import numpy as np
from powersimdata.input.check import (
_check_number_hours_to_analyze,
_check_resources_are_in_grid_and_format,
)
from powersimdata.input.helpers import (
get_plant_id_for_resources_in_area,
get_storage_id_in_area,
)
from powersimdata.scenario.check import _check_scenario_is_in_analyze_state
[docs]def calculate_NLDC(scenario, resources, hours=100): # noqa: N802
"""Calculate the capacity value of a class of resources by comparing the
mean of the top N hour of absolute demand to the mean of the top N hours of
net demand. NLDC = 'Net Load Duration Curve'.
:param powersimdata.scenario.scenario.Scenario scenario: scenario instance.
:param str/list/tuple/set resources: one or more resources to analyze.
:param int hours: number of hours to analyze.
:return: (*float*) -- difference between peak demand and peak net demand.
"""
_check_scenario_is_in_analyze_state(scenario)
grid = scenario.get_grid()
resources = _check_resources_are_in_grid_and_format(resources, grid)
_check_number_hours_to_analyze(scenario, hours)
# Then calculate capacity value
total_demand = scenario.get_demand().sum(axis=1)
prev_peak = total_demand.sort_values(ascending=False).head(hours).mean()
plant_groupby = grid.plant.groupby("type")
plant_indices = sum(
[plant_groupby.get_group(r).index.tolist() for r in resources], []
)
resource_generation = scenario.get_pg()[plant_indices].sum(axis=1)
net_demand = total_demand - resource_generation
net_peak = net_demand.sort_values(ascending=False).head(hours).mean()
return prev_peak - net_peak
[docs]def calculate_net_load_peak(scenario, resources, hours=100):
"""Calculate the capacity value of a class of resources by averaging the
power generated in the top N hours of net load peak.
:param powersimdata.scenario.scenario.Scenario scenario: scenario instance.
:param str/list/tuple/set resources: one or more resources to analyze.
:param int hours: number of hours to analyze.
:return: (*float*) -- resource capacity during hours of peak net demand.
"""
_check_scenario_is_in_analyze_state(scenario)
grid = scenario.get_grid()
resources = _check_resources_are_in_grid_and_format(resources, grid)
_check_number_hours_to_analyze(scenario, hours)
# Then calculate capacity value
total_demand = scenario.get_demand().sum(axis=1)
plant_groupby = grid.plant.groupby("type")
plant_indices = sum(
[plant_groupby.get_group(r).index.tolist() for r in resources], []
)
resource_generation = scenario.get_pg()[plant_indices].sum(axis=1)
net_demand = total_demand - resource_generation
top_hours = net_demand.sort_values(ascending=False).head(hours).index
return resource_generation[top_hours].mean()
[docs]def get_capacity_by_resources(scenario, area, resources, area_type=None):
"""Get the total nameplate capacity for generator type(s) in an area
:param powersimdata.scenario.scenario.Scenario scenario: scenario instance
:param str area: one of *'loadzone'*, *'state'*, *'state_abbr'*, *'interconnect'*
*'all'*
:param str/list resources: one or a list of resources
:param str area_type: one of *'loadzone'*, *'state'*, *'state_abbr'*,
*'interconnect'*. If None, ``area`` will be searched successively into
*'state'*, *'loadzone'*, *'state abbreviation'*, *'interconnect'* and *'all'*.
:return: (*pandas.Series*) -- index: resources, column: total nameplate Pmax
capacity
"""
plant_id = get_plant_id_for_resources_in_area(
scenario, area, resources, area_type=area_type
)
grid = scenario.get_grid()
return grid.plant.loc[plant_id].groupby("type")["Pmax"].sum()
[docs]def get_storage_capacity(scenario, area, area_type=None):
"""Get total storage nameplate capacity in an area.
:param powersimdata.scenario.scenario.Scenario scenario: scenario instance
:param str area: one of *'loadzone'*, *'state'*, *'state_abbr'*, *'interconnect'*
*'all'*
:param str area_type: one of *'loadzone'*, *'state'*, *'state_abbr'*,
*'interconnect'*. If None, ``area`` will be searched successively into
*'state'*, *'loadzone'*, *'state abbreviation'*, *'interconnect'* and *'all'*
:return: (*float*) -- total storage capacity value
"""
grid = scenario.get_grid()
storage_id = get_storage_id_in_area(scenario, area, area_type)
return grid.storage["gen"].loc[storage_id].Pmax.sum()
[docs]def sum_capacity_by_type_zone(scenario):
"""Get total capacity for each generator type and load zone combination.
:param powersimdata.scenario.scenario.Scenario scenario: scenario instance.
:return: (*pandas.DataFrame*) -- index: generator type, column: load zone, value:
total capacity.
"""
grid = scenario.get_grid()
plant = grid.plant
return plant.groupby(["type", "zone_id"])["Pmax"].sum().unstack().fillna(0)
[docs]def get_capacity_factor_time_series(scenario, area, resources, area_type=None):
"""Get the hourly capacity factor of each generator fueled by resource(s) in an
area.
:param powersimdata.scenario.scenario.Scenario scenario: scenario instance
:param str area: one of *'loadzone'*, *'state'*, *'state_abbr'*, *'interconnect'*
*'all'*
:param str/list resources: one or a list of resources
:param str area_type: one of *'loadzone'*, *'state'*, *'state_abbr'*,
*'interconnect'*. If None, ``area`` will be searched successively into
*'state'*, *'loadzone'*, *'state abbreviation'*, *'interconnect'* and *'all'*
:return: (*pandas.DataFrame*) -- index: timestamps, column: plant ids,
value: capacity factors
"""
_check_scenario_is_in_analyze_state(scenario)
plant_id = get_plant_id_for_resources_in_area(
scenario, area, resources, area_type=area_type
)
pg = scenario.get_pg()[plant_id]
capacity = scenario.get_grid().plant.loc[plant_id, "Pmax"]
cf = (pg / capacity).replace(np.inf, 0).clip(0, 1)
return cf
