manual corrections. Also, the connection points of TYNDP links were corrected.

  • Bugfix: Handle absence of hydropower inflow in EQ constraint.

  • Compatibility with pyomo>=6.4.3 in cluster_network.

  • Upgrade to shapely>=2.

  • Updated version of CI cache action to version 3.

  • Updated dependency constraints in environment.yaml.

  • Address various deprecation warnings.

PyPSA-Eur 0.6.1 (20th September 2022)#

  • Individual commits are now tested against pre-commit hooks. This includes black style formatting, sorting of package imports, Snakefile formatting and others. Installation instructions can for the pre-commit can be found here.

  • Pre-commit CI is now part of the repository’s CI.

  • The software now supports running the workflow with different settings within the same directory. A new config section run was created that specifies under which scenario name the created resources, networks and results should be stored. If name is not specified, the workflow uses the default paths. The entry shared_cutouts specifies whether the run should use cutouts from the default root directory or use run-specific cutouts.

  • The heuristic distribution of today’s renewable capacity installations is now enabled by default.

  • The marginal costs of conventional generators are now taking the plant-specific efficiency into account where available.

PyPSA-Eur 0.6.0 (10th September 2022)#

  • Functionality to consider shipping routes when calculating the available area for offshore technologies were added. Data for the shipping density comes from the Global Shipping Traffic Density dataset.

  • When transforming all transmission lines to a unified voltage level of 380kV, the workflow now preserves the transmission capacity rather than electrical impedance and reactance.

  • Memory resources are now specified for all rules.

  • Filtering of power plant data was adjusted to new versions of powerplantmatching.

  • The resolution of land exclusion calculation is now a configurable option. See setting excluder_resolution.

PyPSA-Eur 0.5.0 (27th July 2022)#

New Features

  • New network topology extracted from the ENTSO-E interactive map.

  • Added existing renewable capacities for all countries based on IRENA statistics (IRENASTAT) using new powerplantmatching version:

  • The corresponding config entries changed from estimate_renewable_capacities_from_capacity_stats to estimate_renewable_capacities.

  • The estimation is endabled by setting the subkey enable to True.

  • Configuration of reference year for capacities can be configured (default: 2020)

  • The list of renewables provided by the OPSD database can be used as a basis, using the tag from_opsd: True. This adds the renewables from the database and fills up the missing capacities with the heuristic distribution.

  • Uniform expansion limit of renewable build-up based on existing capacities can be configured using expansion_limit option (default: false; limited to determined renewable potentials)

  • Distribution of country-level capacities proportional to maximum annual energy yield for each bus region

  • The config key renewable_capacities_from_OPSD is deprecated and was moved under the section, estimate_renewable_capacities. To enable it, set from_opsd to True.

  • Add operational reserve margin constraint analogous to GenX implementation. Can be activated with config setting electricity: operational_reserve:.

  • Implement country-specific Energy Availability Factors (EAFs) for nuclear power plants based on IAEA 2018-2020 reported country averages. These are specified data/nuclear_p_max_pu.csv and translate to static p_max_pu values.

  • Add function to add global constraint on use of gas in prepare_network. This can be activated by including the keyword CH4L in the {opts} wildcard which enforces the limit set in electricity: gaslimit: given in MWh thermal. Alternatively, it is possible to append a number in the {opts} wildcard, e.g. CH4L200 which limits the gas use to 200 TWh thermal.

  • Add option to alter marginal costs of a carrier through {opts} wildcard: <carrier>+m<factor>, e.g. gas+m2.5, will multiply the default marginal cost for gas by factor 2.5.

  • Hierarchical clustering was introduced. Distance metric is calculated from renewable potentials on hourly (feature entry ends with -time) or annual (feature entry in config end with -cap) values.

  • Greedy modularity clustering was introduced. Distance metric is based on electrical distance taking into account the impedance of all transmission lines of the network.

  • Techno-economic parameters of technologies (e.g. costs and efficiencies) will now be retrieved from a separate repository PyPSA/technology-data that collects assumptions from a variety of sources. It is activated by default with enable: retrieve_cost_data: true and controlled with costs: year: and costs: version:. The location of this data changed from data/costs.csv to resources/costs.csv [#184].

  • A new section conventional was added to the config file. This section contains configurations for conventional carriers.

  • Add configuration option to implement arbitrary generator attributes for conventional generation technologies.

  • Add option to set CO2 emission prices through {opts} wildcard: Ep<number>, e.g. Ep180, will set the EUR/tCO2 price.

Changes

  • Add an efficiency factor of 88.55% to offshore wind capacity factors as a proxy for wake losses. More rigorous modelling is planned [#277].

  • Following discussion in #285 we have disabled the correction factor for solar PV capacity factors by default while satellite data is used. A correction factor of 0.854337 is recommended if reanalysis data like ERA5 is used.

  • The default deployment density of AC- and DC-connected offshore wind capacity is reduced from 3 MW/sqkm to a more conservative estimate of 2 MW/sqkm [#280].

  • The inclusion of renewable carriers is now specified in the config entry renewable_carriers. Before this was done by commenting/uncommenting sub-sections in the renewable config section.

  • Now, all carriers that should be extendable have to be listed in the config entry extendable_carriers. Before, renewable carriers were always set to be extendable. For backwards compatibility, the workflow is still looking at the listed carriers under the renewable key. In the future, all of them have to be listed under extendable_carriers.

  • It is now possible to set conventional power plants as extendable by adding them to the list of extendable Generator carriers in the config.

  • Listing conventional carriers in extendable_carriers but not in conventional_carriers, sets the corresponding conventional power plants as extendable without a lower capacity bound of today’s capacities.

  • Now, conventional carriers have an assigned capital cost by default.

  • The build_year and lifetime column are now defined for conventional power plants.

  • Use updated SARAH-2 and ERA5 cutouts with slightly wider scope to east and additional variables.

