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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 .. 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: 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 .. 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 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 .. 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 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 xarray version >= 0.15.1, you will need the latest master branch of
atlite version 0.0.2. 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 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 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. 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] 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. 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>`__
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.
Rules overview Rules overview
================= =================
@ -74,17 +77,17 @@ Rules overview
General myopic code structure 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``. 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``. 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 rule add_existing baseyear
@ -110,8 +113,8 @@ Then, the resulting network is saved in ``results/run_name/networks/prenetworks-
rule add_brownfield 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``. Then, the resulting network is saved in ``results/run_name/networks/prenetworks_brownfield``.

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doc/release_notes.rst
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@ -2,6 +2,9 @@
Release Notes 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) 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. Small for decentral applications.
Big pit storage for district heating. Big water pit storage for district heating.
Hydrogen demand Hydrogen demand
@ -122,7 +122,7 @@ Industry (ammonia, precursor to hydrocarbons for chemicals and iron/steel).
Hydrogen supply Hydrogen supply
================= =================
SMR, SMR+CCS, electrolysers. Steam Methane Reforming (SMR), SMR+CCS, electrolysers.
Methane demand Methane demand