README: Link to readthedocs and remove info in documentation

I.e. avoid duplication of text.
This commit is contained in:
Tom Brown 2020-07-08 18:52:18 +02:00
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README.md
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@ -18,6 +18,9 @@ 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.
Please see the [documentation](https://pypsa-eur-sec.readthedocs.io/)
for installation instructions and other useful information.
This diagram gives an overview of the sectors and the links between
them:
@ -43,111 +46,6 @@ 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.
# Spatial resolution of sectors
Not all of the sectors are at the full nodal resolution, and some are
distributed to nodes using heuristics that need to be corrected. Some
networks are copper-plated to reduce computational times.
For example:
Electricity network: nodal.
Electricity demand: nodal, distributed in each country based on
population and GDP.
Building heating demand: nodal, distributed in each country based on
population.
Industry demand: nodal, distributed in each country based on
population (will be corrected to real locations of industry, see
github issue).
Hydrogen network: nodal.
Methane network: copper-plated for Europe, since future demand is so
low and no bottlenecks are expected.
Solid biomass: copper-plated until transport costs can be
incorporated.
CO2: copper-plated (but a transport and storage cost is added for
sequestered CO2).
Liquid hydrocarbons: copper-plated since transport costs are low.
# Installation
First install [PyPSA-Eur](https://github.com/PyPSA/pypsa-eur) and all
its dependencies. Clone the repository:
```shell
projects % git clone git@github.com:PyPSA/pypsa-eur.git
```
then download and unpack all the data files.
Create a parallel directory for PyPSA-Eur-Sec with:
```shell
projects % git clone git@github.com:PyPSA/pypsa-eur-sec.git
```
## Package requirements
The requirements are the same as
[PyPSA-Eur](https://github.com/PyPSA/pypsa-eur). For
`solve_network.py` in addition you need `gurobipy`. If you have
xarray version >= 0.15.1, you will need the latest master branch of
atlite version 0.0.2.
## Data requirements
The data requirements include the JRC-IDEES-2015 database, JRC biomass
potentials, EEA emission statistics, Eurostat Energy Balances, urban
district heating potentials, emobility statistics, timezone mappings
and heating profiles.
The data bundle is about 640 MB.
To download and extract it on the command line:
```shell
projects/pypsa-eur-sec/data % wget "https://nworbmot.org/pypsa-eur-sec-data-bundle-190719.tar.gz"
projects/pypsa-eur-sec/data % tar xvzf pypsa-eur-sec-data-bundle-190719.tar.gz
```
# Getting started
First make your own copy of the `config.yaml`:
```shell
projects/pypsa-eur-sec % cp config.default.yaml config.yaml
```
In `config.yaml` you can control the settings for the scenarios you
want to run, such as the number of nodes, the CO2 limit, the
installable potentials for solar and wind, which technologies are
activated, etc.
To run the full optimization with your settings:
```shell
projects/pypsa-eur-sec % snakemake
```
Warning: you may need a cluster for this (with e.g. 10-100 GB of RAM
and several processors).
To only prepare the networks, you can run the scripts up to the point before optimization:
```shell
projects/pypsa-eur-sec % snakemake prepare_sector_networks
```
# Licence

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@ -4,6 +4,10 @@ PyPSA-Eur-Sec: A Sector-Coupled Open Optimisation Model of the European Energy S
.. image:: https://img.shields.io/github/v/release/pypsa/pypsa-eur-sec?include_prereleases
:alt: GitHub release (latest by date including pre-releases)
.. image:: https://readthedocs.org/projects/pypsa-eur/badge/?version=latest
:target: https://pypsa-eur.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status
.. image:: https://img.shields.io/github/license/pypsa/pypsa-eur-sec
:alt: GitHub
@ -61,6 +65,43 @@ PyPSA-Eur-Sec is designed to be imported into the open toolbox `PyPSA <https://w
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/>`_.
Spatial resolution of sectors
=============================
Not all of the sectors are at the full nodal resolution, and some are
distributed to nodes using heuristics that need to be corrected. Some
networks are copper-plated to reduce computational times.
For example:
Electricity network: nodal.
Electricity demand: nodal, distributed in each country based on
population and GDP.
Building heating demand: nodal, distributed in each country based on
population.
Industry demand: nodal, distributed in each country based on
population (will be corrected to real locations of industry, see
github issue).
Hydrogen network: nodal.
Methane network: copper-plated for Europe, since future demand is so
low and no bottlenecks are expected.
Solid biomass: copper-plated until transport costs can be
incorporated.
CO2: copper-plated (but a transport and storage cost is added for
sequestered CO2).
Liquid hydrocarbons: copper-plated since transport costs are low.
Documentation
=============