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@ClaraBuettner
ClaraBuettner committed Sep 19, 2023
1 parent 0256a3f commit ad5f9cc
Showing 1 changed file with 81 additions and 44 deletions.
125 changes: 81 additions & 44 deletions etrago/tools/plot.py
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Original file line number Diff line number Diff line change
Expand Up @@ -117,7 +117,6 @@ def plot_osm(x, y, zoom, alpha=0.4):


def coloring():

colors = {
"load": "red",
"DC": "blue",
Expand Down Expand Up @@ -219,6 +218,7 @@ def plot_line_loading_diff(networkA, networkB, timestep=0, osm=False):
set_epsg_network(networkA)
set_epsg_network(networkB)
plot_osm(osm["x"], osm["y"], osm["zoom"])

# new colormap to make sure 0% difference has the same color in every plot
def shiftedColorMap(
cmap, start=0, midpoint=0.5, stop=1.0, name="shiftedcmap"
Expand Down Expand Up @@ -1224,7 +1224,6 @@ def storage_p_soc(network, mean="1H", filename=None):
network.storage_units.p_nom_opt[sbatt].sum() > 1
and network.storage_units.p_nom_opt[shydr].sum() < 1
):

(
network.storage_units_t.p[sbatt].resample(mean).mean().sum(axis=1)
/ network.storage_units.p_nom_opt[sbatt].sum()
Expand Down Expand Up @@ -1449,7 +1448,6 @@ def calc_ac_loading(network, timesteps):
)

if not network.lines_t.q0.empty:

loading_lines = (
loading_lines**2
+ mul_weighting(network, network.lines_t.q0)
Expand Down Expand Up @@ -1490,7 +1488,6 @@ def calc_dc_loading(network, timesteps):
& (network.links.length == row["length"])
]
).empty:

l = network.links.index[
(network.links.bus0 == row["bus1"])
& (network.links.bus1 == row["bus0"])
Expand Down Expand Up @@ -1608,7 +1605,6 @@ def calc_network_expansion(network, method="abs", ext_min=0.1):
network.links.p_nom_opt[i] = linked.p_nom_opt.values[0]

if method == "rel":

extension_lines = (
100
* (network.lines.s_nom_opt - network.lines.s_nom_min)
Expand Down Expand Up @@ -1668,6 +1664,7 @@ def plot_background_grid(network, ax):
color_geomap=True,
)


def demand_side_management(self, buses, snapshots, agg="5h", used=False):
"""Calculate shifting potential of demand side management
Expand Down Expand Up @@ -2051,7 +2048,6 @@ def flexibility_usage(
)

elif flexibility == "battery":

df = pd.DataFrame(index=self.network.snapshots[snapshots])

su = self.network.storage_units[
Expand Down Expand Up @@ -2105,7 +2101,9 @@ def flexibility_usage(
fig_e.savefig(pre_path + f"stored_e_{flexibility}")


def plot_carrier(network, carrier_links=["AC"], carrier_buses=["AC"], cartopy=True):
def plot_carrier(
network, carrier_links=["AC"], carrier_buses=["AC"], cartopy=True
):
"""
Parameters
----------
Expand Down Expand Up @@ -2138,13 +2136,11 @@ def plot_carrier(network, carrier_links=["AC"], carrier_buses=["AC"], cartopy=Tr
link_width = pd.Series(index=network.links.index, data=2)

if len(carrier_links) > 0:

link_width.loc[~network.links.carrier.isin(carrier_links)] = 0

bus_sizes = pd.Series(index=network.buses.index, data=0.0005)

if len(carrier_buses) > 0:

bus_sizes.loc[~network.buses.carrier.isin(carrier_buses)] = 0

link_colors = network.links.carrier.map(colors)
Expand Down Expand Up @@ -3259,7 +3255,7 @@ def plot_heat_summary(self, t_resolution="20H", stacked=True, save_path=False):
data.resample(t_resolution).mean().plot(
ax=ax, label=i, legend=True
)

heat_store_dispatch_hb.resample(t_resolution).mean().plot.line(
ax=ax,
legend=True,
Expand All @@ -3279,6 +3275,7 @@ def plot_heat_summary(self, t_resolution="20H", stacked=True, save_path=False):
if save_path:
plt.savefig(save_path, dpi=300)


def shifted_energy(self, carrier, buses):
"""Calulate shifted energy for a specific carrier
Expand Down Expand Up @@ -3337,6 +3334,7 @@ def shifted_energy(self, carrier, buses):
shifted = supply - demand
return shifted


def flexibility_duration_curve(etrago, etrago_lowflex, filename=None):
"""Plot duration curves of flexibility options
Expand All @@ -3356,57 +3354,96 @@ def flexibility_duration_curve(etrago, etrago_lowflex, filename=None):
"""
colors = coloring()

value = 'p'
value = "p"

df = pd.DataFrame()

