import matplotlib.pyplot as plt
import pandas as pd
from powersimdata.input.check import (
_check_resources_are_in_grid_and_format,
_check_resources_are_renewable_and_format,
)
from powersimdata.scenario.check import _check_scenario_is_in_analyze_state
from postreise.analyze.generation.summarize import (
sum_generation_by_state,
sum_generation_by_type_zone,
)
[docs]def plot_bar_renewable_max_profile_actual(
scenario,
interconnect,
gen_type,
percentage=False,
show_as_state=True,
fontsize=15,
plot_show=True,
):
"""Generate for a given scenario the bar plot of total capacity vs. available energy
vs. actual generation for a specific renewable resource in an interconnection.
:param powersimdata.scenario.scenario.Scenario scenario: scenario instance.
:param str interconnect: the interconnection name of interest.
:param str gen_type: renewable resource.
:param bool percentage: show bars in percentage of total capacity or not,
defaults to False.
:param bool show_as_state: each bar represents a state within the given
interconnection or not, defaults to True, if not, each bar will represent a
loadzone instead.
:param int/float fontsize: font size of the texts shown on the plot.
:param plot_show: show the plot or not, defaults to True.
:return: (*matplotlib.axes.Axes*) -- axes object of the plot.
:raises TypeError:
if ``interconnect`` and ``gen_type`` are not str
if ``fontsize`` is not a int or a float
:raises ValueError: if ``interconnect`` is not valid
"""
_check_scenario_is_in_analyze_state(scenario)
if not isinstance(interconnect, str):
raise TypeError("interconnect must be a str")
if not isinstance(gen_type, str):
raise TypeError("gen_type must be a str")
if not isinstance(fontsize, (int, float)):
raise TypeError("fontsize must be either a int or a float")
grid = scenario.get_grid()
mi = grid.model_immutables
_check_resources_are_in_grid_and_format(gen_type, grid)
_check_resources_are_renewable_and_format(gen_type, mi=mi)
plant = grid.plant[grid.plant.type == gen_type]
if interconnect not in mi.zones["interconnect"]:
raise ValueError(
f"interconnect must be one of {sorted(mi.zones['interconnect'])}"
)
if (
len(
mi.zones["interconnect2abv"][interconnect]
- mi.zones["interconnect2abv"][scenario.info["interconnect"]]
)
!= 0
):
raise ValueError("interconnect is incompatible with scenario's interconnect")
if "wind" in gen_type:
profile = scenario.get_wind().sum()
else:
profile = scenario.get_solar().sum()
hour_num = (
pd.Timestamp(scenario.info["end_date"])
- pd.Timestamp(scenario.info["start_date"])
).total_seconds() / 3600 + 1
if show_as_state:
zone_list = [
mi.zones["abv2state"][abv]
for abv in mi.zones["interconnect2abv"][interconnect]
]
group_criteria = plant.zone_name.map(mi.zones["loadzone2state"])
profile_gen = profile.groupby(group_criteria).sum().rename("profile")
total_capacity = plant.groupby(group_criteria)["Pmax"].sum() * hour_num
actual_gen = sum_generation_by_state(scenario)[gen_type] * 1000
else:
zone_list = list(mi.zones["interconnect2loadzone"][interconnect])
profile_gen = profile.groupby(plant.zone_name).sum().rename("profile")
total_capacity = plant.groupby("zone_name")["Pmax"].sum() * hour_num
actual_gen = (
sum_generation_by_type_zone(scenario)
.rename(columns=grid.id2zone)
.T[gen_type]
)
df = pd.concat([total_capacity, profile_gen, actual_gen], axis=1).loc[zone_list]
if percentage:
df_pct = df.copy()
df_pct["Pmax"] = df["Pmax"].apply(lambda x: 1 if x > 0 else 0)
df_pct["profile"] = df["profile"] / df["Pmax"]
df_pct[gen_type] = df[gen_type] / df["Pmax"]
df = df_pct
df.sort_index(inplace=True)
width = 0.8
fig, ax = plt.subplots(figsize=[30, 15])
df["Pmax"].plot(kind="bar", width=width, color="yellowgreen", ax=ax)
df["profile"].plot(kind="bar", width=width * 0.7, color="steelblue", ax=ax)
df[gen_type].plot(kind="bar", width=width * 0.4, color="firebrick", ax=ax)
ax.legend(
["Total Capacity", "Available Energy", "Actual Generation"],
bbox_to_anchor=(0.5, 0.95),
loc="lower center",
ncol=3,
fontsize=fontsize,
)
ax.grid()
if percentage:
ax.set_title(f"{gen_type.capitalize()} Curtailment %")
else:
ax.set_title(f"{gen_type.capitalize()} Curtailment MWh")
for item in (
[ax.title, ax.xaxis.label, ax.yaxis.label]
+ ax.get_xticklabels()
+ ax.get_yticklabels()
):
item.set_fontsize(fontsize)
if plot_show:
plt.show()
return ax
