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Merge pull request #220 from PyPSA/map-proj

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improved legends, EqualEarth projection, w/wo retrofit compatibility
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Fabian Neumann 2022-12-28 15:46:29 +01:00 committed by GitHub
commit 2be8b52a1e
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5 changed files with 280 additions and 159 deletions
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3
Snakefile
View File

@ -516,7 +516,8 @@ rule prepare_sector_network:
rule plot_network:
input:
overrides="data/override_component_attrs",
network=RDIR + "/postnetworks/elec_s{simpl}_{clusters}_lv{lv}_{opts}_{sector_opts}_{planning_horizons}.nc"
network=RDIR + "/postnetworks/elec_s{simpl}_{clusters}_lv{lv}_{opts}_{sector_opts}_{planning_horizons}.nc",
regions=pypsaeur('resources/regions_onshore_elec_s{simpl}_{clusters}.geojson')
output:
map=RDIR + "/maps/elec_s{simpl}_{clusters}_lv{lv}_{opts}_{sector_opts}-costs-all_{planning_horizons}.pdf",
today=RDIR + "/maps/elec_s{simpl}_{clusters}_lv{lv}_{opts}_{sector_opts}_{planning_horizons}-today.pdf"

2
config.default.yaml
View File

@ -401,7 +401,7 @@ plotting:
boundaries: [-11, 30, 34, 71]
color_geomap:
ocean: white
land: whitesmoke
land: white
eu_node_location:
x: -5.5
y: 46.

2
doc/release_notes.rst
View File

@ -86,6 +86,8 @@ incorporates retrofitting options to hydrogen.
* Shipping demand now defaults to (synthetic) oil rather than liquefied hydrogen until 2050.
* Improved network plots including better legends, hydrogen retrofitting network display, and change to EqualEarth projection.
**Bugfixes**
* The CO2 sequestration limit implemented as GlobalConstraint (introduced in the previous version)

1
matplotlibrc
View File

@ -1,4 +1,3 @@
backend: Agg
font.family: sans-serif
font.sans-serif: Ubuntu, DejaVu Sans
image.cmap: viridis

431
scripts/plot_network.py
View File

@ -1,18 +1,17 @@
import pypsa
import numpy as np
import pandas as pd
import geopandas as gpd
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
from matplotlib.legend_handler import HandlerPatch
from matplotlib.patches import Circle, Ellipse
from pypsa.plot import add_legend_circles, add_legend_patches, add_legend_lines
from make_summary import assign_carriers
from plot_summary import rename_techs, preferred_order
from helper import override_component_attrs
plt.style.use('ggplot')
plt.style.use(['ggplot', "matplotlibrc"])
def rename_techs_tyndp(tech):
@ -27,8 +26,8 @@ def rename_techs_tyndp(tech):
return "ammonia"
elif tech in ["OCGT", "CHP", "gas boiler", "H2 Fuel Cell"]:
return "gas-to-power/heat"
elif "solar" in tech:
return "solar"
# elif "solar" in tech:
# return "solar"
elif tech in ["Fischer-Tropsch", "methanolisation"]:
return "power-to-liquid"
elif "offshore wind" in tech:
@ -39,36 +38,6 @@ def rename_techs_tyndp(tech):
return tech
def make_handler_map_to_scale_circles_as_in(ax, dont_resize_actively=False):
fig = ax.get_figure()
def axes2pt():
return np.diff(ax.transData.transform([(0, 0), (1, 1)]), axis=0)[0] * (72. / fig.dpi)
