Merge pull request #1013 from PyPSA/store-network-shapes

Store network shapes
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Fabian Hofmann 2024-04-17 12:59:54 +02:00 committed by GitHub
commit 0a19d90b60
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5 changed files with 104 additions and 29 deletions

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@ -184,6 +184,8 @@ Upcoming Release
* Fix custom busmap read in `cluster_network`.
* Added shapes to .nc file for different stages of the network object in `base_network`, `build_bus_regions`, and `cluster_network`.
* Fix p_nom_min of renewables generators for myopic approach and add check of existing capacities in `add_land_use_constraint_m`.
* Add documentation section for how to contribute documentation

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@ -698,6 +698,22 @@ def _adjust_capacities_of_under_construction_branches(n, config):
return n
def _set_shapes(n, country_shapes, offshore_shapes):
# Write the geodataframes country_shapes and offshore_shapes to the network.shapes component
country_shapes = gpd.read_file(country_shapes).rename(columns={"name": "idx"})
country_shapes["type"] = "country"
offshore_shapes = gpd.read_file(offshore_shapes).rename(columns={"name": "idx"})
offshore_shapes["type"] = "offshore"
all_shapes = pd.concat([country_shapes, offshore_shapes], ignore_index=True)
n.madd(
"Shape",
all_shapes.index,
geometry=all_shapes.geometry,
idx=all_shapes.idx,
type=all_shapes["type"],
)
def base_network(
eg_buses,
eg_converters,
@ -758,11 +774,14 @@ def base_network(
n = _adjust_capacities_of_under_construction_branches(n, config)
_set_shapes(n, country_shapes, offshore_shapes)
return n
if __name__ == "__main__":
if "snakemake" not in globals():
from _helpers import mock_snakemake
snakemake = mock_snakemake("base_network")

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@ -109,6 +109,34 @@ def voronoi_partition_pts(points, outline):
return polygons
def append_bus_shapes(n, shapes, type):
"""
Append shapes to the network. If shapes with the same component and type
already exist, they will be removed.
Parameters:
n (pypsa.Network): The network to which the shapes will be appended.
shapes (geopandas.GeoDataFrame): The shapes to be appended.
**kwargs: Additional keyword arguments used in `n.madd`.
Returns:
None
"""
remove = n.shapes.query("component == 'Bus' and type == @type").index
n.mremove("Shape", remove)
offset = n.shapes.index.astype(int).max() + 1 if not n.shapes.empty else 0
shapes = shapes.rename(lambda x: int(x) + offset)
n.madd(
"Shape",
shapes.index,
geometry=shapes.geometry,
idx=shapes.name,
component="Bus",
type=type,
)
if __name__ == "__main__":
if "snakemake" not in globals():
from _helpers import mock_snakemake
@ -119,7 +147,8 @@ if __name__ == "__main__":
countries = snakemake.params.countries
n = pypsa.Network(snakemake.input.base_network)
base_network = snakemake.input.base_network
n = pypsa.Network(base_network)
country_shapes = gpd.read_file(snakemake.input.country_shapes).set_index("name")[
"geometry"
@ -173,12 +202,17 @@ if __name__ == "__main__":
offshore_regions_c = offshore_regions_c.loc[offshore_regions_c.area > 1e-2]
offshore_regions.append(offshore_regions_c)
pd.concat(onshore_regions, ignore_index=True).to_file(
snakemake.output.regions_onshore
)
shapes = pd.concat(onshore_regions, ignore_index=True)
shapes.to_file(snakemake.output.regions_onshore)
append_bus_shapes(n, shapes, "onshore")
if offshore_regions:
pd.concat(offshore_regions, ignore_index=True).to_file(
snakemake.output.regions_offshore
)
shapes = pd.concat(offshore_regions, ignore_index=True)
shapes.to_file(snakemake.output.regions_offshore)
append_bus_shapes(n, shapes, "offshore")
else:
offshore_shapes.to_frame().to_file(snakemake.output.regions_offshore)
# save network with shapes
n.export_to_netcdf(base_network)

