013b705ee4
* Cluster first: build renewable profiles and add all assets after clustering * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * correction: pass landfall_lengths through functions * assign landfall_lenghts correctly * remove parameter add_land_use_constraint * fix network_dict * calculate distance to shoreline, remove underwater_fraction * adjust simplification parameter to exclude Crete from offshore wind connections * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * remove unused geth2015 hydro capacities * removing remaining traces of {simpl} wildcard * add release notes and update workflow graphics * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: lisazeyen <lisa.zeyen@web.de>
14 KiB
Tutorial: Electricity-Only
Note
If you have not done it yet, follow the :ref:`installation` steps first.
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Unknown interpreted text role "ref".In this tutorial, we will build a heavily simplified power system model for Belgium. But before getting started with PyPSA-Eur it makes sense to be familiar with its general modelling framework PyPSA.
Running the tutorial requires limited computational resources compared to the full model, which allows the user to explore most of its functionalities on a local machine. The tutorial will cover examples on how to configure and customise the PyPSA-Eur model and run the snakemake workflow step by step from network creation to the solved network. The configuration for the tutorial is located at config/test/config.electricity.yaml. It includes parts deviating from the default config file config/config.default.yaml. To run the tutorial with this configuration, execute
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.. code:: bash
:class: full-width
snakemake -call results/test-elec/networks/base_s_6_elec_lcopt_.nc --configfile config/test/config.electricity.yaml
This configuration is set to download a reduced cutout via the rule :mod:`retrieve_cutout`. For more information on the data dependencies of PyPSA-Eur, continue reading :ref:`data`.
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Unknown interpreted text role "mod".System Message: ERROR/3 (<stdin>, line 37); backlink
Unknown interpreted text role "ref".How to configure runs?
The model can be adapted to only include selected countries (e.g. Belgium) instead of all European countries to limit the spatial scope.
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Unknown directive type "literalinclude".
.. literalinclude:: ../config/test/config.electricity.yaml :language: yaml :start-at: countries: :end-before: snapshots:
Likewise, the example's temporal scope can be restricted (e.g. to a single week).
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Unknown directive type "literalinclude".
.. literalinclude:: ../config/test/config.electricity.yaml :language: yaml :start-at: snapshots: :end-before: electricity:
It is also possible to allow less or more carbon-dioxide emissions. Here, we limit the emissions of Belgium to 100 Mt per year.
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Unknown directive type "literalinclude".
.. literalinclude:: ../config/test/config.electricity.yaml :language: yaml :start-at: electricity: :end-before: extendable_carriers:
PyPSA-Eur also includes a database of existing conventional powerplants. We can select which types of existing powerplants we like to be extendable:
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Unknown directive type "literalinclude".
.. literalinclude:: ../config/test/config.electricity.yaml :language: yaml :start-at: extendable_carriers: :end-before: renewable_carriers:
To accurately model the temporal and spatial availability of renewables such as wind and solar energy, we rely on historical weather data. It is advisable to adapt the required range of coordinates to the selection of countries.
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Unknown directive type "literalinclude".
.. literalinclude:: ../config/test/config.electricity.yaml :language: yaml :start-at: atlite: :end-before: renewable:
We can also decide which weather data source should be used to calculate potentials and capacity factor time-series for each carrier. For example, we may want to use the ERA-5 dataset for solar and not the default SARAH-3 dataset.
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Unknown directive type "literalinclude".
.. literalinclude:: ../config/test/config.electricity.yaml :language: yaml :start-at: solar: :end-at: cutout:
Finally, it is possible to pick a solver. For instance, this tutorial uses the open-source solver GLPK.
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Unknown directive type "literalinclude".
.. literalinclude:: ../config/test/config.electricity.yaml :language: yaml :start-at: solver: :end-before: plotting:
Note, that config/test/config.electricity.yaml only includes changes relative to the default configuration. There are many more configuration options, which are documented at :ref:`config`.
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Unknown interpreted text role "ref".How to use snakemake rules?
