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README.md
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README.md
@ -18,6 +18,9 @@ heating, biomass, industry and industrial feedstocks. This completes
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the energy system and includes all greenhouse gas emitters except
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the energy system and includes all greenhouse gas emitters except
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waste management, agriculture, forestry and land use.
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waste management, agriculture, forestry and land use.
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Please see the [documentation](https://pypsa-eur-sec.readthedocs.io/)
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for installation instructions and other useful information.
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This diagram gives an overview of the sectors and the links between
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This diagram gives an overview of the sectors and the links between
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them:
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them:
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@ -43,111 +46,6 @@ wind, solar PV and hydroelectricity potentials and time series. Then
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PyPSA-Eur-Sec adds other conventional generators, storage units and
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PyPSA-Eur-Sec adds other conventional generators, storage units and
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the additional sectors.
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the additional sectors.
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Currently the scripts to solve and process the resulting PyPSA models
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are also included in PyPSA-Eur-Sec, although they could in future be
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better integrated with the corresponding scripts in PyPSA-Eur. A
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stumbling block to sharing solve_network.py between PyPSA-Eur and
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PyPSA-Eur-Sec is the different extra_functionality required to build
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storage and CHP constraints.
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# Spatial resolution of sectors
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Not all of the sectors are at the full nodal resolution, and some are
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distributed to nodes using heuristics that need to be corrected. Some
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networks are copper-plated to reduce computational times.
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For example:
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Electricity network: nodal.
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Electricity demand: nodal, distributed in each country based on
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population and GDP.
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Building heating demand: nodal, distributed in each country based on
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population.
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Industry demand: nodal, distributed in each country based on
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population (will be corrected to real locations of industry, see
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github issue).
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Hydrogen network: nodal.
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Methane network: copper-plated for Europe, since future demand is so
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low and no bottlenecks are expected.
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Solid biomass: copper-plated until transport costs can be
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incorporated.
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CO2: copper-plated (but a transport and storage cost is added for
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sequestered CO2).
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Liquid hydrocarbons: copper-plated since transport costs are low.
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# Installation
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First install [PyPSA-Eur](https://github.com/PyPSA/pypsa-eur) and all
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its dependencies. Clone the repository:
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```shell
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projects % git clone git@github.com:PyPSA/pypsa-eur.git
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```
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then download and unpack all the data files.
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Create a parallel directory for PyPSA-Eur-Sec with:
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```shell
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projects % git clone git@github.com:PyPSA/pypsa-eur-sec.git
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```
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## Package requirements
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The requirements are the same as
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[PyPSA-Eur](https://github.com/PyPSA/pypsa-eur). For
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`solve_network.py` in addition you need `gurobipy`. If you have
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xarray version >= 0.15.1, you will need the latest master branch of
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atlite version 0.0.2.
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## Data requirements
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The data requirements include the JRC-IDEES-2015 database, JRC biomass
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potentials, EEA emission statistics, Eurostat Energy Balances, urban
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district heating potentials, emobility statistics, timezone mappings
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and heating profiles.
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The data bundle is about 640 MB.
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To download and extract it on the command line:
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```shell
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projects/pypsa-eur-sec/data % wget "https://nworbmot.org/pypsa-eur-sec-data-bundle-190719.tar.gz"
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projects/pypsa-eur-sec/data % tar xvzf pypsa-eur-sec-data-bundle-190719.tar.gz
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```
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# Getting started
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First make your own copy of the `config.yaml`:
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```shell
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projects/pypsa-eur-sec % cp config.default.yaml config.yaml
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```
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In `config.yaml` you can control the settings for the scenarios you
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want to run, such as the number of nodes, the CO2 limit, the
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installable potentials for solar and wind, which technologies are
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activated, etc.
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To run the full optimization with your settings:
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```shell
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projects/pypsa-eur-sec % snakemake
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```
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Warning: you may need a cluster for this (with e.g. 10-100 GB of RAM
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and several processors).