  • Resource definitions for memory usage now follow Snakemake standard resource definition mem_mb rather than mem.

  • The powerplants that have been shut down by 2021 are filtered out.

  • Updated historical EIA hydro generation data.

  • Network building is made deterministic by supplying a fixed random state to network clustering routines.

  • Clustering strategies for generator and bus attributes can now be specified directly in the config/config.yaml.

  • Iterative solving with impedance updates is skipped if there are no expandable lines.

  • The unused argument simple_hvdc_costs in add_electricity was removed.

  • Switch from Germany to Belgium for continuous integration and tutorial to save resources.

  • It is now possible to skip the progressbar for land eligibility calculations for additional speedup.

Bugs and Compatibility

  • Fix crs bug. Change crs 4236 to 4326.

  • powerplantmatching>=0.5.1 is now required for IRENASTATS.

  • Update rasterio version to correctly calculate exclusion raster.

  • It is now possible to run the workflow with only landlocked countries.

  • Bugfixes for manual load adjustments across years.

  • Enable parallel computing with new dask version.

  • Restore compatibility of mock_snakemake with latest Snakemake versions.

  • Script build_bus_regions: move voronoi partition from vresutils to script.

  • Script add_electricity: remove vresutils.costdata.annuity dependency.

  • Fix the plot_network snakemake rule.

  • Compatibility with pandas 1.4. Address deprecations.

  • Restore Windows compatibility by using shutil.move rather than mv.

Synchronisation Release - Ukraine and Moldova (17th March 2022)#

On March 16, 2022, the transmission networks of Ukraine and Moldova have successfully been synchronised with the continental European grid. We have taken this as an opportunity to add the power systems of Ukraine and Moldova to PyPSA-Eur. This includes:

_images/synchronisation.png

  • the transmission network topology from the ENTSO-E interactive map.

  • existing power plants (incl. nuclear, coal, gas and hydro) from the powerplantmatching tool

  • country-level load time series from ENTSO-E through the OPSD platform, which are then distributed heuristically to substations by GDP and population density.

  • wind and solar profiles based on ERA5 and SARAH-2 weather data

  • hydro profiles based on historical EIA generation data

  • a simplified calculation of wind and solar potentials based on the Copernicus Land Cover dataset.

  • electrical characteristics of 750 kV transmission lines

The Crimean power system is currently disconnected from the main Ukrainian grid and, hence, not included.

This release is not on the master branch. It can be used with

git clone https://github.com/pypsa/pypsa-eur
git checkout synchronisation-release

PyPSA-Eur 0.4.0 (22th September 2021)#

New Features and Changes

  • With this release, we change the license from copyleft GPLv3 to the more liberal MIT license with the consent of all contributors [#276].

  • Switch to the new major atlite release v0.2. The version upgrade comes along with significant speed up for the rule build_renewable_profiles.py (~factor 2). A lot of the code which calculated the land-use availability is now outsourced and does not rely on glaes, geokit anymore. This facilitates the environment building and version compatibility of gdal, libgdal with other packages [#224].

  • Implemented changes to n.snapshot_weightings in new PyPSA version v0.18 (cf. PyPSA/PyPSA/#227) [#259].

  • Add option to pre-aggregate nodes without power injections (positive or negative, i.e. generation or demand) to electrically closest nodes or neighbors in simplify_network. Defaults to False. This affects nodes that are no substations or have no offshore connection.

  • In simplify_network, bus columns with no longer correct entries are removed (symbol, tags, under_construction, substation_lv, substation_off) [#219]

  • Add option to include marginal costs of links representing fuel cells, electrolysis, and battery inverters [#232].

  • The rule and script build_country_flh are removed as they are no longer used or maintained.

  • The connection cost of generators in simplify_network are now reported in resources/connection_costs_s{simpl}.csv [#261].

  • The tutorial cutout was renamed from cutouts/europe-2013-era5.nc to cutouts/be-03-2013-era5.nc to accommodate tutorial and productive cutouts side-by-side.

  • The flag keep_all_available_areas in the configuration for renewable potentials was deprecated and now defaults to True.

  • Update dependencies in envs/environment.yaml [#257]

  • Continuous integration testing switches to Github Actions from Travis CI [#252].

  • Documentation on readthedocs.io is now built with pip only and no longer requires conda [#267].

  • Use Citation.cff [#273].

Bugs and Compatibility

  • Support for PyPSA v0.18 [#268].

  • Minimum Python version set to 3.8.

  • Removed six dependency [#245].

  • Update plot_network and make_summary rules to latest PyPSA versions [#270].

  • Keep converter links to store components when using the ATK wildcard and only remove DC links [#214].

  • Value for co2base in config.yaml adjusted to 1.487e9 t CO2-eq (from 3.1e9 t CO2-eq). The new value represents emissions related to the electricity sector for EU+UK+Balkan. The old value was too high and used when the emissions wildcard in {opts} was used [#233].

  • Add escape in base_network if all TYNDP links are already contained in the network [#246].

  • In solve_operations_network the optimised capacities are now fixed for all extendable links, not only HVDC links [#244].

  • The focus_weights are now also considered when pre-clustering in the simplify_network rule [#241].

  • in build_renewable_profile where offshore wind profiles could no longer be created [#249].

  • Lower expansion limit of extendable carriers is now set to the existing capacity, i.e. p_nom_min = p_nom (0 before). Simultaneously, the upper limit (p_nom_max) is now the maximum of the installed capacity (p_nom) and the previous estimate based on land availability (p_nom_max) [#260].

  • Solving an operations network now includes optimized store capacities as well. Before only lines, links, generators and storage units were considered [#269].

  • With load_shedding: true in the solving options of config.yaml load shedding generators are only added at the AC buses, excluding buses for H2 and battery stores [#269].