Open a terminal, go into the PyPSA-Eur directory, and activate the pypsa-eur environment with
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.. code:: bash
mamba activate pypsa-eur
Let's say based on the modifications above we would like to solve a very simplified model clustered down to 6 buses and every 24 hours aggregated to one snapshot. The command
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.. code:: bash
snakemake -call results/test-elec/networks/base_s_6_elec_lcopt_.nc --configfile config/test/config.electricity.yaml
orders snakemake to run the rule :mod:`solve_network` that produces the solved network and stores it in results/networks with the name base_s_6_elec_lcopt_.nc:
System Message: ERROR/3 (<stdin>, line 119); backlink
Unknown interpreted text role "mod".System Message: ERROR/3 (<stdin>, line 121)
Unknown directive type "literalinclude".
.. literalinclude:: ../rules/solve_electricity.smk :start-at: rule solve_network: :end-before: rule solve_operations_network:
This triggers a workflow of multiple preceding jobs that depend on each rule's inputs and outputs:
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Unknown directive type "graphviz".
.. graphviz::
:class: full-width
:align: center
digraph snakemake_dag {
graph[bgcolor=white, margin=0];
node[shape=box, style=rounded, fontname=sans, fontsize=10, penwidth=2];
edge[penwidth=2, color=grey];
0[label = "solve_network", color = "0.19 0.6 0.85", style="rounded"];
1[label = "prepare_network\nll: copt\nopts: ", color = "0.24 0.6 0.85", style="rounded"];
2[label = "add_electricity", color = "0.35 0.6 0.85", style="rounded"];
3[label = "build_renewable_profiles", color = "0.15 0.6 0.85", style="rounded"];
4[label = "determine_availability_matrix\ntechnology: solar", color = "0.39 0.6 0.85", style="rounded"];
5[label = "retrieve_databundle", color = "0.65 0.6 0.85", style="rounded"];
6[label = "build_shapes", color = "0.45 0.6 0.85", style="rounded"];
7[label = "retrieve_naturalearth_countries", color = "0.03 0.6 0.85", style="rounded"];
8[label = "retrieve_eez", color = "0.17 0.6 0.85", style="rounded"];
9[label = "cluster_network\nclusters: 6", color = "0.38 0.6 0.85", style="rounded"];
10[label = "simplify_network", color = "0.14 0.6 0.85", style="rounded"];
11[label = "add_transmission_projects_and_dlr", color = "0.61 0.6 0.85", style="rounded"];
12[label = "base_network", color = "0.36 0.6 0.85", style="rounded"];
13[label = "retrieve_osm_prebuilt", color = "0.22 0.6 0.85", style="rounded"];
14[label = "build_line_rating", color = "0.50 0.6 0.85", style="rounded"];
15[label = "retrieve_cutout\ncutout: be-03-2013-era5", color = "0.02 0.6 0.85", style="rounded"];
16[label = "build_transmission_projects", color = "0.08 0.6 0.85", style="rounded"];
17[label = "build_electricity_demand_base", color = "0.11 0.6 0.85", style="rounded"];
18[label = "build_electricity_demand", color = "0.60 0.6 0.85", style="rounded"];
19[label = "retrieve_electricity_demand", color = "0.60 0.6 0.85", style="rounded"];
20[label = "retrieve_synthetic_electricity_demand", color = "0.32 0.6 0.85", style="rounded"];
21[label = "build_renewable_profiles", color = "0.15 0.6 0.85", style="rounded"];
22[label = "determine_availability_matrix\ntechnology: solar-hsat", color = "0.39 0.6 0.85", style="rounded"];
23[label = "build_renewable_profiles", color = "0.15 0.6 0.85", style="rounded"];
24[label = "determine_availability_matrix\ntechnology: onwind", color = "0.39 0.6 0.85", style="rounded"];
25[label = "build_renewable_profiles", color = "0.15 0.6 0.85", style="rounded"];
26[label = "determine_availability_matrix\ntechnology: offwind-ac", color = "0.39 0.6 0.85", style="rounded"];
27[label = "build_ship_raster", color = "0.12 0.6 0.85", style="rounded"];
28[label = "retrieve_ship_raster", color = "0.44 0.6 0.85", style="rounded"];
29[label = "build_renewable_profiles", color = "0.15 0.6 0.85", style="rounded"];
30[label = "determine_availability_matrix\ntechnology: offwind-dc", color = "0.39 0.6 0.85", style="rounded"];
31[label = "build_renewable_profiles", color = "0.15 0.6 0.85", style="rounded"];
32[label = "determine_availability_matrix\ntechnology: offwind-float", color = "0.39 0.6 0.85", style="rounded"];
33[label = "retrieve_cost_data\nyear: 2030", color = "0.01 0.6 0.85", style="rounded"];
34[label = "build_powerplants", color = "0.52 0.6 0.85", style="rounded"];
1 -> 0
2 -> 1
33 -> 1
3 -> 2
21 -> 2
23 -> 2
25 -> 2
29 -> 2
31 -> 2
9 -> 2
33 -> 2
34 -> 2
17 -> 2
4 -> 3
6 -> 3
9 -> 3
15 -> 3
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15 -> 21
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32 -> 31
6 -> 31
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5 -> 32
27 -> 32
6 -> 32
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9 -> 34
}
In the terminal, this will show up as a list of jobs to be run:
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.. code:: bash
Building DAG of jobs...
