182 lines
4.3 KiB
Python
182 lines
4.3 KiB
Python
# SPDX-FileCopyrightText: : 2017-2022 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 energy and cost summaries for solved networks.
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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 os
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import logging
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from _helpers import configure_logging
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import pandas as pd
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import matplotlib.pyplot as plt
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logger = logging.getLogger(__name__)
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def rename_techs(label):
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if "H2" in label:
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label = "hydrogen storage"
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elif label == "solar":
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label = "solar PV"
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elif label == "offwind-ac":
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label = "offshore wind ac"
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elif label == "offwind-dc":
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label = "offshore wind dc"
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elif label == "onwind":
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label = "onshore wind"
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elif label == "ror":
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label = "hydroelectricity"
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elif label == "hydro":
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label = "hydroelectricity"
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elif label == "PHS":
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label = "hydroelectricity"
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elif "battery" in label:
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label = "battery storage"
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return label
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preferred_order = pd.Index(["transmission lines","hydroelectricity","hydro reservoir","run of river","pumped hydro storage","onshore wind","offshore wind ac", "offshore wind dc","solar PV","solar thermal","OCGT","hydrogen storage","battery storage"])
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def plot_costs(infn, config, fn=None):
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## For now ignore the simpl header
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cost_df = pd.read_csv(infn,index_col=list(range(3)),header=[1,2,3])
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df = cost_df.groupby(cost_df.index.get_level_values(2)).sum()
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#convert to billions
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df = df/1e9
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df = df.groupby(df.index.map(rename_techs)).sum()
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to_drop = df.index[df.max(axis=1) < config['plotting']['costs_threshold']]
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print("dropping")
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print(df.loc[to_drop])
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df = df.drop(to_drop)
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print(df.sum())
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new_index = (preferred_order&df.index).append(df.index.difference(preferred_order))
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new_columns = df.sum().sort_values().index
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fig, ax = plt.subplots()
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fig.set_size_inches((12,8))
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df.loc[new_index,new_columns].T.plot(kind="bar",ax=ax,stacked=True,color=[config['plotting']['tech_colors'][i] for i in new_index])
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handles,labels = ax.get_legend_handles_labels()
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handles.reverse()
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labels.reverse()
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ax.set_ylim([0,config['plotting']['costs_max']])
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ax.set_ylabel("System Cost [EUR billion per year]")
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ax.set_xlabel("")
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ax.grid(axis="y")
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ax.legend(handles,labels,ncol=4,loc="upper left")
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fig.tight_layout()
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if fn is not None:
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fig.savefig(fn, transparent=True)
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def plot_energy(infn, config, fn=None):
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energy_df = pd.read_csv(infn, index_col=list(range(2)),header=[1,2,3])
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df = energy_df.groupby(energy_df.index.get_level_values(1)).sum()
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#convert MWh to TWh
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df = df/1e6
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df = df.groupby(df.index.map(rename_techs)).sum()
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to_drop = df.index[df.abs().max(axis=1) < config['plotting']['energy_threshold']]
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print("dropping")
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print(df.loc[to_drop])
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df = df.drop(to_drop)
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print(df.sum())
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new_index = (preferred_order&df.index).append(df.index.difference(preferred_order))
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new_columns = df.columns.sort_values()
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fig, ax = plt.subplots()
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fig.set_size_inches((12,8))
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df.loc[new_index,new_columns].T.plot(kind="bar",ax=ax,stacked=True,color=[config['plotting']['tech_colors'][i] for i in new_index])
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handles,labels = ax.get_legend_handles_labels()
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handles.reverse()
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labels.reverse()
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ax.set_ylim([config['plotting']['energy_min'], config['plotting']['energy_max']])
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ax.set_ylabel("Energy [TWh/a]")
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ax.set_xlabel("")
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ax.grid(axis="y")
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ax.legend(handles,labels,ncol=4,loc="upper left")
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fig.tight_layout()
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if fn is not None:
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fig.savefig(fn, transparent=True)
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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('plot_summary', summary='energy',
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simpl='', clusters=5, ll='copt', opts='Co2L-24H',
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attr='', ext='png', country='all')
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configure_logging(snakemake)
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config = snakemake.config
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summary = snakemake.wildcards.summary
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try:
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func = globals()[f"plot_{summary}"]
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except KeyError:
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raise RuntimeError(f"plotting function for {summary} has not been defined")
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func(os.path.join(snakemake.input[0], f"{summary}.csv"), config, snakemake.output[0])
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