  • Delete duplicated capital costs at battery discharge link [#240].

  • Propagate the solver log file name to the solver. Previously, the PyPSA network solving functions were not told about the solver logfile specified in the Snakemake file [#247]

PyPSA-Eur 0.3.0 (7th December 2020)#

New Features

Using the {opts} wildcard for scenario:

  • An option is introduced which adds constraints such that each country or node produces on average a minimal share of its total consumption itself. For example EQ0.5c set in the {opts} wildcard requires each country to produce on average at least 50% of its consumption. Additionally, the option ATK requires autarky at each node and removes all means of power transmission through lines and links. ATKc only removes cross-border transfer capacities. [#166].

  • Added an option to alter the capital cost (c) or installable potentials (p) of carriers by a factor via carrier+{c,p}factor in the {opts} wildcard. This can be useful for exploring uncertain cost parameters. Example: solar+c0.5 reduces the capital cost of solar to 50% of original values [#167, #207].

  • Added an option to the {opts} wildcard that applies a time series segmentation algorithm based on renewables, hydro inflow and load time series to produce a given total number of adjacent snapshots of varying lengths. This feature is an alternative to downsampling the temporal resolution by simply averaging and uses the tsam package [#186].

More OPSD integration:

  • Add renewable power plants from OPSD to the network for specified technologies. This will overwrite the capacities calculated from the heuristic approach in estimate_renewable_capacities() [#212].

  • Electricity consumption data is now retrieved directly from the OPSD website using the rule build_electricity_demand. The user can decide whether to take the ENTSO-E power statistics data (default) or the ENTSO-E transparency data [#211].

Other:

  • Added an option to use custom busmaps in rule cluster_network. To use this feature set enable: custom_busmap: true. Then, the rule looks for custom busmaps at data/custom_busmap_elec_s{simpl}_{clusters}.csv, which should have the same format as resources/busmap_elec_s{simpl}_{clusters}.csv. i.e. the index should contain the buses of networks/elec_s{simpl}.nc [#193].

  • Line and link capacities can be capped in the config.yaml at lines: s_nom_max: and links: p_nom_max: [#166].

  • Added Google Cloud Platform tutorial (for Windows users) [#177].

Changes

  • Don’t remove capital costs from lines and links, when imposing a line volume limit (lv) or a line cost limit (lc). Previously, these were removed to move the expansion in direction of the limit [#183].

  • The mappings for clustered lines and buses produced by the simplify_network and cluster_network rules changed from Hierarchical Data Format (.h5) to Comma-Separated Values format (.csv) for ease of use. [#198]

  • The N-1 security margin for transmission lines is now fixed to a provided value in config.yaml, removing an undocumented linear interpolation between 0.5 and 0.7 in the range between 37 and 200 nodes. [#199].

  • Modelling hydrogen and battery storage with Store and Link components is now the default, rather than using StorageUnit components with fixed power-to-energy ratio [#205].

  • Use mamba (mamba-org/mamba) for faster Travis CI builds [#196].

  • Multiple smaller changes: Removed unused {network} wildcard, moved environment files to dedicated envs folder, removed sector-coupling components from configuration files, updated documentation colors, minor refactoring and code cleaning [#190].

Bugs and Compatibility

  • Add compatibility for pyomo 5.7.0 in cluster_network and simplify_network [#172].

  • Fixed a bug for storage units such that individual store and dispatch efficiencies are correctly taken account of rather than only their round-trip efficiencies. In the cost database (data/costs.csv) the efficiency of battery inverters should be stated as per discharge/charge rather than per roundtrip [#202].

  • Corrected exogenous emission price setting (in config: cost: emission price:), which now correctly accounts for the efficiency and effective emission of the generators [#171].

  • Corrected HVDC link connections (a) between Norway and Denmark and (b) mainland Italy, Corsica (FR) and Sardinia (IT) as well as for East-Western and Anglo-Scottish interconnectors [#181, #206].

  • Fix bug of clustering offwind-{ac,dc} generators in the option of high-resolution generators for renewables. Now, there are more sites for offwind-{ac,dc} available than network nodes. Before, they were clustered to the resolution of the network (elec_s1024_37m.nc: 37 network nodes, 1024 generators) [#191].

  • Raise a warning if tech_colors in the config are not defined for all carriers [#178].

PyPSA-Eur 0.2.0 (8th June 2020)#

  • The optimization is now performed using the pyomo=False setting in the pypsa.lopf.network_lopf(). This speeds up the solving process significantly and consumes much less memory. The inclusion of additional constraints were adjusted to the new implementation. They are all passed to the network_lopf() function via the extra_functionality argument. The rule trace_solve_network was integrated into the rule solve_network and can be activated via configuration with solving: options: track_iterations: true. The charging and discharging capacities of batteries modelled as store-link combination are now coupled [#116].

  • An updated extract of the ENTSO-E Transmission System Map (including Malta) was added to the repository using the GridKit tool. This tool has been updated to retrieve up-to-date map extracts using a single script. The update extract features 5322 buses, 6574 lines, 46 links. [#118].

  • Added FSFE REUSE compliant license information. Documentation now licensed under CC-BY-4.0 [#160].

  • Added a 30 minute video introduction and a 20 minute video tutorial

  • Networks now store a color and a nicely formatted name for each carrier, accessible via n.carrier['color'] and n.carrier['nice_name'] ``(networks after ``elec.nc).

  • Added an option to skip iterative solving usually performed to update the line impedances of expanded lines at solving: options: skip_iterations:.

  • snakemake rules for retrieving cutouts and the natura raster can now be disabled independently from their respective rules to build them; via config.*yaml [#136].

  • Removed the id column for custom power plants in data/custom_powerplants.csv to avoid custom power plants with conflicting ids getting attached to the wrong bus [#131].