ellipses = []
if not dont_resize_actively:
def update_width_height(event):
dist = axes2pt()
for e, radius in ellipses:
e.width, e.height = 2. * radius * dist
fig.canvas.mpl_connect('resize_event', update_width_height)
ax.callbacks.connect('xlim_changed', update_width_height)
ax.callbacks.connect('ylim_changed', update_width_height)
def legend_circle_handler(legend, orig_handle, xdescent, ydescent,
width, height, fontsize):
w, h = 2. * orig_handle.get_radius() * axes2pt()
e = Ellipse(xy=(0.5 * width - 0.5 * xdescent, 0.5 *
height - 0.5 * ydescent), width=w, height=w)
ellipses.append((e, orig_handle.get_radius()))
return e
return {Circle: HandlerPatch(patch_func=legend_circle_handler)}
def make_legend_circles_for(sizes, scale=1.0, **kw):
return [Circle((0, 0), radius=(s / scale)**0.5, **kw) for s in sizes]
def assign_location(n):
for c in n.iterate_components(n.one_port_components | n.branch_components):
ifind = pd.Series(c.df.index.str.find(" ", start=4), c.df.index)
@ -80,7 +49,9 @@ def assign_location(n):
def plot_map(network, components=["links", "stores", "storage_units", "generators"],
bus_size_factor=1.7e10, transmission=False):
bus_size_factor=1.7e10, transmission=False, with_legend=True):
tech_colors = snakemake.config['plotting']['tech_colors']
n = network.copy()
assign_location(n)
@ -111,7 +82,7 @@ def plot_map(network, components=["links", "stores", "storage_units", "generator
costs = costs[new_columns]
for item in new_columns:
if item not in snakemake.config['plotting']['tech_colors']:
if item not in tech_colors:
print("Warning!",item,"not in config/plotting/tech_colors")
costs = costs.stack() # .sort_index()
@ -133,34 +104,39 @@ def plot_map(network, components=["links", "stores", "storage_units", "generator
# make sure they are removed from index
costs.index = pd.MultiIndex.from_tuples(costs.index.values)
threshold = 100e6 # 100 mEUR/a
carriers = costs.groupby(level=1).sum()
carriers = carriers.where(carriers > threshold).dropna()
carriers = list(carriers.index)
# PDF has minimum width, so set these to zero
line_lower_threshold = 500.
line_upper_threshold = 1e4
linewidth_factor = 2e3
ac_color = "gray"
dc_color = "m"
linewidth_factor = 4e3
ac_color = "rosybrown"
dc_color = "darkseagreen"
if snakemake.wildcards["lv"] == "1.0":
# should be zero
line_widths = n.lines.s_nom_opt - n.lines.s_nom
link_widths = n.links.p_nom_opt - n.links.p_nom
title = "Transmission reinforcement"
title = "added grid"
if transmission:
line_widths = n.lines.s_nom_opt
link_widths = n.links.p_nom_opt
linewidth_factor = 2e3
line_lower_threshold = 0.
title = "Today's transmission"
title = "current grid"
else:
line_widths = n.lines.s_nom_opt - n.lines.s_nom_min
link_widths = n.links.p_nom_opt - n.links.p_nom_min
title = "Transmission reinforcement"
title = "added grid"
if transmission:
line_widths = n.lines.s_nom_opt
link_widths = n.links.p_nom_opt
title = "Total transmission"
title = "total grid"
line_widths[line_widths < line_lower_threshold] = 0.
link_widths[link_widths < line_lower_threshold] = 0.