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To only prepare the networks, you can run the scripts up to the point before optimization:
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```shell
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projects/pypsa-eur-sec % snakemake prepare_sector_networks
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```
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# Licence
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# Licence
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@ -4,6 +4,10 @@ PyPSA-Eur-Sec: A Sector-Coupled Open Optimisation Model of the European Energy S
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.. image:: https://img.shields.io/github/v/release/pypsa/pypsa-eur-sec?include_prereleases
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.. image:: https://img.shields.io/github/v/release/pypsa/pypsa-eur-sec?include_prereleases
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:alt: GitHub release (latest by date including pre-releases)
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:alt: GitHub release (latest by date including pre-releases)
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.. image:: https://readthedocs.org/projects/pypsa-eur/badge/?version=latest
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:target: https://pypsa-eur.readthedocs.io/en/latest/?badge=latest
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:alt: Documentation Status
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.. image:: https://img.shields.io/github/license/pypsa/pypsa-eur-sec
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.. image:: https://img.shields.io/github/license/pypsa/pypsa-eur-sec
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:alt: GitHub
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:alt: GitHub
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@ -61,6 +65,43 @@ PyPSA-Eur-Sec is designed to be imported into the open toolbox `PyPSA <https://w
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This project is maintained by the `Energy System Modelling group <https://www.iai.kit.edu/english/2338.php>`_ at the `Institute for Automation and Applied Informatics <https://www.iai.kit.edu/english/index.php>`_ at the `Karlsruhe Institute of Technology <http://www.kit.edu/english/index.php>`_. The group is funded by the `Helmholtz Association <https://www.helmholtz.de/en/>`_ until 2024. Previous versions were developed by the `Renewable Energy Group <https://fias.uni-frankfurt.de/physics/schramm/renewable-energy-system-and-network-analysis/>`_ at `FIAS <https://fias.uni-frankfurt.de/>`_ to carry out simulations for the `CoNDyNet project <http://condynet.de/>`_, financed by the `German Federal Ministry for Education and Research (BMBF) <https://www.bmbf.de/en/index.html>`_ as part of the `Stromnetze Research Initiative <http://forschung-stromnetze.info/projekte/grundlagen-und-konzepte-fuer-effiziente-dezentrale-stromnetze/>`_.
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This project is maintained by the `Energy System Modelling group <https://www.iai.kit.edu/english/2338.php>`_ at the `Institute for Automation and Applied Informatics <https://www.iai.kit.edu/english/index.php>`_ at the `Karlsruhe Institute of Technology <http://www.kit.edu/english/index.php>`_. The group is funded by the `Helmholtz Association <https://www.helmholtz.de/en/>`_ until 2024. Previous versions were developed by the `Renewable Energy Group <https://fias.uni-frankfurt.de/physics/schramm/renewable-energy-system-and-network-analysis/>`_ at `FIAS <https://fias.uni-frankfurt.de/>`_ to carry out simulations for the `CoNDyNet project <http://condynet.de/>`_, financed by the `German Federal Ministry for Education and Research (BMBF) <https://www.bmbf.de/en/index.html>`_ as part of the `Stromnetze Research Initiative <http://forschung-stromnetze.info/projekte/grundlagen-und-konzepte-fuer-effiziente-dezentrale-stromnetze/>`_.
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Spatial resolution of sectors
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=============================
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Not all of the sectors are at the full nodal resolution, and some are
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distributed to nodes using heuristics that need to be corrected. Some
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networks are copper-plated to reduce computational times.
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For example:
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Electricity network: nodal.
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Electricity demand: nodal, distributed in each country based on
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population and GDP.
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Building heating demand: nodal, distributed in each country based on
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population.
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Industry demand: nodal, distributed in each country based on
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population (will be corrected to real locations of industry, see
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github issue).
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Hydrogen network: nodal.
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Methane network: copper-plated for Europe, since future demand is so
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low and no bottlenecks are expected.
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Solid biomass: copper-plated until transport costs can be
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incorporated.
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CO2: copper-plated (but a transport and storage cost is added for
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sequestered CO2).
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Liquid hydrocarbons: copper-plated since transport costs are low.
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Documentation
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Documentation
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=============
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=============
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