  • Add option renewables: {carrier}: keep_all_available_areas: to use all available weather cells for renewable profile and potential generation. The default ignores weather cells where only less than 1 MW can be installed [#150].

  • Added a function _helpers.load_network() which loads a network with overridden components specified in snakemake.config['override_components'] [#128].

  • Bugfix in base_network which now finds all closest links, not only the first entry [#143].

  • Bugfix in cluster_network which now skips recalculation of link parameters if there are no links [#149].

  • Added information on pull requests to contribution guidelines [#151].

  • Improved documentation on open-source solver setup and added usage warnings.

  • Updated conda environment regarding pypsa, pyproj, gurobi, lxml. This release requires PyPSA v0.17.0.

PyPSA-Eur 0.1.0 (9th January 2020)#

This is the first release of PyPSA-Eur, a model of the European power system at the transmission network level. Recent changes include:

  • Documentation on installation, workflows and configuration settings is now available online at pypsa-eur.readthedocs.io [#65].

  • The conda environment files were updated and extended [#81].

  • The power plant database was updated with extensive filtering options via pandas.query functionality [#84 and #94].

  • Continuous integration testing with Travis CI is now included for Linux, Mac and Windows [#82].

  • Data dependencies were moved to zenodo and are now versioned [#60].

  • Data dependencies are now retrieved directly from within the snakemake workflow [#86].

  • Emission prices can be added to marginal costs of generators through the keywords Ep in the {opts} wildcard [#100].

  • An option is introduced to add extendable nuclear power plants to the network [#98].

  • Focus weights can now be specified for particular countries for the network clustering, which allows to set a proportion of the total number of clusters for particular countries [#87].

  • A new rule add_extra_components allows to add additional components to the network only after clustering. It is thereby possible to model storage units (e.g. battery and hydrogen) in more detail via a combination of Store, Link and Bus elements [#97].

  • Hydrogen pipelines (including cost assumptions) can now be added alongside clustered network connections in the rule add_extra_components . Set electricity: extendable_carriers: Link: [H2 pipeline] and ensure hydrogen storage is modelled as a Store. This is a first simplified stage [#108].

  • Logfiles for all rules of the snakemake workflow are now written in the folder log/ [#102].

  • The new function _helpers.mock_snakemake creates a snakemake object which mimics the actual snakemake object produced by workflow by parsing the Snakefile and setting all paths for inputs, outputs, and logs. This allows running all scripts within a (I)python terminal (or just by calling python <script-name>) and thereby facilitates developing and debugging scripts significantly [#107].

PyPSA-Eur-Sec Releases (pre-merge)#

PyPSA-Eur-Sec 0.7.0 (16th February 2023)#

This release includes many new features. Highlights include new gas infrastructure data with retrofitting options for hydrogen transport, improved carbon management and infrastructure planning, regionalised potentials for hydrogen underground storage and carbon sequestration, new applications for biomass, and explicit modelling of methanol and ammonia as separate energy carriers.

This release is known to work with PyPSA-Eur Version 0.7.0 and Technology Data Version 0.5.0.

Gas Transmission Network

  • New rule retrieve_gas_infrastructure_data that downloads and extracts the SciGRID_gas IGGIELGN dataset from zenodo. It includes data on the transmission routes, pipe diameters, capacities, pressure, and whether the pipeline is bidirectional and carries H-Gas or L-Gas.

  • New rule build_gas_network processes and cleans the pipeline data from SciGRID_gas. Missing or uncertain pipeline capacities can be inferred by diameter.

  • New rule build_gas_input_locations compiles the LNG import capacities (from the Global Energy Monitor’s Europe Gas Tracker, pipeline entry capacities and local production capacities for each region of the model. These are the regions where fossil gas can eventually enter the model.

  • New rule cluster_gas_network that clusters the gas transmission network data to the model resolution. Cross-regional pipeline capacities are aggregated (while pressure and diameter compatibility is ignored), intra-regional pipelines are dropped. Lengths are recalculated based on the regions’ centroids.

  • With the option sector: gas_network:, the existing gas network is added with a lossless transport model. A length-weighted k-edge augmentation algorithm can be run to add new candidate gas pipelines such that all regions of the model can be connected to the gas network. The number of candidates can be controlled via the setting sector: gas_network_connectivity_upgrade:. When the gas network is activated, all the gas demands are regionally disaggregated as well.

  • New constraint allows endogenous retrofitting of gas pipelines to hydrogen pipelines. This option is activated via the setting sector: H2_retrofit:. For every unit of gas pipeline capacity dismantled, sector: H2_retrofit_capacity_per_CH4 units are made available as hydrogen pipeline capacity in the corresponding corridor. These repurposed hydrogen pipelines have lower costs than new hydrogen pipelines. Both new and repurposed pipelines can be built simultaneously. The retrofitting option sector: H2_retrofit: also works with a copperplated methane infrastructure, i.e. when sector: gas_network: false.

  • New hydrogen pipelines can now be built where there are already power or gas transmission routes. Previously, only the electricity transmission routes were considered.

Carbon Management and Biomass

  • Add option to spatially resolve carrier representing stored carbon dioxide (co2_spatial). This allows for more detailed modelling of CCUTS, e.g. regarding the capturing of industrial process emissions, usage as feedstock for electrofuels, transport of carbon dioxide, and geological sequestration sites.

  • Add option for regionally-resolved geological carbon dioxide sequestration potentials through new rule build_sequestration_potentials based on CO2StoP. This can be controlled in the section regional_co2_sequestration_potential of the config.yaml. It includes options to select the level of conservatism, whether onshore potentials should be included, the respective upper and lower limits per region, and an annualisation parameter for the cumulative potential. The defaults are preliminary and will be validated the next release.

  • Add option to sweep the global CO2 sequestration potentials with keyword seq200 in the {sector_opts} wildcard (for limit of 200 Mt CO2).

