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Merge fa49442 into eb6f9b7
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@Flix6x
Flix6x committed May 25, 2023
2 parents eb6f9b7 + fa49442 commit 89892ee
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Showing 2 changed files with 41 additions and 42 deletions.
77 changes: 38 additions & 39 deletions flexmeasures/data/models/planning/storage.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -41,10 +41,8 @@ def compute(self, skip_validation: bool = False) -> pd.Series | None:
"""Schedule a battery or Charge Point based directly on the latest beliefs regarding market prices within the specified time window.
For the resulting consumption schedule, consumption is defined as positive values.
Args:
skip_validation: bool, default=False
whether to skip validation of constraints from data
:param skip_validation: If True, skip validation of constraints specified in the data.
:returns: The computed schedule.
"""
if not self.config_deserialized:
self.deserialize_config()
Expand Down Expand Up @@ -328,7 +326,7 @@ def get_min_max_targets(

def get_min_max_soc_on_sensor(
self, adjust_unit: bool = False, deserialized_names: bool = True
) -> tuple[float | None]:
) -> tuple[float | None, float | None]:
soc_min_sensor = self.sensor.get_attribute("min_soc_in_mwh", None)
soc_max_sensor = self.sensor.get_attribute("max_soc_in_mwh", None)
soc_unit_label = "soc_unit" if deserialized_names else "soc-unit"
Expand Down Expand Up @@ -440,22 +438,21 @@ def add_storage_constraints(
soc_max: float,
soc_min: float,
) -> pd.DataFrame:
"""_summary_
Args:
storage_device_constraints (pd.DataFrame): _description_
start (datetime): start of the schedule.
end (datetime): end of the schedule.
resolution (timedelta): timedelta used to resample the forecasts to the resolution of the schedule.
soc_at_start (float): state of charge at the start time.
soc_targets (List[Dict[str, datetime | float]] | pd.Series | None): list of (time : value) pairs
soc_maxima (List[Dict[str, datetime | float]] | pd.Series | None): _description_
soc_minima (List[Dict[str, datetime | float]] | pd.Series | None): _description_
soc_max (float): _description_
soc_min (float): _description_
Returns:
pd.DataFrame: _description_
"""Collect all constraints for a given storage device in a DataFrame that the device_scheduler can interpret.
:param storage_device_constraints: Empty frame without constraints (columns) for a storage device,
but already defining each time step (index).
:param start: Start of the schedule.
:param end: End of the schedule.
:param resolution: Timedelta used to resample the forecasts to the resolution of the schedule.
:param soc_at_start: State of charge at the start time.
:param soc_targets: Exact targets for the state of charge at each time.
:param soc_maxima: Maximum state of charge at each time.
:param soc_minima: Minimum state of charge at each time.
:param soc_max: Maximum state of charge at all times.
:param soc_min: Minimum state of charge at all times.
:returns: Constraints (columns) for a storage device, at each time step (index).
See device_scheduler for possible column names.
"""

if soc_targets is not None:
Expand Down Expand Up @@ -511,11 +508,11 @@ def validate_storage_constraints(
min_soc: float,
max_soc: float,
resolution: timedelta,
) -> list:
) -> list[dict]:
"""Check that the storage constraints are fulfilled, e.g min <= equals <= max.
A. Global validation
A.1) min <= min_soc
A.1) min >= min_soc
A.2) max <= max_soc
B. Validation in the same time frame
B.1) min <= max
Expand All @@ -529,10 +526,12 @@ def validate_storage_constraints(
C.5) condition equals(t) - max(t-1) <= `derivative max`(t)
C.6) `derivative min`(t) <= equals(t) - min(t-1)
Args:
storage_constraints: pd.DataFrame
dataframe containing the constraints of a storage device
:param storage_constraints: dataframe containing the constraints of a storage device
:param soc_at_start: State of charge at the start time.
:param min_soc: Minimum state of charge at all times.
:param max_soc: Maximum state of charge at all times.
:param resolution: Constant duration between the start of each time step.
:returns: List of constraint violations, specifying their time, constraint and violation.
"""

constraint_violations = []
Expand All @@ -542,7 +541,7 @@ def validate_storage_constraints(
########################
min_soc = (min_soc - soc_at_start) * timedelta(hours=1) / resolution

# 1) min <= min_soc
# 1) min >= min_soc
mask = ~(storage_constraints["min"] >= min_soc)
time_condition_fails = storage_constraints.index[mask]

Expand All @@ -552,8 +551,8 @@ def validate_storage_constraints(
constraint_violations.append(
dict(
dt=dt.to_pydatetime(),
condition="min <= min_soc",
violation=f"min [{value_min}] <= min_soc [{min_soc}]",
condition="min >= min_soc",
violation=f"min [{value_min}] >= min_soc [{min_soc}]",
)
)

