92 lines
2.3 KiB
Python
92 lines
2.3 KiB
Python
# -*- coding: utf-8 -*-
|
|
# SPDX-FileCopyrightText: : 2017-2023 The PyPSA-Eur Authors
|
|
#
|
|
# SPDX-License-Identifier: MIT
|
|
|
|
"""
|
|
Plots renewable installation potentials per capacity factor.
|
|
|
|
Relevant Settings
|
|
-----------------
|
|
|
|
Inputs
|
|
------
|
|
|
|
Outputs
|
|
-------
|
|
|
|
Description
|
|
-----------
|
|
"""
|
|
import logging
|
|
|
|
import matplotlib.pyplot as plt
|
|
import pandas as pd
|
|
import pypsa
|
|
from _helpers import configure_logging
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
def cum_p_nom_max(net, tech, country=None):
|
|
carrier_b = net.generators.carrier == tech
|
|
|
|
generators = pd.DataFrame(
|
|
dict(
|
|
p_nom_max=net.generators.loc[carrier_b, "p_nom_max"],
|
|
p_max_pu=net.generators_t.p_max_pu.loc[:, carrier_b].mean(),
|
|
country=net.generators.loc[carrier_b, "bus"].map(net.buses.country),
|
|
)
|
|
).sort_values("p_max_pu", ascending=False)
|
|
|
|
if country is not None:
|
|
generators = generators.loc[generators.country == country]
|
|
|
|
generators["cum_p_nom_max"] = generators["p_nom_max"].cumsum() / 1e6
|
|
|
|
return generators
|
|
|
|
|
|
if __name__ == "__main__":
|
|
if "snakemake" not in globals():
|
|
from _helpers import mock_snakemake
|
|
|
|
snakemake = mock_snakemake(
|
|
"plot_p_nom_max",
|
|
simpl="",
|
|
techs="solar,onwind,offwind-dc",
|
|
ext="png",
|
|
clusts="5,full",
|
|
country="all",
|
|
)
|
|
configure_logging(snakemake)
|
|
|
|
plot_kwds = dict(drawstyle="steps-post")
|
|
|
|
clusters = snakemake.wildcards.clusts.split(",")
|
|
techs = snakemake.wildcards.techs.split(",")
|
|
country = snakemake.wildcards.country
|
|
if country == "all":
|
|
country = None
|
|
else:
|
|
plot_kwds["marker"] = "x"
|
|
|
|
fig, axes = plt.subplots(1, len(techs))
|
|
|
|
for j, cluster in enumerate(clusters):
|
|
net = pypsa.Network(snakemake.input[j])
|
|
|
|
for i, tech in enumerate(techs):
|
|
cum_p_nom_max(net, tech, country).plot(
|
|
x="p_max_pu", y="cum_p_nom_max", label=cluster, ax=axes[i], **plot_kwds
|
|
)
|
|
|
|
for i, tech in enumerate(techs):
|
|
ax = axes[i]
|
|
ax.set_xlabel(f"Capacity factor of {tech}")
|
|
ax.set_ylabel("Cumulative installable capacity / TW")
|
|
|
|
plt.legend(title="Cluster level")
|
|
|
|
fig.savefig(snakemake.output[0], transparent=True, bbox_inches="tight")
|