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update documentation and release notes

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martavp 2021-01-01 17:53:59 +01:00
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13
doc/installation.rst
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@ -16,7 +16,7 @@ its dependencies. Clone the repository:
.. code:: bash
projects % git clone git@github.com:PyPSA/pypsa-eur.git
projects % git clone https://github.com/PyPSA/pypsa-eur.git
then download and unpack all the PyPSA-Eur data files by running the following snakemake rule:
@ -32,7 +32,7 @@ Next install the technology assumptions database `technology-data <https://githu
.. code:: bash
projects % git clone git@github.com:PyPSA/technology-data.git
projects % git clone https://github.com/PyPSA/technology-data.git
Clone PyPSA-Eur-Sec repository
@ -42,7 +42,7 @@ Create a parallel directory for `PyPSA-Eur-Sec <https://github.com/PyPSA/pypsa-e
.. code:: bash
projects % git clone git@github.com:PyPSA/pypsa-eur-sec.git
projects % git clone https://github.com/PyPSA/pypsa-eur-sec.git
Environment/package requirements
================================
@ -54,6 +54,13 @@ The requirements are the same as `PyPSA-Eur <https://github.com/PyPSA/pypsa-eur>
xarray version >= 0.15.1, you will need the latest master branch of
atlite version 0.0.2.
You can create an enviroment using the environment.yaml file in pypsa-eur/envs:
.../pypsa-eur % conda env create -f envs/environment.yaml
.../pypsa-eur % conda activate pypsa-eur
See details in `PyPSA-Eur Installation <https://pypsa-eur.readthedocs.io/en/latest/installation.html>`_
Data requirements
=================

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doc/myopic.rst
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@ -6,7 +6,7 @@ Myopic transition path
The myopic code can be used to investigate progressive changes in a network, for instance, those taking place throughout a transition path. The capacities installed in a certain time step are maintained in the network until their operational lifetime expires.
The myopic approach was initially developed and used in the paper `Early decarbonisation of the European Energy system pays off (2020) <https://arxiv.org/abs/2004.11009>`__ but the current implementation complies with the pypsa-eur-sec standard working flow and is compatible with using the higher resolution electricity transmission model `PyPSA-Eur <https://github.com/PyPSA/pypsa-eur>`__ rather than a one-node-per-country model.
The myopic approach was initially developed and used in the paper `Early decarbonisation of the European Energy system pays off (2020) <https://www.nature.com/articles/s41467-020-20015-4>`__ but the current implementation complies with the pypsa-eur-sec standard working flow and is compatible with using the higher resolution electricity transmission model `PyPSA-Eur <https://github.com/PyPSA/pypsa-eur>`__ rather than a one-node-per-country model.
The current code applies the myopic approach to generators, storage technologies and links in the power sector and the space and water heating sector.
@ -61,12 +61,15 @@ Wildcards
The {planning_horizons} wildcard indicates the timesteps in which the network is optimized, e.g. planning_horizons: [2020, 2030, 2040, 2050]
Options
=============
The total carbon budget for the entire transition path can be indicated in the ``scenario.sector_opts`` in ``config.yaml``.
The carbon budget can be split among the ``planning_horizons`` following an exponential or beta decay.
E.g. ``'cb40ex0'`` splits the a carbon budget equal to 40 GtCO_2 following an exponential decay whose initial linear growth rate $r$ is zero
**{co2_budget_name} wildcard**
$e(t) = e_0 (1+ (r+m)t) e^(-mt)$
The {co2_budget_name} wildcard indicates the name of the co2 budget.
A csv file is used as input including the planning_horizons as index, the name of co2_budget as column name, and the maximum co2 emissions (relative to 1990) as values.
See details in Supplementary Note 1 of the paper `Early decarbonisation of the European Energy system pays off (2020) <https://www.nature.com/articles/s41467-020-20015-4>`__
Rules overview
=================
@ -74,17 +77,17 @@ Rules overview
General myopic code structure
===============================
The myopic code solves the network for the time steps included in planning_horizons in a recursive loop, so that:
The myopic code solves the network for the time steps included in ``planning_horizons`` in a recursive loop, so that:
1.The existing capacities (those installed before the base year are added as fixed capacities with p_nom=value, p_nom_extendable=False). E.g. for baseyear=2020, capacities installed before 2020 are added. In addition, the network comprises additional generator, storage, and link capacities with p_nom_extendable=True. The non-solved network is saved in ``results/run_name/networks/prenetworks-brownfield``.
The base year is the first element in planning_horizons. Step 1 is implemented with the rule add_baseyear for the base year and with the rule add_brownfield for the remaining planning_horizons.
The base year is the first element in ``planning_horizons``. Step 1 is implemented with the rule add_baseyear for the base year and with the rule add_brownfield for the remaining planning_horizons.
2.The 2020 network is optimized. The solved network is saved in ‘results/run_name/networks/postnetworks’
2.The 2020 network is optimized. The solved network is saved in ``results/run_name/networks/postnetworks``
3.For the next planning horizon, e.g. 2030, the capacities from a previous time step are added if they are still in operation (i.e., if they fulfil planning horizon <= commissioned year + lifetime). In addition, the network comprises additional generator, storage, and link capacities with p_nom_extendable=True. The non-solved network is saved in ``results/run_name/networks/prenetworks-brownfield``.
Steps 2 and 3 are solved recursively for all the planning_horizons included in the configuration file.
Steps 2 and 3 are solved recursively for all the planning_horizons included in ``config.yaml``.
rule add_existing baseyear
@ -110,8 +113,8 @@ Then, the resulting network is saved in ``results/run_name/networks/prenetworks-
rule add_brownfield
===================
The rule add_brownfield loads the network in ‘results/run_name/networks/prenetworks’ and performs the following operation:
The rule add_brownfield loads the network in ``results/run_name/networks/prenetworks`` and performs the following operation:
1.Read the capacities optimized in the previous time step and add them to the network if they are still in operation (i.e., if they fulfil planning horizon < commissioned year + lifetime)
1.Read the capacities optimized in the previous time step and add them to the network if they are still in operation (i.e., if they fulfill planning horizon < commissioned year + lifetime)
Then, the resulting network is saved in ``results/run_name/networks/prenetworks_brownfield``.

3
doc/release_notes.rst
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@ -2,6 +2,9 @@
Release Notes
##########################################
Future release
===================
*For the myopic option, a carbon budget and a type of decay (exponential or beta) can be selected in the config file to distribute the budget across the planning_horizons.
PyPSA-Eur-Sec 0.4.0 (11th December 2020)
=========================================

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doc/supply_demand.rst
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@ -106,7 +106,7 @@ Thermal energy storage using hot water tanks
Small for decentral applications.
Big pit storage for district heating.
Big water pit storage for district heating.
Hydrogen demand
@ -122,7 +122,7 @@ Industry (ammonia, precursor to hydrocarbons for chemicals and iron/steel).
Hydrogen supply
=================
SMR, SMR+CCS, electrolysers.
Steam Methane Reforming (SMR), SMR+CCS, electrolysers.
Methane demand