Job stats:
job count
------------------------------------- -------
add_electricity 1
add_transmission_projects_and_dlr 1
base_network 1
build_electricity_demand 1
build_electricity_demand_base 1
build_line_rating 1
build_powerplants 1
build_renewable_profiles 6
build_shapes 1
build_ship_raster 1
build_transmission_projects 1
cluster_network 1
determine_availability_matrix 6
prepare_network 1
retrieve_cost_data 1
retrieve_cutout 1
retrieve_databundle 1
retrieve_eez 1
retrieve_electricity_demand 1
retrieve_naturalearth_countries 1
retrieve_osm_prebuilt 1
retrieve_ship_raster 1
retrieve_synthetic_electricity_demand 1
simplify_network 1
solve_network 1
total 35
snakemake then runs these jobs in the correct order.
A job (here simplify_network) will display its attributes and normally some logs below this block:
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.. code:: bash
rule simplify_network:
input: resources/test/networks/base_extended.nc, resources/test/regions_onshore.geojson, resources/test/regions_offshore.geojson
output: resources/test/networks/base_s.nc, resources/test/regions_onshore_base_s.geojson, resources/test/regions_offshore_base_s.geojson, resources/test/busmap_base_s.csv
log: logs/test/simplify_network.log
jobid: 10
benchmark: benchmarks/test/simplify_network_b
reason: Forced execution
resources: tmpdir=<TBD>, mem_mb=12000, mem_mib=11445
Once the whole worktree is finished, it should state so in the terminal.
You will notice that many intermediate stages are saved, namely the outputs of each individual snakemake rule.
You can produce any output file occurring in the Snakefile by running
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.. code:: bash
snakemake -call <output file>
For example, you can explore the evolution of the PyPSA networks by running
- snakemake resources/networks/base.nc -call --configfile config/test/config.electricity.yaml
- snakemake resources/networks/base_s.nc -call --configfile config/test/config.electricity.yaml
- snakemake resources/networks/base_s_6.nc -call --configfile config/test/config.electricity.yaml
- snakemake resources/networks/base_s_6_elec_lcopt_.nc -call --configfile config/test/config.electricity.yaml
To run all combinations of wildcard values provided in the config/config.yaml under scenario:, you can use the collection rule solve_elec_networks.
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.. code:: bash
snakemake -call solve_elec_networks --configfile config/test/config.electricity.yaml
If you now feel confident and want to tackle runs with larger temporal and spatial scope, clean-up the repository and after modifying the config/config.yaml file target the collection rule solve_elec_networks again without providing the test configuration file.
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.. code:: bash
snakemake -call purge
snakemake -call solve_elec_networks
Note
It is good practice to perform a dry-run using the option -n, before you commit to a run:
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.. code:: bash
snakemake -call solve_elec_networks -n
How to analyse results?
The solved networks can be analysed just like any other PyPSA network (e.g. in Jupyter Notebooks).
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.. code:: python
import pypsa
n = pypsa.Network("results/networks/base_s_6_elec_lcopt_.nc")
For inspiration, read the examples section in the PyPSA documentation.