@ -168,12 +144,12 @@ def plot_map(network, components=["links", "stores", "storage_units", "generator
line_widths[line_widths > line_upper_threshold] = line_upper_threshold
link_widths[link_widths > line_upper_threshold] = line_upper_threshold
fig, ax = plt.subplots(subplot_kw={"projection": ccrs.PlateCarree()})
fig, ax = plt.subplots(subplot_kw={"projection": ccrs.EqualEarth()})
fig.set_size_inches(7, 6)
n.plot(
bus_sizes=costs / bus_size_factor,
bus_colors=snakemake.config['plotting']['tech_colors'],
bus_colors=tech_colors,
line_colors=ac_color,
link_colors=dc_color,
line_widths=line_widths / linewidth_factor,
@ -181,45 +157,66 @@ def plot_map(network, components=["links", "stores", "storage_units", "generator
ax=ax, **map_opts
)
handles = make_legend_circles_for(
[5e9, 1e9],
scale=bus_size_factor,
facecolor="gray"
)
sizes = [20, 10, 5]
labels = [f"{s} bEUR/a" for s in sizes]
sizes = [s/bus_size_factor*1e9 for s in sizes]
labels = ["{} bEUR/a".format(s) for s in (5, 1)]
l2 = ax.legend(
handles, labels,
legend_kw = dict(
loc="upper left",
bbox_to_anchor=(0.01, 1.01),
labelspacing=1.0,
bbox_to_anchor=(0.01, 1.06),
labelspacing=0.8,
frameon=False,
title='System cost',
handler_map=make_handler_map_to_scale_circles_as_in(ax)
handletextpad=0,
title='system cost',
)
ax.add_artist(l2)
add_legend_circles(
ax,
sizes,
labels,
srid=n.srid,
patch_kw=dict(facecolor="lightgrey"),
legend_kw=legend_kw
)
handles = []
labels = []
sizes = [10, 5]
labels = [f"{s} GW" for s in sizes]
scale = 1e3 / linewidth_factor
sizes = [s*scale for s in sizes]
for s in (10, 5):
handles.append(plt.Line2D([0], [0], color=ac_color,
linewidth=s * 1e3 / linewidth_factor))
labels.append("{} GW".format(s))
l1_1 = ax.legend(
handles, labels,
legend_kw = dict(
loc="upper left",
bbox_to_anchor=(0.22, 1.01),
bbox_to_anchor=(0.27, 1.06),
frameon=False,
labelspacing=0.8,
handletextpad=1.5,
handletextpad=1,
title=title
)
ax.add_artist(l1_1)
add_legend_lines(
ax,
sizes,
labels,
patch_kw=dict(color='lightgrey'),
legend_kw=legend_kw
)
legend_kw = dict(
bbox_to_anchor=(1.52, 1.04),
frameon=False,
)
if with_legend:
colors = [tech_colors[c] for c in carriers] + [ac_color, dc_color]
labels = carriers + ["HVAC line", "HVDC link"]
add_legend_patches(
ax,
colors,
labels,
legend_kw=legend_kw,
)
fig.savefig(
snakemake.output.map,
@ -248,7 +245,7 @@ def group_pipes(df, drop_direction=False):
return pipe_capacity
def plot_h2_map(network):
def plot_h2_map(network, regions):
n = network.copy()
if "H2 pipeline" not in n.links.carrier.unique():
@ -256,6 +253,10 @@ def plot_h2_map(network):
assign_location(n)
h2_storage = n.stores.query("carrier == 'H2'")
regions["H2"] = h2_storage.rename(index=h2_storage.bus.map(n.buses.location)).e_nom_opt.div(1e6) # TWh
regions["H2"] = regions["H2"].where(regions["H2"] > 0.1)
bus_size_factor = 1e5
linewidth_factor = 1e4
# MW below which not drawn
@ -264,7 +265,9 @@ def plot_h2_map(network):
# Drop non-electric buses so they don't clutter the plot
n.buses.drop(n.buses.index[n.buses.carrier != "AC"], inplace=True)
elec = n.links[n.links.carrier.isin(["H2 Electrolysis", "H2 Fuel Cell"])].index
carriers = ["H2 Electrolysis", "H2 Fuel Cell"]
elec = n.links[n.links.carrier.isin(carriers)].index