  • Add option to include Allam cycle gas power plants (allam_cycle).

  • Add option for planning a new carbon dioxide network (co2network).

  • Separate option to regionally resolve biomass (biomass_spatial) from option to allow biomass transport (biomass_transport).

  • Add option for biomass boilers (wood pellets) for decentral heating.

  • Add option for BioSNG (methane from biomass) with and without carbon capture.

  • Add option for BtL (biomass to liquid fuel/oil) with and without carbon capture.

Other new features

  • Add regionalised hydrogen salt cavern storage potentials from Technical Potential of Salt Caverns for Hydrogen Storage in Europe. This data is compiled in a new rule build_salt_cavern_potentials.

  • Add option to resolve ammonia as separate energy carrier with Haber-Bosch synthesis, ammonia cracking, storage and industrial demand. The ammonia carrier can be nodally resolved or copperplated across Europe (see ammonia).

  • Add methanol as energy carrier, methanolisation as process, and option for methanol demand in shipping sector.

  • Shipping demand now defaults to methanol rather than liquefied hydrogen until 2050.

  • Demand for liquid hydrogen in international shipping is now geographically distributed by port trade volumes in a new rule build_shipping_demand using data from the World Bank Data Catalogue. Domestic shipping remains distributed by population.

  • Add option to aggregate network temporally using representative snapshots or segments (with tsam).

  • Add option for minimum part load for Fischer-Tropsch plants (default: 90%) and methanolisation plants (default: 50%).

  • Add option to use waste heat of electrolysis in district heating networks (use_electrolysis_waste_heat).

  • Add option for coal CHPs with carbon capture (see coal_cc).

  • In overnight optimisation, it is now possible to specify a year for the technology cost projections separate from the planning horizon.

  • New config options for changing energy demands in aviation (aviation_demand_factor) and HVC industry (HVC_demand_factor), as well as explicit ICE shares for land transport (land_transport_ice_share) and agriculture machinery (agriculture_machinery_oil_share).

  • It is now possible to merge residential and services heat buses to reduce the problem size (see cluster_heat_nodes).

  • Added option to tweak (almost) any configuration parameter through the {sector_opts} wildcard. The regional_co2_sequestration_potential is triggered by the prefix CF+ after which it is possible to pipe to any setting that does not contain underscores (_). Example: CF+sector+v2g+false disables vehicle-to-grid flexibility.

  • Option retrieve_sector_databundle to automatically retrieve and extract data bundle.

  • Removed the need to clone technology-data repository in a parallel directory. The new approach automatically retrieves the technology data from remote in the rule retrieve_cost_data.

  • Improved network plots including better legends, hydrogen retrofitting network display, and change to EqualEarth projection. A new color scheme for technologies was also introduced.

  • Add two new rules build_transport_demand and build_population_weighted_energy_totals using code previously contained in prepare_sector_network.

  • Rules that convert weather data with atlite now largely run separately for categories residential, rural and total.

  • Units are assigned to the buses. These only provide a better understanding. The specifications of the units are not taken into account in the optimisation, which means that no automatic conversion of units takes place.

  • Configuration file and wildcards are now stored under n.meta in every PyPSA network.

  • Updated data bundle that includes the hydrogan salt cavern storage potentials.

  • Updated and extended documentation in <https://pypsa-eur-sec.readthedocs.io/en/latest/>

  • Added new rule copy_conda_env that exports a list of packages with which the workflow was executed.

  • Add basic continuous integration using Github Actions.

  • Add basic rsync setup.

Bugfixes

  • The CO2 sequestration limit implemented as GlobalConstraint (introduced in the previous version) caused a failure to read in the shadow prices of other global constraints.

  • Correct capital cost of Fischer-Tropsch according to new units in technology-data repository.

  • Fix unit conversion error for thermal energy storage.

  • For myopic pathway optimisation, set optimised capacities of power grid expansion of previous iteration as minimum capacity for next iteration.

  • Further rather minor bugfixes for myopic optimisation code (see #256).

Many thanks to all who contributed to this release!

PyPSA-Eur-Sec 0.6.0 (4 October 2021)#

This release includes improvements regarding the basic chemical production, the addition of plastics recycling, the addition of the agriculture, forestry and fishing sector, more regionally resolved biomass potentials, CO2 pipeline transport and storage, and more options in setting exogenous transition paths, besides many performance improvements.

This release is known to work with PyPSA-Eur Version 0.4.0, Technology Data Version 0.3.0 and PyPSA Version 0.18.0.

Please note that the data bundle has also been updated.

General

  • With this release, we change the license from copyleft GPLv3 to the more liberal MIT license with the consent of all contributors.

New features and functionality

  • Distinguish costs for home battery storage and inverter from utility-scale battery costs.

  • Separate basic chemicals into HVC (high-value chemicals), chlorine, methanol and ammonia [#166].

  • Add option to specify reuse, primary production, and mechanical and chemical recycling fraction of platics [#166].

  • Include energy demands and CO2 emissions for the agriculture, forestry and fishing sector. It is included by default through the option A in the sector_opts wildcard. Part of the emissions (1.A.4.c) was previously assigned to “industry non-elec” in the co2_totals.csv. Hence, excluding the agriculture sector will now lead to a tighter CO2 limit. Energy demands are taken from the JRC IDEES database (missing countries filled with eurostat data) and are split into electricity (lighting, ventilation, specific electricity uses, pumping devices (electric)), heat (specific heat uses, low enthalpy heat) machinery oil (motor drives, farming machine drives, pumping devices (diesel)). Heat demand is assigned at “services rural heat” buses. Electricity demands are added to low-voltage buses. Time series for demands are constant and distributed inside countries by population [#147].

  • Include today’s district heating shares in myopic optimisation and add option to specify exogenous path for district heating share increase under sector: district_heating: [#149].

