remove plot_p_nom_max
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Fabian Neumann
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6e1fb8049f
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@ -24,9 +24,9 @@ ATLITE_NPROCESSES = config["atlite"].get("nprocesses", 4)
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wildcard_constraints:
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simpl="[a-zA-Z0-9]*|all",
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clusters="[0-9]+m?|all",
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ll="(v|c)([0-9\.]+|opt|all)|all",
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simpl="[a-zA-Z0-9]*",
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clusters="[0-9]+m?",
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ll="(v|c)([0-9\.]+|opt)",
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opts="[-+a-zA-Z0-9\.]*",
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sector_opts="[-+a-zA-Z0-9\.\s]*"
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@ -9,42 +9,6 @@ Plotting and Summary
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.. warning:: The corresponding code is currently under revision and has only minimal documentation.
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.. _plot_potentials:
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Rule ``plot_p_nom_max``
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==========================
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.. graphviz::
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:align: center
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digraph snakemake_dag {
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graph [bgcolor=white,
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margin=0,
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size="8,5"
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];
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node [fontname=sans,
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fontsize=10,
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penwidth=2,
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shape=box,
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style=rounded
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];
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edge [color=grey,
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penwidth=2
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];
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0 [color="0.42 0.6 0.85",
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fillcolor=gray,
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label=plot_p_nom_max,
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style=filled];
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1 [color="0.58 0.6 0.85",
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label=cluster_network];
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1 -> 0;
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}
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.. automodule:: plot_p_nom_max
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.. _summary:
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Rule ``make_summary``
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========================
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@ -128,10 +128,6 @@ series and potentials using the rule :mod:`build_renewable_profiles`.
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It can take the values ``onwind``, ``offwind-ac``, ``offwind-dc``, and ``solar`` but **not** ``hydro``
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(since hydroelectric plant profiles are created by a different rule).
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The wildcard can moreover be used to create technology specific figures and summaries.
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For instance ``{technology}`` can be used to plot regionally disaggregated potentials
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with the rule :mod:`plot_p_nom_max`.
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.. _attr:
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The ``{attr}`` wildcard
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@ -148,7 +144,7 @@ The ``{ext}`` wildcard
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======================
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The ``{ext}`` wildcard specifies the file type of the figures the
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rule :mod:`plot_network`, :mod:`plot_summary`, and :mod:`plot_p_nom_max` produce.
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rule :mod:`plot_network` and :mod:`plot_summary` produce.
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Typical examples are ``pdf`` and ``png``. The list of supported file
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formats depends on the used backend. To query the supported file types on your system, issue:
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@ -1,91 +0,0 @@
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# -*- coding: utf-8 -*-
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# SPDX-FileCopyrightText: : 2017-2023 The PyPSA-Eur Authors
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#
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# SPDX-License-Identifier: MIT
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"""
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Plots renewable installation potentials per capacity factor.
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Relevant Settings
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-----------------
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Inputs
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------
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Outputs
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-------
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Description
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-----------
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"""
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import logging
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import matplotlib.pyplot as plt
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import pandas as pd
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import pypsa
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from _helpers import configure_logging
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logger = logging.getLogger(__name__)
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def cum_p_nom_max(net, tech, country=None):
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carrier_b = net.generators.carrier == tech
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generators = pd.DataFrame(
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dict(
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p_nom_max=net.generators.loc[carrier_b, "p_nom_max"],
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p_max_pu=net.generators_t.p_max_pu.loc[:, carrier_b].mean(),
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country=net.generators.loc[carrier_b, "bus"].map(net.buses.country),
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)
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).sort_values("p_max_pu", ascending=False)
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if country is not None:
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generators = generators.loc[generators.country == country]
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generators["cum_p_nom_max"] = generators["p_nom_max"].cumsum() / 1e6
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return generators
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if __name__ == "__main__":
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if "snakemake" not in globals():
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from _helpers import mock_snakemake
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snakemake = mock_snakemake(
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"plot_p_nom_max",
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simpl="",
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techs="solar,onwind,offwind-dc",
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ext="png",
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clusts="5,full",
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country="all",
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)
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configure_logging(snakemake)
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plot_kwds = dict(drawstyle="steps-post")
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clusters = snakemake.wildcards.clusts.split(",")
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techs = snakemake.wildcards.techs.split(",")
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country = snakemake.wildcards.country
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if country == "all":
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country = None
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else:
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plot_kwds["marker"] = "x"
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fig, axes = plt.subplots(1, len(techs))
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for j, cluster in enumerate(clusters):
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net = pypsa.Network(snakemake.input[j])
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for i, tech in enumerate(techs):
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cum_p_nom_max(net, tech, country).plot(
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x="p_max_pu", y="cum_p_nom_max", label=cluster, ax=axes[i], **plot_kwds
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)
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for i, tech in enumerate(techs):
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ax = axes[i]
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ax.set_xlabel(f"Capacity factor of {tech}")
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ax.set_ylabel("Cumulative installable capacity / TW")
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plt.legend(title="Cluster level")
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fig.savefig(snakemake.output[0], transparent=True, bbox_inches="tight")
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