bus_sizes = n.links.loc[elec,"p_nom_opt"].groupby([n.links["bus0"], n.links.carrier]).sum() / bus_size_factor
@ -275,14 +278,44 @@ def plot_h2_map(network):
h2_new = n.links.loc[n.links.carrier=="H2 pipeline"]
h2_retro = n.links.loc[n.links.carrier=='H2 pipeline retrofitted']
# sum capacitiy for pipelines from different investment periods
h2_new = group_pipes(h2_new)
h2_retro = group_pipes(h2_retro, drop_direction=True).reindex(h2_new.index).fillna(0)
if snakemake.config['foresight'] == 'myopic':
# sum capacitiy for pipelines from different investment periods
h2_new = group_pipes(h2_new)
h2_retro = group_pipes(h2_retro, drop_direction=True).reindex(h2_new.index).fillna(0)
if not h2_retro.empty:
positive_order = h2_retro.bus0 < h2_retro.bus1
h2_retro_p = h2_retro[positive_order]
swap_buses = {"bus0": "bus1", "bus1": "bus0"}
h2_retro_n = h2_retro[~positive_order].rename(columns=swap_buses)
h2_retro = pd.concat([h2_retro_p, h2_retro_n])
h2_retro["index_orig"] = h2_retro.index
h2_retro.index = h2_retro.apply(
lambda x: f"H2 pipeline {x.bus0.replace(' H2', '')} -> {x.bus1.replace(' H2', '')}",
axis=1
)
retro_w_new_i = h2_retro.index.intersection(h2_new.index)
h2_retro_w_new = h2_retro.loc[retro_w_new_i]
retro_wo_new_i = h2_retro.index.difference(h2_new.index)
h2_retro_wo_new = h2_retro.loc[retro_wo_new_i]
h2_retro_wo_new.index = h2_retro_wo_new.index_orig
to_concat = [h2_new, h2_retro_w_new, h2_retro_wo_new]
h2_total = pd.concat(to_concat).p_nom_opt.groupby(level=0).sum()
else:
h2_total = h2_new
link_widths_total = h2_total / linewidth_factor
n.links.rename(index=lambda x: x.split("-2")[0], inplace=True)
n.links = n.links.groupby(level=0).first()
link_widths_total = (h2_new + h2_retro) / linewidth_factor
link_widths_total = link_widths_total.reindex(n.links.index).fillna(0.)
link_widths_total[n.links.p_nom_opt < line_lower_threshold] = 0.
@ -293,15 +326,27 @@ def plot_h2_map(network):
n.links.bus0 = n.links.bus0.str.replace(" H2", "")
n.links.bus1 = n.links.bus1.str.replace(" H2", "")
proj = ccrs.EqualEarth()
regions = regions.to_crs(proj.proj4_init)
fig, ax = plt.subplots(
figsize=(7, 6),
subplot_kw={"projection": ccrs.PlateCarree()}
subplot_kw={"projection": proj}
)
color_h2_pipe = '#b3f3f4'
color_retrofit = '#499a9c'
bus_colors = {
"H2 Electrolysis": "#ff29d9",
"H2 Fuel Cell": '#805394'
}
n.plot(
geomap=True,
bus_sizes=bus_sizes,
bus_colors=snakemake.config['plotting']['tech_colors'],
link_colors='#a2f0f2',
bus_colors=bus_colors,
link_colors=color_h2_pipe,
link_widths=link_widths_total,
branch_components=["Link"],
ax=ax,
@ -309,53 +354,88 @@ def plot_h2_map(network):
)
n.plot(
geomap=True,
bus_sizes=0,
link_colors='#72d3d6',
link_colors=color_retrofit,
link_widths=link_widths_retro,
branch_components=["Link"],
ax=ax,
**map_opts
color_geomap=False,
boundaries=map_opts["boundaries"]
)
handles = make_legend_circles_for(
[50000, 10000],
scale=bus_size_factor,
facecolor='grey'
regions.plot(
ax=ax,
column="H2",
cmap='Blues',
linewidths=0,
legend=True,
vmax=10,
vmin=0,
legend_kwds={
"label": "Hydrogen Storage [TWh]",
"shrink": 0.7,
"extend": "max",
},
)
labels = ["{} GW".format(s) for s in (50, 10)]
sizes = [50, 10]
labels = [f"{s} GW" for s in sizes]