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@ -135,6 +135,7 @@ import pypsa
import seaborn as sns
from _helpers import configure_logging, set_scenario_config, update_p_nom_max
from add_electricity import load_costs
from build_bus_regions import append_bus_shapes
from packaging.version import Version, parse
from pypsa.clustering.spatial import (
busmap_by_greedy_modularity,
@ -428,20 +429,27 @@ def clustering_for_n_clusters(
return clustering
def cluster_regions(busmaps, input=None, output=None):
def cluster_regions(busmaps, regions):
"""
Cluster regions based on busmaps and save the results to a file and to the
network.
Parameters:
- busmaps (list): A list of busmaps used for clustering.
- which (str): The type of regions to cluster.
Returns:
None
"""
busmap = reduce(lambda x, y: x.map(y), busmaps[1:], busmaps[0])
for which in ("regions_onshore", "regions_offshore"):
regions = gpd.read_file(getattr(input, which))
regions = regions.reindex(columns=["name", "geometry"]).set_index("name")
regions_c = regions.dissolve(busmap)
regions_c.index.name = "name"
regions_c = regions_c.reset_index()
regions_c.to_file(getattr(output, which))
regions = regions.reindex(columns=["name", "geometry"]).set_index("name")
regions_c = regions.dissolve(busmap)
regions_c.index.name = "name"
return regions_c.reset_index()
def plot_busmap_for_n_clusters(n, n_clusters, fn=None):
busmap = busmap_for_n_clusters(n, n_clusters)
def plot_busmap_for_n_clusters(n, n_clusters, solver_name="scip", fn=None):
busmap = busmap_for_n_clusters(n, n_clusters, solver_name)
cs = busmap.unique()
cr = sns.color_palette("hls", len(cs))
n.plot(bus_colors=busmap.map(dict(zip(cs, cr))))
@ -538,21 +546,25 @@ if __name__ == "__main__":
params.focus_weights,
)
update_p_nom_max(clustering.network)
nc = clustering.network
update_p_nom_max(nc)
if params.cluster_network.get("consider_efficiency_classes"):
labels = [f" {label} efficiency" for label in ["low", "medium", "high"]]
nc = clustering.network
nc.generators["carrier"] = nc.generators.carrier.replace(labels, "", regex=True)
clustering.network.meta = dict(
snakemake.config, **dict(wildcards=dict(snakemake.wildcards))
)
clustering.network.export_to_netcdf(snakemake.output.network)
for attr in (
"busmap",
"linemap",
): # also available: linemap_positive, linemap_negative
getattr(clustering, attr).to_csv(snakemake.output[attr])
cluster_regions((clustering.busmap,), snakemake.input, snakemake.output)
nc.shapes = n.shapes.copy()
for which in ["regions_onshore", "regions_offshore"]:
regions = gpd.read_file(snakemake.input[which])
clustered_regions = cluster_regions((clustering.busmap,), regions)
clustered_regions.to_file(snakemake.output[which])
append_bus_shapes(nc, clustered_regions, type=which.split("_")[1])
nc.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards)))
nc.export_to_netcdf(snakemake.output.network)

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@ -88,12 +88,14 @@ The rule :mod:`simplify_network` does up to four things:
import logging
from functools import reduce
import geopandas as gpd
import numpy as np
import pandas as pd
import pypsa
import scipy as sp
from _helpers import configure_logging, set_scenario_config, update_p_nom_max
from add_electricity import load_costs
from build_bus_regions import append_bus_shapes
from cluster_network import cluster_regions, clustering_for_n_clusters
from pypsa.clustering.spatial import (
aggregateoneport,
@ -610,6 +612,7 @@ if __name__ == "__main__":
n.lines.drop(remove, axis=1, errors="ignore", inplace=True)
if snakemake.wildcards.simpl:
shapes = n.shapes
n, cluster_map = cluster(
n,
int(snakemake.wildcards.simpl),
@ -619,14 +622,19 @@ if __name__ == "__main__":
params.simplify_network["feature"],
params.aggregation_strategies,
)
n.shapes = shapes
busmaps.append(cluster_map)
update_p_nom_max(n)
n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards)))
n.export_to_netcdf(snakemake.output.network)
busmap_s = reduce(lambda x, y: x.map(y), busmaps[1:], busmaps[0])
busmap_s.to_csv(snakemake.output.busmap)
cluster_regions(busmaps, snakemake.input, snakemake.output)
for which in ["regions_onshore", "regions_offshore"]:
regions = gpd.read_file(snakemake.input[which])
clustered_regions = cluster_regions(busmaps, regions)
clustered_regions.to_file(snakemake.output[which])
append_bus_shapes(n, clustered_regions, type=which.split("_")[1])
n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards)))
n.export_to_netcdf(snakemake.output.network)