def test_check_areas_are_in_grid_and_format_argument_value(mock_grid):
arg = (
({"county": "Kentucky"}, mock_grid),
({"state": "California"}, mock_grid),
({"loadzone": "Texas"}, mock_grid),
({"state": "El Paso"}, mock_grid),
({"interconnect": "Nebraska"}, mock_grid),
)
for a in arg:
with pytest.raises(ValueError):
_check_areas_are_in_grid_and_format(a[0], a[1])
def calculate_curtailment_time_series_by_resources_and_areas(
scenario, areas=None, resources=None):
"""Calculate hourly curtailment of each generator fueled by resources and located
in area(s).
:param powersimdata.scenario.scenario.Scenario scenario: scenario instance.
:param str/tuple/list/set resources: names of resources. Default is all renewable
resources.
:param dict areas: keys are area types ('*loadzone*', '*state*' or
'*interconnect*'), values are a list of areas. Default is the scenario
interconnect(s).
:return: (*dict*) -- keys are areas, values are dictionaries whose keys are
resources and values are data frames indexed by (timestamp, plant id).
"""
curtailment = calculate_curtailment_time_series(scenario)
grid = scenario.state.get_grid()
areas = (_check_areas_are_in_grid_and_format(areas, grid)
if areas is not None else {
"interconnect": grid.interconnect
})
if resources is None:
resources = grid.model_immutables.plants[
"renewable_resources"].intersection(set(grid.plant.type))
else:
resources = _check_resources_are_renewable_and_format(
resources, grid_model=scenario.info["grid_model"])
curtailment_by_resources_and_areas = (
decompose_plant_data_frame_into_resources_and_areas(
curtailment, resources, areas, grid))
return curtailment_by_resources_and_areas
def decompose_plant_data_frame_into_areas(df, areas, grid):
"""Take a plant-column data frame and decompose it into plant-column data frames
for areas.
:param pandas.DataFrame df: data frame, columns are plant id in grid.
:param dict areas: areas to use for decomposition. Keys are area types
('*loadzone*', '*state*', or '*interconnect*'), values are
str/list/tuple/set of areas.
:param powersimdata.input.grid.Grid grid: Grid instance.
:return: (*dict*) -- keys are areas, values are plant-column data frames.
"""
_check_data_frame(df, "PG")
plant_id = set(df.columns)
_check_plants_are_in_grid(plant_id, grid)
areas = _check_areas_are_in_grid_and_format(areas, grid)
df_areas = {}
for k, v in areas.items():
if k == "interconnect":
for i in v:
name = "%s interconnect" % " - ".join(i.split("_"))
df_areas[name] = df[get_plant_id_in_interconnects(i, grid)
& plant_id]
elif k == "state":
for s in v:
df_areas[s] = df[get_plant_id_in_states(s, grid) & plant_id]
elif k == "loadzone":
for l in v:
df_areas[l] = df[get_plant_id_in_loadzones(l, grid) & plant_id]
return df_areas
def get_plant_id_in_interconnects(interconnects, grid):
"""Get plant id for plants in interconnect(s).
:param str/list/tuple/set interconnects: name of interconnect(s).
:param powersimdata.input.grid.Grid grid: Grid instance.
:return: (*set*) -- list of plant id
"""
areas = _check_areas_are_in_grid_and_format(
{"interconnect": interconnects}, grid)
return set.union(*(set(grid.plant.groupby("interconnect").groups[i])
for i in areas["interconnect"]))
def get_plant_id_in_loadzones(loadzones, grid):
"""Get plant id for plants in loadzone(s).
:param str/list/tuple/set loadzones: name of load zone(s).
:param powersimdata.input.grid.Grid grid: Grid instance.
:return: (*set*) -- list of plant id.
"""
areas = _check_areas_are_in_grid_and_format({"loadzone": loadzones}, grid)
plant = grid.plant
plant_id = plant[(plant.zone_name.isin(areas["loadzone"]))].index
return set(plant_id)
def test_check_areas_are_in_grid_and_format(mock_grid):
assert _check_areas_are_in_grid_and_format(
{
"state": {"Washington", "Kentucky", "NE", "TX", "WA"},
"loadzone": ["Washington", "East", "El Paso", "Bay Area"],
"interconnect": "Texas",
},
mock_grid,
) == {
"interconnect": {"Texas"},
"state": {"Washington", "Kentucky", "Nebraska", "Texas"},
"loadzone": {"Washington", "East", "El Paso", "Bay Area"},
}
def get_plant_id_in_states(states, grid):
"""Get plant id for plants in state(s).
:param str/list/tuple/set states: states(s) name or abbreviation(s).
:param powersimdata.input.grid.Grid grid: Grid instance.
:return: (*set*) -- list of plant id.
"""
areas = _check_areas_are_in_grid_and_format({"state": states}, grid)
loadzones = set.union(*(grid.model_immutables.zones["state2loadzone"][i]
for i in areas["state"]))
plant = grid.plant
plant_id = plant[(plant.zone_name.isin(loadzones))].index
return set(plant_id)
def get_plant_id_in_interconnects(interconnects, grid):
"""Get plant id for plants in interconnect(s).
:param str/list/tuple/set interconnects: name of interconnect(s).
:param powersimdata.input.grid.Grid grid: Grid instance.
:return: (*set*) -- list of plant id
"""
areas = _check_areas_are_in_grid_and_format({"interconnect": interconnects}, grid)
loadzones = set.union(
*(
grid.model_immutables.zones["interconnect2loadzone"][i]
for i in areas["interconnect"]
)
)
plant = grid.plant
plant_id = plant[(plant.zone_name.isin(loadzones))].index
return set(plant_id)
def calculate_curtailment_time_series_by_areas(scenario, areas=None):
"""Calculate hourly curtailment by area(s).
:param powersimdata.scenario.scenario.Scenario scenario: scenario instance.
:param dict areas: keys are area types ('*loadzone*', '*state*' or
'*interconnect*'), values are a list of areas. Default is the interconnect of
the scenario. Default is the scenario interconnect.
:return: (*dict*) -- keys are areas, values are data frames indexed by
(datetime, plant id).
"""
curtailment = calculate_curtailment_time_series(scenario)
grid = scenario.state.get_grid()
areas = (_check_areas_are_in_grid_and_format(areas, grid)
if areas is not None else {
"interconnect": grid.interconnect
})
curtailment_by_areas = decompose_plant_data_frame_into_areas(
curtailment, areas, grid)
return curtailment_by_areas
def test_check_areas_are_in_grid_and_format_argument_type(mock_grid):
arg = (({"Texas", "El Paso"}, mock_grid), ({123: "Nebraska"}, mock_grid))
for a in arg:
with pytest.raises(TypeError):
_check_areas_are_in_grid_and_format(a[0], a[1])