pypsa-eur/doc/index.rst

PyPSA-Eur-Sec: A Sector-Coupled Open Optimisation Model of the European Energy System
=====================================================================================

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PyPSA-Eur-Sec is an open model dataset of the European energy system at the
transmission network level that covers the full ENTSO-E area.

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.

.. note::
    More about the current model capabilities and preliminary results
    can be found in `a recent presentation at EMP-E <https://nworbmot.org/energy/brown-empe.pdf>`_
    and the the following `preprint with a description of the industry sector <https://arxiv.org/abs/2109.09563>`_.

This diagram gives an overview of the sectors and the links between
them:

.. image:: ../graphics/multisector_figure.png

PyPSA-Eur-Sec was initially based on the model PyPSA-Eur-Sec-30 described
in the paper `Synergies of sector coupling and transmission
reinforcement in a cost-optimised, highly renewable European energy
system <https://arxiv.org/abs/1801.05290>`_ (2018) but it differs by
being based on the higher resolution electricity transmission model
`PyPSA-Eur <https://github.com/PyPSA/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 <https://snakemake.readthedocs.io/en/stable/index.html>`_
`subworkflow <https://snakemake.readthedocs.io/en/stable/snakefiles/modularization.html#snakefiles-sub-workflows>`_. 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.

Currently the scripts to solve and process the resulting PyPSA models
are also included in PyPSA-Eur-Sec, although they could in future be
better integrated with the corresponding scripts in PyPSA-Eur. A
stumbling block to sharing solve_network.py between PyPSA-Eur and
PyPSA-Eur-Sec is the different extra_functionality required to build
storage and CHP constraints.


PyPSA-Eur-Sec is designed to be imported into the open toolbox `PyPSA
<https://www.pypsa.org>`_ for which `documentation <https://pypsa.org/doc>`_ is
available as well.

This project is currently maintained by the `Department of Digital
Transformation in Energy Systems <https://tub-ensys.github.io>`_ at the
`Technical University of Berlin <https://www.tu.berlin>`_. Previous versions
were developed 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>`_
which was funded by the `Helmholtz Association <https://www.helmholtz.de/en/>`_,
and 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/>`_.


Documentation
=============

**Getting Started**

* :doc:`installation`

.. toctree::
   :hidden:
   :maxdepth: 1
   :caption: Getting Started

   installation

**Implementation details**

* :doc:`spatial_resolution`
* :doc:`supply_demand`

.. toctree::
   :hidden:
   :maxdepth: 1
   :caption: Implementation details

   spatial_resolution
   supply_demand


**Foresight options**

* :doc:`overnight`
* :doc:`myopic`

.. toctree::
   :hidden:
   :maxdepth: 1
   :caption: Foresight options

   overnight
   myopic

**References**

* :doc:`release_notes`

.. toctree::
   :hidden:
   :maxdepth: 1
   :caption: References

   release_notes


Warnings
========

**WARNING**: This model is under construction and contains serious
problems that distort the results. See the github repository
`issues <https://github.com/PyPSA/pypsa-eur-sec/issues>`_ for some of
the problems (please feel free to help or make suggestions). There is
neither documentation nor a paper yet, but we hope to have a preprint
out by summer 2020. We cannot support this model if you choose to use
it.


Licence
=======

The code in PyPSA-Eur-Sec is released as free software under the
`MIT license <https://opensource.org/licenses/MIT>`_, see
`LICENSE <https://github.com/PyPSA/pypsa-eur-sec/blob/master/LICENSE.txt>`_.
However, different licenses and terms of use may apply to the various input data.