Expand Down Expand Up @@ -594,7 +593,7 @@ def validate_storage_constraints(
)
)

# 2) min <= equals
# 2) equals >= min
mask = ~(storage_constraints["equals"] >= storage_constraints["min"])
mask = mask & ~storage_constraints["equals"].isna()
time_condition_fails = storage_constraints.index[mask]
Expand All @@ -606,7 +605,7 @@ def validate_storage_constraints(
constraint_violations.append(
dict(
dt=dt.to_pydatetime(),
condition="min <= equals",
condition="equals >= min",
violation=f"equal [{value_equals}] >= min [{value_min}]",
)
)
Expand Down Expand Up @@ -656,7 +655,7 @@ def validate_storage_constraints(
dict(
dt=dt.to_pydatetime(),
condition="equals(t) - equals(t-1) <= `derivative max`(t)",
violation=f"equals(t) [{value_equals}] - equals(t-1) [{value_equals_previous}] <= max [{value_derivative_max}]",
violation=f"equals(t) [{value_equals}] - equals(t-1) [{value_equals_previous}] <= `derivative max`(t) [{value_derivative_max}]",
)
)

Expand Down Expand Up @@ -695,13 +694,10 @@ def validate_storage_constraints(
min_extended[storage_constraints.index[0] - resolution] = min_soc
min_extended = min_extended.sort_index()

# 3) min(t) - max(t-1) <= `derivative max`(t)
delta_min_max = min_extended - max_extended.shift(1)
delta_min_max = delta_min_max[1:]

delta_max_min = max_extended - min_extended.shift(1)
delta_max_min = delta_max_min[1:]

# 3) min(t) - max(t-1) <= `derivative max`(t)
condition3 = delta_min_max <= storage_constraints["derivative max"] * factor_w_wh
mask = ~condition3
time_condition_fails = storage_constraints.index[mask]
Expand All @@ -715,11 +711,14 @@ def validate_storage_constraints(
dict(
dt=dt.to_pydatetime(),
condition="min(t) - max(t-1) <= `derivative max`(t)",
violation=f"min(t) [{value_min}] <= max(t-1) [{value_max_previous}] + `derivative max` [{value_derivative_max}]",
violation=f"min(t) [{value_min}] - max(t-1) [{value_max_previous}] <= `derivative max`(t) [{value_derivative_max}]",
)
)

# 4) max(t) - min(t-1) >= `derivative min`(t)
delta_max_min = max_extended - min_extended.shift(1)
delta_max_min = delta_max_min[1:]

condition4 = delta_max_min >= storage_constraints["derivative min"] * factor_w_wh
mask = ~condition4
time_condition_fails = storage_constraints.index[mask]
Expand All @@ -733,7 +732,7 @@ def validate_storage_constraints(
dict(
dt=dt.to_pydatetime(),
condition="max(t) - min(t-1) >= `derivative min`",
violation=f"max(t) [{value_max}] - min(t-1) [{value_min_previous}]<= `derivative min` [{value_derivative_min}]",
violation=f"max(t) [{value_max}] - min(t-1) [{value_min_previous}] >= `derivative min`(t) [{value_derivative_min}]",
)
)

Expand Down
6 changes: 3 additions & 3 deletions flexmeasures/data/models/planning/tests/test_solver.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -607,9 +607,9 @@ def test_add_storage_constraints(
"value_min1, value_equals1, value_max1, value_min2, value_equals2, value_max2, expected_constraint_type_violations",
[
(1, np.nan, 9, 2, np.nan, 20, ["max <= max_soc"]),
(-1, np.nan, 9, 1, np.nan, 9, ["min <= min_soc"]),
(-1, np.nan, 9, 1, np.nan, 9, ["min >= min_soc"]),
(1, 10, 9, 1, np.nan, 9, ["equals <= max"]),
(1, 0, 9, 1, np.nan, 9, ["min <= equals"]),
(1, 0, 9, 1, np.nan, 9, ["equals >= min"]),
(
1,
np.nan,
Expand All @@ -619,7 +619,7 @@ def test_add_storage_constraints(
1,
["min <= max"],
),
(9, 5, 1, 1, np.nan, 9, ["min <= equals", "equals <= max", "min <= max"]),
(9, 5, 1, 1, np.nan, 9, ["equals >= min", "equals <= max", "min <= max"]),
(1, np.nan, 9, 1, np.nan, 9, []), # same interval, should not fail
(1, np.nan, 9, 3, np.nan, 7, []), # should not fail, containing interval
(1, np.nan, 3, 3, np.nan, 5, []), # difference = 0 < 1, should not fail
Expand Down

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