  • Added option for hydrogen liquefaction costs for hydrogen demand in shipping. This introduces a new H2 liquid bus at each location. It is activated via sector: shipping_hydrogen_liquefaction: true.

  • The share of shipping transformed into hydrogen fuel cell can be now defined for different years in the config.yaml file. The carbon emission from the remaining share is treated as a negative load on the atmospheric carbon dioxide bus, just like aviation and land transport emissions.

  • The transformation of the Steel and Aluminium production can be now defined for different years in the config.yaml file.

  • Include the option to alter the maximum energy capacity of a store via the carrier+factor in the {sector_opts} wildcard. This can be useful for sensitivity analyses. Example: co2 stored+e2 multiplies the e_nom_max by factor 2. In this example, e_nom_max represents the CO2 sequestration potential in Europe.

  • Use JRC ENSPRESO database to spatially disaggregate biomass potentials to PyPSA-Eur regions based on overlaps with NUTS2 regions from ENSPRESO (proportional to area) (#151).

  • Add option to regionally disaggregate biomass potential to individual nodes (previously given per country, then distributed by population density within) and allow the transport of solid biomass. The transport costs are determined based on the JRC-EU-Times Bioenergy report in the new optional rule build_biomass_transport_costs. Biomass transport can be activated with the setting sector: biomass_transport: true.

  • Add option to regionally resolve CO2 storage and add CO2 pipeline transport because geological storage potential, CO2 utilisation sites and CO2 capture sites may be separated. The CO2 network is built from zero based on the topology of the electricity grid (greenfield). Pipelines are assumed to be bidirectional and lossless. Furthermore, neither retrofitting of natural gas pipelines (required pressures are too high, 80-160 bar vs <80 bar) nor other modes of CO2 transport (by ship, road or rail) are considered. The regional representation of CO2 is activated with the config setting sector: co2_network: true but is deactivated by default. The global limit for CO2 sequestration now applies to the sum of all CO2 stores via an extra_functionality constraint.

  • The myopic option can now be used together with different clustering for the generators and the network. The existing renewable capacities are split evenly among the regions in every country [#144].

  • Add optional function to use geopy to locate entries of the Hotmaps database of industrial sites with missing location based on city and country, which reduces missing entries by half. It can be activated by setting industry: hotmaps_locate_missing: true, takes a few minutes longer, and should only be used if spatial resolution is coarser than city level.

Performance and Structure

  • Extended use of multiprocessing for much better performance (from up to 20 minutes to less than one minute).

  • Handle most input files (or base directories) via snakemake.input.

  • Use of mock_snakemake from PyPSA-Eur.

  • Update solve_network rule to match implementation in PyPSA-Eur by using n.ilopf() and remove outdated code using pyomo. Allows the new setting to skip iterated impedance updates with solving: options: skip_iterations: true.

  • The component attributes that are to be overridden are now stored in the folder data/override_component_attrs analogous to pypsa/component_attrs. This reduces verbosity and also allows circumventing the n.madd() hack for individual components with non-default attributes. This data is also tracked in the Snakefile. A function helper.override_component_attrs was added that loads this data and can pass the overridden component attributes into pypsa.Network().

  • Add various parameters to config.default.yaml which were previously hardcoded inside the scripts (e.g. energy reference years, BEV settings, solar thermal collector models, geomap colours).

  • Removed stale industry demand rules build_industrial_energy_demand_per_country and build_industrial_demand. These are superseded with more regionally resolved rules.

  • Use simpler and shorter gdf.sjoin() function to allocate industrial sites from the Hotmaps database to onshore regions. This change also fixes a bug: The previous version allocated sites to the closest bus, but at country borders (where Voronoi cells are distorted by the borders), this had resulted in e.g. a Spanish site close to the French border being wrongly allocated to the French bus if the bus center was closer.

  • Retrofitting rule is now only triggered if endogeneously optimised.

  • Show progress in build rules with tqdm progress bars.

  • Reduced verbosity of Snakefile through directory prefixes.

  • Improve legibility of config.default.yaml and remove unused options.

  • Use the country-specific time zone mappings from pytz rather than a manual mapping.

  • A function add_carrier_buses() was added to the prepare_network rule to reduce code duplication.

  • In the prepare_network rule the cost and potential adjustment was moved into an own function maybe_adjust_costs_and_potentials().

  • Use matplotlibrc to set the default plotting style and backend.

  • Added benchmark files for each rule.

  • Consistent use of __main__ block and further unspecific code cleaning.

  • Updated data bundle and moved data bundle to zenodo.org (10.5281/zenodo.5546517).

Bugfixes and Compatibility

  • Compatibility with atlite>=0.2. Older versions of atlite will no longer work.

  • Corrected calculation of “gas for industry” carbon capture efficiency.

  • Implemented changes to n.snapshot_weightings in PyPSA v0.18.0.

  • Compatibility with xarray version 0.19.

  • New dependencies: tqdm, atlite>=0.2.4, pytz and geopy (optional). These are included in the environment specifications of PyPSA-Eur v0.4.0.

Many thanks to all who contributed to this release!

PyPSA-Eur-Sec 0.5.0 (21st May 2021)#

This release includes improvements to the cost database for building retrofits, carbon budget management and wildcard settings, as well as an important bugfix for the emissions from land transport.

This release is known to work with PyPSA-Eur Version 0.3.0 and Technology Data Version 0.2.0.

Please note that the data bundle has also been updated.

New features and bugfixes:

  • The cost database for retrofitting of the thermal envelope of buildings has been updated. Now, for calculating the space heat savings of a building, losses by thermal bridges and ventilation are included as well as heat gains (internal and by solar radiation). See the section retro for more details on the retrofitting module.

  • For the myopic investment option, a carbon budget and a type of decay (exponential or beta) can be selected in the config.yaml file to distribute the budget across the planning_horizons. For example, cb40ex0 in the {sector_opts} wildcard will distribute a carbon budget of 40 GtCO2 following an exponential decay with initial growth rate 0.

