adjust summary and plotting
This commit is contained in:
lisazeyen
parent
20bf1cdaf5
commit
6585e2c623
@ -13,7 +13,6 @@ other metrics.
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
import pypsa
|
||||
from _helpers import override_component_attrs
|
||||
from make_summary import (
|
||||
assign_carriers,
|
||||
assign_locations,
|
||||
@ -221,31 +220,43 @@ def calculate_curtailment(n, label, curtailment):
|
||||
|
||||
|
||||
def calculate_energy(n, label, energy):
|
||||
investments = n.investment_periods
|
||||
cols = pd.MultiIndex.from_product(
|
||||
[
|
||||
energy.columns.levels[0],
|
||||
energy.columns.levels[1],
|
||||
energy.columns.levels[2],
|
||||
investments,
|
||||
],
|
||||
names=energy.columns.names[:3] + ["year"],
|
||||
)
|
||||
energy = energy.reindex(cols, axis=1)
|
||||
|
||||
for c in n.iterate_components(n.one_port_components | n.branch_components):
|
||||
if c.name in n.one_port_components:
|
||||
c_energies = (
|
||||
c.pnl.p.multiply(n.snapshot_weightings, axis=0)
|
||||
.sum()
|
||||
c.pnl.p.multiply(n.snapshot_weightings.generators, axis=0)
|
||||
.groupby(level=0).sum()
|
||||
.multiply(c.df.sign)
|
||||
.groupby(c.df.carrier)
|
||||
.groupby(c.df.carrier, axis=1)
|
||||
.sum()
|
||||
)
|
||||
else:
|
||||
c_energies = pd.Series(0.0, c.df.carrier.unique())
|
||||
c_energies = pd.DataFrame(0.0, columns=c.df.carrier.unique(), index=n.investment_periods)
|
||||
for port in [col[3:] for col in c.df.columns if col[:3] == "bus"]:
|
||||
totals = c.pnl["p" + port].multiply(n.snapshot_weightings, axis=0).sum()
|
||||
totals = c.pnl["p" + port].multiply(n.snapshot_weightings.generators, axis=0).groupby(level=0).sum()
|
||||
# remove values where bus is missing (bug in nomopyomo)
|
||||
no_bus = c.df.index[c.df["bus" + port] == ""]
|
||||
totals.loc[no_bus] = n.component_attrs[c.name].loc[
|
||||
totals[no_bus] = float(n.component_attrs[c.name].loc[
|
||||
"p" + port, "default"
|
||||
]
|
||||
c_energies -= totals.groupby(c.df.carrier).sum()
|
||||
])
|
||||
c_energies -= totals.groupby(c.df.carrier, axis=1).sum()
|
||||
|
||||
c_energies = pd.concat([c_energies], keys=[c.list_name])
|
||||
c_energies = pd.concat([c_energies.T], keys=[c.list_name])
|
||||
|
||||
energy = energy.reindex(c_energies.index.union(energy.index))
|
||||
|
||||
energy.loc[c_energies.index, label] = c_energies
|
||||
energy.loc[c_energies.index, label] = c_energies.values
|
||||
|
||||
return energy
|
||||
|
||||
@ -599,7 +610,7 @@ def calculate_co2_emissions(n, label, df):
|
||||
if emissions.empty:
|
||||
return
|
||||
|
||||
weightings = n.snapshot_weightings.mul(
|
||||
weightings = n.snapshot_weightings.generators.mul(
|
||||
n.investment_period_weightings["years"]
|
||||
.reindex(n.snapshots)
|
||||
.fillna(method="bfill")
|
||||
@ -661,11 +672,10 @@ def make_summaries(networks_dict):
|
||||
for output in outputs:
|
||||
df[output] = pd.DataFrame(columns=columns, dtype=float)
|
||||
|
||||
overrides = override_component_attrs(snakemake.input.overrides)
|
||||
for label, filename in iteritems(networks_dict):
|
||||
print(label, filename)
|
||||
try:
|
||||
n = pypsa.Network(filename, override_component_attrs=overrides)
|
||||
n = pypsa.Network(filename)
|
||||
except OSError:
|
||||
print(label, " not solved yet.")
|
||||
continue
|
||||
@ -694,7 +704,6 @@ if __name__ == "__main__":
|
||||
# Detect running outside of snakemake and mock snakemake for testing
|
||||
if "snakemake" not in globals():
|
||||
from _helpers import mock_snakemake
|
||||
|
||||
snakemake = mock_snakemake("make_summary_perfect")
|
||||
|
||||
networks_dict = {
|
||||
|
||||
@ -49,6 +49,10 @@ def rename_techs(label):
|
||||
# "H2 Fuel Cell": "hydrogen storage",
|
||||
# "H2 pipeline": "hydrogen storage",
|
||||
"battery": "battery storage",
|
||||
"H2 for industry": "H2 for industry",
|
||||
"land transport fuel cell": "land transport fuel cell",
|
||||
"land transport oil": "land transport oil",
|
||||
"oil shipping": "shipping oil",
|
||||
# "CC": "CC"
|
||||
}
|
||||
|
||||
@ -157,11 +161,11 @@ def plot_costs():
|
||||
df.index.difference(preferred_order)
|
||||
)
|
||||
|
||||
new_columns = df.sum().sort_values().index
|
||||
# new_columns = df.sum().sort_values().index
|
||||
|
||||
fig, ax = plt.subplots(figsize=(12, 8))
|
||||
|
||||
df.loc[new_index, new_columns].T.plot(
|
||||
df.loc[new_index].T.plot(
|
||||
kind="bar",
|
||||
ax=ax,
|
||||
stacked=True,
|
||||
@ -222,13 +226,13 @@ def plot_energy():
|
||||
df.index.difference(preferred_order)
|
||||
)
|
||||
|
||||
new_columns = df.columns.sort_values()
|
||||
# new_columns = df.columns.sort_values()
|
||||
|
||||
fig, ax = plt.subplots(figsize=(12, 8))
|
||||
|
||||
logger.debug(df.loc[new_index, new_columns])
|
||||
logger.debug(df.loc[new_index])
|
||||
|
||||
df.loc[new_index, new_columns].T.plot(
|
||||
df.loc[new_index].T.plot(
|
||||
kind="bar",
|
||||
ax=ax,
|
||||
stacked=True,
|
||||
@ -272,7 +276,7 @@ def plot_balances():
|
||||
i for i in balances_df.index.levels[0] if i not in co2_carriers
|
||||
]
|
||||
|
||||
fig, ax = plt.subplots(figsize=(12, 8))
|
||||
|
||||
|
||||
for k, v in balances.items():
|
||||
df = balances_df.loc[v]
|
||||
@ -317,6 +321,8 @@ def plot_balances():
|
||||
)
|
||||
|
||||
new_columns = df.columns.sort_values()
|
||||
|
||||
fig, ax = plt.subplots(figsize=(12, 8))
|
||||
|
||||
df.loc[new_index, new_columns].T.plot(
|
||||
kind="bar",
|
||||
@ -544,7 +550,7 @@ def plot_carbon_budget_distribution(input_eurostat):
|
||||
path_cb_plot = "results/" + snakemake.params.RDIR + "/graphs/"
|
||||
plt.savefig(path_cb_plot + "carbon_budget_plot.pdf", dpi=300)
|
||||
|
||||
|
||||
#%%
|
||||
if __name__ == "__main__":
|
||||
if "snakemake" not in globals():
|
||||
from _helpers import mock_snakemake
|
||||
|
||||
Loading…
Reference in New Issue
Block a user