sizes = [s/bus_size_factor*1e3 for s in sizes]
l2 = ax.legend(
handles, labels,
legend_kw = dict(
loc="upper left",
bbox_to_anchor=(-0.03, 1.01),
labelspacing=1.0,
bbox_to_anchor=(0, 1),
labelspacing=0.8,
handletextpad=0,
frameon=False,
title='Electrolyzer capacity',
handler_map=make_handler_map_to_scale_circles_as_in(ax)
)
ax.add_artist(l2)
add_legend_circles(ax, sizes, labels,
srid=n.srid,
patch_kw=dict(facecolor='lightgrey'),
legend_kw=legend_kw
)
handles = []
labels = []
sizes = [30, 10]
labels = [f"{s} GW" for s in sizes]
scale = 1e3 / linewidth_factor
sizes = [s*scale for s in sizes]
for s in (50, 10):
handles.append(plt.Line2D([0], [0], color="grey",
linewidth=s * 1e3 / linewidth_factor))
labels.append("{} GW".format(s))
l1_1 = ax.legend(
handles, labels,
legend_kw = dict(
loc="upper left",
bbox_to_anchor=(0.28, 1.01),
bbox_to_anchor=(0.23, 1),
frameon=False,
labelspacing=0.8,
handletextpad=1.5,
title='H2 pipeline capacity'
handletextpad=1,
)
ax.add_artist(l1_1)
add_legend_lines(
ax,
sizes,
labels,
patch_kw=dict(color='lightgrey'),
legend_kw=legend_kw,
)
colors = [bus_colors[c] for c in carriers] + [color_h2_pipe, color_retrofit]
labels = carriers + ["H2 pipeline (total)", "H2 pipeline (repurposed)"]
legend_kw = dict(
loc="upper left",
bbox_to_anchor=(0, 1.13),
ncol=2,
frameon=False,
)
add_legend_patches(
ax,
colors,
labels,
legend_kw=legend_kw
)
ax.set_facecolor("white")
fig.savefig(
snakemake.output.map.replace("-costs-all","-h2_network"),
@ -415,26 +495,32 @@ def plot_ch4_map(network):
link_widths_used = max_usage / linewidth_factor
link_widths_used[max_usage < line_lower_threshold] = 0.
link_color_used = n.links.carrier.map({"gas pipeline": "#f08080",
"gas pipeline new": "#c46868"})
tech_colors = snakemake.config['plotting']['tech_colors']
pipe_colors = {
"gas pipeline": "#f08080",
"gas pipeline new": "#c46868",
"gas pipeline (in 2020)": 'lightgrey',
"gas pipeline (available)": '#e8d1d1',
}
link_color_used = n.links.carrier.map(pipe_colors)
n.links.bus0 = n.links.bus0.str.replace(" gas", "")
n.links.bus1 = n.links.bus1.str.replace(" gas", "")
tech_colors = snakemake.config['plotting']['tech_colors']
bus_colors = {
"fossil gas": tech_colors["fossil gas"],
"methanation": tech_colors["methanation"],
"biogas": "seagreen"
}
fig, ax = plt.subplots(figsize=(7,6), subplot_kw={"projection": ccrs.PlateCarree()})
fig, ax = plt.subplots(figsize=(7,6), subplot_kw={"projection": ccrs.EqualEarth()})
n.plot(
bus_sizes=bus_sizes,
bus_colors=bus_colors,
link_colors='lightgrey',
link_colors=pipe_colors['gas pipeline (in 2020)'],
link_widths=link_widths_orig,
branch_components=["Link"],
ax=ax,
@ -444,10 +530,11 @@ def plot_ch4_map(network):
n.plot(
ax=ax,
bus_sizes=0.,
link_colors='#e8d1d1',
link_colors=pipe_colors['gas pipeline (available)'],
link_widths=link_widths_rem,
branch_components=["Link"],
**map_opts
color_geomap=False,
boundaries=map_opts["boundaries"]
)
n.plot(
@ -456,46 +543,76 @@ def plot_ch4_map(network):
link_colors=link_color_used,
link_widths=link_widths_used,
branch_components=["Link"],
**map_opts
color_geomap=False,
boundaries=map_opts["boundaries"]
)
handles = make_legend_circles_for(
[10e6, 100e6],
scale=bus_size_factor,
facecolor='grey'
)