  • Added an option to alter the capital cost or maximum capacity of carriers by a factor via carrier+factor in the {sector_opts} wildcard. This can be useful for exploring uncertain cost parameters. Example: solar+c0.5 reduces the capital_cost of solar to 50% of original values. Similarly solar+p3 multiplies the p_nom_max by 3.

  • Rename the bus for European liquid hydrocarbons from Fischer-Tropsch to EU oil, since it can be supplied not just with the Fischer-Tropsch process, but also with fossil oil.

  • Bugfix: The new separation of land transport by carrier in Version 0.4.0 failed to account for the carbon dioxide emissions from internal combustion engines in land transport. This is now treated as a negative load on the atmospheric carbon dioxide bus, just like aviation emissions.

  • Bugfix: Fix reading in of pypsa-eur/resources/powerplants.csv to PyPSA-Eur Version 0.3.0 (use column attribute name DateIn instead of old YearDecommissioned).

  • Bugfix: Make sure that Store components (battery and H2) are also removed from PyPSA-Eur, so they can be added later by PyPSA-Eur-Sec.

Thanks to Lisa Zeyen (KIT) for the retrofitting improvements and Marta Victoria (Aarhus University) for the carbon budget and wildcard management.

PyPSA-Eur-Sec 0.4.0 (11th December 2020)#

This release includes a more accurate nodal disaggregation of industry demand within each country, fixes to CHP and CCS representations, as well as changes to some configuration settings.

It has been released to coincide with PyPSA-Eur Version 0.3.0 and Technology Data Version 0.2.0, and is known to work with these releases.

New features:

  • The Hotmaps Industrial Database is used to disaggregate the industrial demand spatially to the nodes inside each country (previously it was distributed by population density).

  • Electricity demand from industry is now separated from the regular electricity demand and distributed according to the industry demand. Only the remaining regular electricity demand for households and services is distributed according to GDP and population.

  • A cost database for the retrofitting of the thermal envelope of residential and services buildings has been integrated, as well as endogenous optimisation of the level of retrofitting. This is described in the paper Mitigating heat demand peaks in buildings in a highly renewable European energy system. Retrofitting can be activated both exogenously and endogenously from the config.yaml.

  • The biomass and gas combined heat and power (CHP) parameters c_v and c_b were read in assuming they were extraction plants rather than back pressure plants. The data is now corrected in Technology Data Version 0.2.0 to the correct DEA back pressure assumptions and they are now implemented as single links with a fixed ratio of electricity to heat output (even as extraction plants, they were always sitting on the backpressure line in simulations, so there was no point in modelling the full heat-electricity feasibility polygon). The old assumptions underestimated the heat output.

  • The Danish Energy Agency released new assumptions for carbon capture in October 2020, which have now been incorporated in PyPSA-Eur-Sec, including direct air capture (DAC) and post-combustion capture on CHPs, cement kilns and other industrial facilities. The electricity and heat demand for DAC is modelled for each node (with heat coming from district heating), but currently the electricity and heat demand for industrial capture is not modelled very cleanly (for process heat, 10% of the energy is assumed to go to carbon capture) - a new issue will be opened on this.

  • Land transport is separated by energy carrier (fossil, hydrogen fuel cell electric vehicle, and electric vehicle), but still needs to be separated into heavy and light vehicles (the data is there, just not the code yet).

  • For assumptions that change with the investment year, there is a new time-dependent format in the config.yaml using a dictionary with keys for each year. Implemented examples include the CO2 budget, exogenous retrofitting share and land transport energy carrier; more parameters will be dynamised like this in future.

  • Some assumptions have been moved out of the code and into the config.yaml, including the carbon sequestration potential and cost, the heat pump sink temperature, reductions in demand for high value chemicals, and some BEV DSM parameters and transport efficiencies.

  • Documentation on Supply and demand options has been added.

Many thanks to Fraunhofer ISI for opening the hotmaps database and to Lisa Zeyen (KIT) for implementing the building retrofitting.

PyPSA-Eur-Sec 0.3.0 (27th September 2020)#

This releases focuses on improvements to industry demand and the generation of intermediate files for demand for basic materials. There are still inconsistencies with CCS and waste management that need to be improved.

It is known to work with PyPSA-Eur v0.1.0 (commit bb3477cd69), PyPSA v0.17.1 and technology-data v0.1.0. Please note that the data bundle has also been updated.

New features:

  • In previous version of PyPSA-Eur-Sec the energy demand for industry was calculated directly for each location. Now, instead, the production of each material (steel, cement, aluminium) at each location is calculated as an intermediate data file, before the energy demand is calculated from it. This allows us in future to have competing industrial processes for supplying the same material demand.

  • The script build_industrial_production_per_country_tomorrow.py determines the future industrial production of materials based on today’s levels as well as assumed recycling and demand change measures.

  • The energy demand for each industry sector and each location in 2015 is also calculated, so that it can be later incorporated in the pathway optimization.

  • Ammonia production data is taken from the USGS and deducted from JRC-IDEES’s “basic chemicals” so that it ammonia can be handled separately from the others (olefins, aromatics and chlorine).

  • Solid biomass is no longer allowed to be used for process heat in cement and basic chemicals, since the wastes and residues cannot be guaranteed to reach the high temperatures required. Instead, solid biomass is used in the paper and pulp as well as food, beverages and tobacco industries, where required temperatures are lower (see DOI:10.1002/er.3436 and DOI:10.1007/s12053-017-9571-y).

  • National installable potentials for salt caverns are now applied.

  • When electricity distribution grids are activated, new industry electricity demand, resistive heaters and micro-CHPs are now connected to the lower voltage levels.

  • Gas distribution grid costs are included for gas boilers and micro-CHPs.

