***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.
* Renamed script file from PyPSA-EUR ``build_load_data`` to ``build_electricity_demand`` and ``retrieve_load_data`` to ``retrieve_electricity_demand``.
* The :mod:`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 <https://pypsa.readthedocs.io/en/latest/examples/optimization-with-linopy-migrate-extra-functionalities.html>`_ 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 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
* Greedy modularity clustering was introduced. Distance metric is based on electrical distance taking into account the impedance of all transmission lines of the network.
On March 16, 2022, the transmission networks of Ukraine and Moldova have
successfully been `synchronised with the continental European grid <https://www.entsoe.eu/news/2022/03/16/continental-europe-successful-synchronisation-with-ukraine-and-moldova-power-systems/>`_. We have taken
this as an opportunity to add the power systems of Ukraine and Moldova to
PyPSA-Eur. This includes:
..image:: img/synchronisation.png
:width:500
* the transmission network topology from the `ENTSO-E interactive map <https://www.entsoe.eu/data/map/>`_.
* existing power plants (incl. nuclear, coal, gas and hydro) from the `powerplantmatching <https://github.com/fresna/powerplantmatching>`_ tool
* country-level load time series from ENTSO-E through the `OPSD platform <https://data.open-power-system-data.org/time_series/2020-10-06>`_, 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 <https://www.eia.gov/international/data/world>`_
* a simplified calculation of wind and solar potentials based on the `Copernicus Land Cover dataset <https://land.copernicus.eu/global/products/lc>`_.
* 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
* 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
* Add renewable power plants from `OPSD <https://data.open-power-system-data.org/renewable_power_plants/2020-08-25>`_ to the network for specified technologies.
This will overwrite the capacities calculated from the heuristic approach in :func:`estimate_renewable_capacities()`
* Electricity consumption data is now retrieved directly from the `OPSD website <https://data.open-power-system-data.org/time_series/2019-06-05>`_ using the rule :mod:`build_electricity_demand`.
* 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.
* The optimization is now performed using the ``pyomo=False`` setting in the :func:`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 :func:`network_lopf` function via the ``extra_functionality`` argument. The rule ``trace_solve_network`` was integrated into the rule :mod:`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 <https://github.com/PyPSA/pypsa-eur/pull/116>`_].
* An updated extract of the `ENTSO-E Transmission System Map <https://www.entsoe.eu/data/map/>`_ (including Malta) was added to the repository using the `GridKit <https://github.com/PyPSA/GridKit>`_ tool. This tool has been updated to retrieve up-to-date map extracts using a single `script <https://github.com/PyPSA/GridKit/blob/master/entsoe/runall_in_docker.sh>`_. The update extract features 5322 buses, 6574 lines, 46 links. [`#118 <https://github.com/PyPSA/pypsa-eur/pull/118>`_].
* Added a 30 minute `video introduction <https://pypsa-eur.readthedocs.io/en/latest/introduction.html>`_ and a 20 minute `video tutorial <https://pypsa-eur.readthedocs.io/en/latest/tutorial.html>`_
* 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 <https://github.com/PyPSA/pypsa-eur/pull/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 <https://github.com/PyPSA/pypsa-eur/pull/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 <https://github.com/PyPSA/pypsa-eur/pull/150>`_].
* Added a function ``_helpers.load_network()`` which loads a network with overridden components specified in ``snakemake.config['override_components']`` [`#128 <https://github.com/PyPSA/pypsa-eur/pull/128>`_].
* Bugfix in :mod:`cluster_network` which now skips recalculation of link parameters if there are no links [`#149 <https://github.com/PyPSA/pypsa-eur/pull/149>`_].
* Documentation on installation, workflows and configuration settings is now available online at `pypsa-eur.readthedocs.io <pypsa-eur.readthedocs.io>`_ [`#65 <https://github.com/PyPSA/pypsa-eur/pull/65>`_].
* The power plant database was updated with extensive filtering options via ``pandas.query`` functionality [`#84 <https://github.com/PyPSA/pypsa-eur/pull/84>`_ and `#94 <https://github.com/PyPSA/pypsa-eur/pull/94>`_].
* Continuous integration testing with `Travis CI <https://travis-ci.org>`_ is now included for Linux, Mac and Windows [`#82 <https://github.com/PyPSA/pypsa-eur/pull/82>`_].
* Emission prices can be added to marginal costs of generators through the keywords ``Ep`` in the ``{opts}`` wildcard [`#100 <https://github.com/PyPSA/pypsa-eur/pull/100>`_].
* 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 <https://github.com/PyPSA/pypsa-eur/pull/87>`_].
* A new rule :mod:`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 <https://github.com/PyPSA/pypsa-eur/pull/97>`_].
* Hydrogen pipelines (including cost assumptions) can now be added alongside clustered network connections in the rule :mod:`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 <https://github.com/PyPSA/pypsa-eur/pull/108>`_].
* 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 <https://github.com/PyPSA/pypsa-eur/pull/107>`_].
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 <https://github.com/PyPSA/pypsa-eur>`_ Version 0.3.0 and `Technology Data <https://github.com/PyPSA/technology-data>`_ Version 0.2.0.
Please note that the data bundle has also been updated.
* 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 :ref:`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``).
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 <https://github.com/PyPSA/pypsa-eur>`_ Version 0.3.0 and `Technology Data <https://github.com/PyPSA/technology-data>`_ Version 0.2.0, and is known to work with these releases.
New features:
* The `Hotmaps Industrial Database <https://gitlab.com/hotmaps/industrial_sites/industrial_sites_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 <https://arxiv.org/abs/2012.01831>`_. 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 <https://github.com/PyPSA/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 <https://ens.dk/en/our-services/projections-and-models/technology-data/technology-data-industrial-process-heat-and>`_ 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 :doc:`supply_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.
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 <https://doi.org/10.1002/er.3436>`_ and `DOI:10.1007/s12053-017-9571-y <https://doi.org/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``.
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 <https://github.com/PyPSA/technology-data>`_ repository.
* Option for pathway optimization with myopic foresight, based on the paper `Early decarbonisation of the European Energy system pays off (2020) <https://arxiv.org/abs/2004.11009>`_. 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 <https://github.com/PyPSA/pypsa-eur-sec/issues/19#issuecomment-678194802>`_ 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 :doc:`myopic`.
* Technology assumptions (costs, efficiencies, etc.) are no longer stored in the repository. Instead, you have to install the `technology-data <https://github.com/PyPSA/technology-data>`_ database in a parallel directory. These assumptions are largely based on the `Danish Energy Agency Technology Data <https://ens.dk/en/our-services/projections-and-models/technology-data>`_. More details on the installation can be found in :doc:`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.
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 <https://github.com/PyPSA/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.
* Make a `GitHub release <https://github.com/PyPSA/pypsa-eur-sec/releases>`_, which automatically triggers archiving to the `zenodo code repository <https://doi.org/10.5281/zenodo.3520874>`_ with `MIT license <https://opensource.org/licenses/MIT>`_.
* Upload pre-built networks to `zenodo data repository <https://doi.org/10.5281/zenodo.3601881>`_ with `CC BY 4.0 <https://creativecommons.org/licenses/by/4.0/>`_ license.