labels = ["{} TWh".format(s) for s in (10, 100)]
l2 = ax.legend(
handles, labels,
sizes = [100, 10]
labels = [f"{s} TWh" for s in sizes]
sizes = [s/bus_size_factor*1e6 for s in sizes]
legend_kw = dict(
loc="upper left",
bbox_to_anchor=(-0.03, 1.01),
labelspacing=1.0,
bbox_to_anchor=(0, 1.03),
labelspacing=0.8,
frameon=False,
title='gas generation',
handler_map=make_handler_map_to_scale_circles_as_in(ax)
handletextpad=1,
title='gas sources',
)
add_legend_circles(
ax,
sizes,
labels,
srid=n.srid,
patch_kw=dict(facecolor='lightgrey'),
legend_kw=legend_kw,
)
ax.add_artist(l2)
handles = []
labels = []
for s in (50, 10):
handles.append(plt.Line2D([0], [0], color="grey", linewidth=s * 1e3 / linewidth_factor))
labels.append("{} GW".format(s))
l1_1 = ax.legend(
handles, labels,
sizes = [50, 10]
labels = [f"{s} GW" for s in sizes]
scale = 1e3 / linewidth_factor
sizes = [s*scale for s in sizes]
legend_kw = dict(
loc="upper left",
bbox_to_anchor=(0.28, 1.01),
bbox_to_anchor=(0.25, 1.03),
frameon=False,
labelspacing=0.8,
handletextpad=1.5,
title='gas pipeline used capacity'
handletextpad=1,
title='gas pipeline'
)
add_legend_lines(
ax,
sizes,
labels,
patch_kw=dict(color='lightgrey'),
legend_kw=legend_kw,
)
ax.add_artist(l1_1)
colors = list(pipe_colors.values()) + list(bus_colors.values())
labels = list(pipe_colors.keys()) + list(bus_colors.keys())
# legend on the side
# legend_kw = dict(
# bbox_to_anchor=(1.47, 1.04),
# frameon=False,
# )
legend_kw = dict(
loc='upper left',
bbox_to_anchor=(0, 1.24),
ncol=2,
frameon=False,
)
add_legend_patches(
ax,
colors,
labels,
legend_kw=legend_kw,
)
fig.savefig(
snakemake.output.map.replace("-costs-all","-ch4_network"),
@ -513,15 +630,15 @@ def plot_map_without(network):
fig, ax = plt.subplots(
figsize=(7, 6),
subplot_kw={"projection": ccrs.PlateCarree()}
subplot_kw={"projection": ccrs.EqualEarth()}
)
# PDF has minimum width, so set these to zero
line_lower_threshold = 200.
line_upper_threshold = 1e4
linewidth_factor = 2e3
ac_color = "gray"
dc_color = "m"
linewidth_factor = 3e3
ac_color = "rosybrown"
dc_color = "darkseagreen"
# hack because impossible to drop buses...
if "EU gas" in n.buses.index:
@ -560,7 +677,7 @@ def plot_map_without(network):
for s in (10, 5):
handles.append(plt.Line2D([0], [0], color=ac_color,
linewidth=s * 1e3 / linewidth_factor))
labels.append("{} GW".format(s))
labels.append(f"{s} GW")
l1_1 = ax.legend(handles, labels,
loc="upper left", bbox_to_anchor=(0.05, 1.01),
frameon=False,
@ -710,25 +827,27 @@ if __name__ == "__main__":
snakemake = mock_snakemake(
'plot_network',
simpl='',
clusters="45",
lv=1.0,
clusters="181",
lv='opt',
opts='',
sector_opts='168H-T-H-B-I-A-solar+p3-dist1',
sector_opts='Co2L0-730H-T-H-B-I-A-solar+p3-linemaxext10',
planning_horizons="2050",
)
overrides = override_component_attrs(snakemake.input.overrides)
n = pypsa.Network(snakemake.input.network, override_component_attrs=overrides)
regions = gpd.read_file(snakemake.input.regions).set_index("name")
map_opts = snakemake.config['plotting']['map']
plot_map(n,
components=["generators", "links", "stores", "storage_units"],
bus_size_factor=1.5e10,
bus_size_factor=2e10,
transmission=False
)
plot_h2_map(n)
plot_h2_map(n, regions)
plot_ch4_map(n)
plot_map_without(n)