  • Installable potentials for rooftop PV are included with an assumption of 1 kWp per person.

  • Some intermediate files produced by scripts have been moved from the folder data to the folder resources. Now data only includes input data, while resources only includes intermediate files necessary for building the network models. Please note that the data bundle has also been updated.

  • Biomass potentials for different years and scenarios from the JRC are generated in an intermediate file, so that a selection can be made more explicitly by specifying the biomass types from the config.yaml.

PyPSA-Eur-Sec 0.2.0 (21st August 2020)#

This release introduces pathway optimization over many years (e.g. 2020, 2030, 2040, 2050) with myopic foresight, as well as outsourcing the technology assumptions to the technology-data repository.

It is known to work with PyPSA-Eur v0.1.0 (commit bb3477cd69), PyPSA v0.17.1 and technology-data v0.1.0.

New features:

  • Option for pathway optimization with myopic foresight, based on the paper Early decarbonisation of the European Energy system pays off (2020). Investments are optimized sequentially for multiple years (e.g. 2020, 2030, 2040, 2050) taking account of existing assets built in previous years and their lifetimes. The script uses data on the existing assets for electricity and building heating technologies, but there are no assumptions yet for existing transport and industry (if you include these, the model will greenfield them). There are also some outstanding issues on e.g. the distribution of existing wind, solar and heating technologies within each country. To use myopic foresight, set foresight : 'myopic' in the config.yaml instead of the default foresight : 'overnight'. An example configuration can be found in config.myopic.yaml. More details on the implementation can be found in myopic.

  • Technology assumptions (costs, efficiencies, etc.) are no longer stored in the repository. Instead, you have to install the technology-data database in a parallel directory. These assumptions are largely based on the Danish Energy Agency Technology Data. More details on the installation can be found in Installation.

  • Logs and benchmarks are now stored with the other model outputs in results/run-name/.

  • All buses now have a location attribute, e.g. bus DE0 3 urban central heat has a location of DE0 3.

  • All assets have a lifetime attribute (integer in years). For the myopic foresight, a build_year attribute is also stored.

  • Costs for solar and onshore and offshore wind are recalculated by PyPSA-Eur-Sec based on the investment year, including the AC or DC connection costs for offshore wind.

Many thanks to Marta Victoria for implementing the myopic foresight, and Marta Victoria, Kun Zhu and Lisa Zeyen for developing the technology assumptions database.

PyPSA-Eur-Sec 0.1.0 (8th July 2020)#

This is the first proper release of PyPSA-Eur-Sec, a model of the European energy system at the transmission network level that covers the full ENTSO-E area.

It is known to work with PyPSA-Eur v0.1.0 (commit bb3477cd69) and PyPSA v0.17.0.

We are making this release since in version 0.2.0 we will introduce changes to allow myopic investment planning that will require minor changes for users of the overnight investment planning.

PyPSA-Eur-Sec builds on the electricity generation and transmission model PyPSA-Eur to add demand and supply for the following sectors: transport, space and water heating, biomass, industry and industrial feedstocks. This completes the energy system and includes all greenhouse gas emitters except waste management, agriculture, forestry and land use.

PyPSA-Eur-Sec was initially based on the model PyPSA-Eur-Sec-30 (Version 0.0.1 below) described in the paper Synergies of sector coupling and transmission reinforcement in a cost-optimised, highly renewable European energy system (2018) but it differs by being based on the higher resolution electricity transmission model PyPSA-Eur rather than a one-node-per-country model, and by including biomass, industry, industrial feedstocks, aviation, shipping, better carbon management, carbon capture and usage/sequestration, and gas networks.

PyPSA-Eur-Sec includes PyPSA-Eur as a snakemake subworkflow. PyPSA-Eur-Sec uses PyPSA-Eur to build the clustered transmission model along with wind, solar PV and hydroelectricity potentials and time series. Then PyPSA-Eur-Sec adds other conventional generators, storage units and the additional sectors.

PyPSA-Eur-Sec 0.0.2 (4th September 2020)#

This version, also called PyPSA-Eur-Sec-30-Path, built on PyPSA-Eur-Sec 0.0.1 (also called PyPSA-Eur-Sec-30) to include myopic pathway optimisation for the paper Early decarbonisation of the European energy system pays off (2020). The myopic pathway optimisation was then merged into the main PyPSA-Eur-Sec codebase in Version 0.2.0 above.

This model has its own github repository and is archived on Zenodo.

PyPSA-Eur-Sec 0.0.1 (12th January 2018)#

This is the first published version of PyPSA-Eur-Sec, also called PyPSA-Eur-Sec-30. It was first used in the research paper Synergies of sector coupling and transmission reinforcement in a cost-optimised, highly renewable European energy system (2018). The model covers 30 European countries with one node per country. It includes demand and supply for electricity, space and water heating in buildings, and land transport.

It is archived on Zenodo.

Release Process#

  • Checkout a new release branch git checkout -b release-v0.x.x.

  • Finalise release notes at doc/release_notes.rst.

  • Update envs/environment.fixed.yaml via conda env export -n pypsa-eur -f envs/environment.fixed.yaml --no-builds from an up-to-date pypsa-eur environment.

  • Update version number in doc/conf.py, CITATION.cff and *config.*.yaml.

  • Make a git commit.

  • Open, review and merge pull request for branch release-v0.x.x. Make sure to close issues and PRs or the release milestone with it (e.g. closes #X).

  • Tag a release on Github via git tag v0.x.x, git push, git push --tags. Include release notes in the tag message.

  • Make a GitHub release, which automatically triggers archiving to the zenodo code repository with MIT license.

  • Create pre-built networks for config.default.yaml by running snakemake -call prepare_sector_networks.

  • Upload pre-built networks to zenodo data repository with CC BY 4.0 license.

  • Send announcement on the PyPSA mailing list.