dsm_stores = etrago.network.stores[etrago.network.stores.carrier.str.contains('dsm')]
df['dsm_positive'] = etrago.network.stores_t[value][dsm_stores.index].clip(lower=0).sum(axis=1)
df['dsm_negative'] = etrago.network.stores_t[value][dsm_stores.index].clip(upper=0).sum(axis=1)

dsm_stores = etrago.network.stores[
etrago.network.stores.carrier.str.contains("dsm")
]
df["dsm_positive"] = (
etrago.network.stores_t[value][dsm_stores.index]
.clip(lower=0)
.sum(axis=1)
)
df["dsm_negative"] = (
etrago.network.stores_t[value][dsm_stores.index]
.clip(upper=0)
.sum(axis=1)
)

emob_static = etrago_lowflex.network.loads[
etrago_lowflex.network.loads.carrier=='land transport EV']

etrago_lowflex.network.loads.carrier == "land transport EV"
]

emob_static_t = etrago_lowflex.network.loads_t.p_set[emob_static.index]

emob_static_t = emob_static_t.loc[:, emob_static.index]

emob_static_t.columns = emob_static.bus.values

emob_flex = etrago.network.links[etrago.network.links.carrier.str.contains('BEV')]


emob_flex = etrago.network.links[
etrago.network.links.carrier.str.contains("BEV")
]

emob_flex_t = etrago.network.links_t.p0[emob_flex.index]

emob_flex_t = emob_flex_t.loc[:, emob_flex.index]

emob_flex_t.columns = emob_flex.bus0.values

emob_flex_t - emob_static_t
df['BEV charger_positive'] = (emob_flex_t - emob_static_t).clip(lower=0).sum(axis=1)
df['BEV charger_negative'] = (emob_flex_t - emob_static_t).clip(upper=0).sum(axis=1)
df["BEV charger_positive"] = (
(emob_flex_t - emob_static_t).clip(lower=0).sum(axis=1)
)
df["BEV charger_negative"] = (
(emob_flex_t - emob_static_t).clip(upper=0).sum(axis=1)
)

heat_stores = etrago.network.stores[etrago.network.stores.carrier.str.contains('heat')]
df['heat_positive'] = etrago.network.stores_t[value][heat_stores.index].clip(lower=0).sum(axis=1)
df['heat_negative'] = etrago.network.stores_t[value][heat_stores.index].clip(upper=0).sum(axis=1)
heat_stores = etrago.network.stores[
etrago.network.stores.carrier.str.contains("heat")
]
df["heat_positive"] = (
etrago.network.stores_t[value][heat_stores.index]
.clip(lower=0)
.sum(axis=1)
)
df["heat_negative"] = (
etrago.network.stores_t[value][heat_stores.index]
.clip(upper=0)
.sum(axis=1)
)

h2_stores = etrago.network.stores[etrago.network.stores.carrier.str.contains('H2')]
df['H2_positive'] = etrago.network.stores_t[value][h2_stores.index].clip(lower=0).sum(axis=1)
df['H2_negative'] = etrago.network.stores_t[value][h2_stores.index].clip(upper=0).sum(axis=1)
h2_stores = etrago.network.stores[
etrago.network.stores.carrier.str.contains("H2")
]
df["H2_positive"] = (
etrago.network.stores_t[value][h2_stores.index]
.clip(lower=0)
.sum(axis=1)
)
df["H2_negative"] = (
etrago.network.stores_t[value][h2_stores.index]
.clip(upper=0)
.sum(axis=1)
)

fig, ax = plt.subplots(figsize=(15, 8))
for c in df.columns:
result = pd.Series(dtype=float)
color = colors[c.split('_')[0]]
for p in range(0,100):
result[
p*df[c].abs().max()
*np.sign(df[c].sum())/100] = (
df[c][df[c].abs()>p*0.01*df[c].abs().max()].size / df[c].size) *100

data_to_plot = pd.DataFrame(index = result.values, data = result.index*1e-3)
data_to_plot.columns = [c.split('_')[0]]
data_to_plot.plot(ax=ax, color = color, linewidth=3.0)
plt.axhline(y = 0.0, color = 'grey', linestyle = 'dotted')
color = colors[c.split("_")[0]]
for p in range(0, 100):
result[p * df[c].abs().max() * np.sign(df[c].sum()) / 100] = (
df[c][df[c].abs() > p * 0.01 * df[c].abs().max()].size
/ df[c].size
) * 100

data_to_plot = pd.DataFrame(
index=result.values, data=result.index * 1e-3
)
data_to_plot.columns = [c.split("_")[0]]
data_to_plot.plot(ax=ax, color=color, linewidth=3.0)
plt.axhline(y=0.0, color="grey", linestyle="dotted")
ax.set_xlim(0, 80)
ax.set_xlabel("time in %")
ax.set_ylabel("flexibility usage in GW")
Expand Down

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