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feat: add function to quantify wind speed shift
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In similar way that power curve, rpm and pitch shifts are already
calculated, this change adds wind speed shift to the ops curve shift
module
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@samuelwnaylor
samuelwnaylor committed Oct 9, 2024
1 parent 5121f08 commit 847827a
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Showing 2 changed files with 76 additions and 29 deletions.
41 changes: 37 additions & 4 deletions tests/test_ops_curve_shift.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -6,13 +6,14 @@
import pytest

from wind_up.ops_curve_shift import (
CURVE_CONSTANTS,
CurveConfig,
CurveShiftInput,
CurveThresholds,
CurveTypes,
calculate_pitch_curve_shift,
calculate_power_curve_shift,
calculate_rpm_curve_shift,
calculate_wind_speed_curve_shift,
check_for_ops_curve_shift,
)

Expand Down Expand Up @@ -115,7 +116,7 @@ def test_calculate_power_curve_shift(
y_col="power",
)

if abs(expected) > CurveThresholds.POWER_CURVE.value:
if abs(expected) > CURVE_CONSTANTS[CurveTypes.POWER_CURVE.value]["warning_threshold"]:
assert "Ops Curve Shift warning" in caplog.text

np.testing.assert_almost_equal(actual=actual, desired=expected)
Expand All @@ -140,7 +141,7 @@ def test_calculate_rpm_curve_shift(
y_col="gen_rpm",
)

if abs(expected) > CurveThresholds.RPM.value:
if abs(expected) > CURVE_CONSTANTS[CurveTypes.RPM.value]["warning_threshold"]:
assert "Ops Curve Shift warning" in caplog.text

np.testing.assert_almost_equal(actual=actual, desired=expected)
Expand All @@ -165,7 +166,32 @@ def test_calculate_pitch_curve_shift(
y_col="pitch",
)

if abs(expected) > CurveThresholds.PITCH.value:
if abs(expected) > CURVE_CONSTANTS[CurveTypes.PITCH.value]["warning_threshold"]:
assert "Ops Curve Shift warning" in caplog.text

np.testing.assert_almost_equal(actual=actual, desired=expected)


@pytest.mark.parametrize(
("shift_amount", "expected"),
[
pytest.param(2.0, 0.21621621621621623, id="shift DOES exceed threshold"),
pytest.param(0.05, -0.04729729729729748, id="shift DOES NOT exceed threshold"),
],
)
def test_calculate_wind_speed_curve_shift(
shift_amount: float, expected: float, fake_power_curve_df: pd.DataFrame, caplog: pytest.LogCaptureFixture
) -> None:
with caplog.at_level(logging.WARNING):
actual = calculate_wind_speed_curve_shift(
turbine_name="anything",
pre_df=fake_power_curve_df.reset_index(),
post_df=(fake_power_curve_df + shift_amount).reset_index(),
x_col="power",
y_col="wind_speed",
)

if abs(expected) > CURVE_CONSTANTS[CurveTypes.WIND_SPEED.value]["warning_threshold"]:
assert "Ops Curve Shift warning" in caplog.text

np.testing.assert_almost_equal(actual=actual, desired=expected)
Expand Down Expand Up @@ -222,6 +248,7 @@ def test_missing_required_column(
f"{CurveTypes.POWER_CURVE.value}_shift": np.nan,
f"{CurveTypes.RPM.value}_shift": np.nan,
f"{CurveTypes.PITCH.value}_shift": np.nan,
f"{CurveTypes.WIND_SPEED.value}_shift": np.nan,
}

assert actual == expected
Expand All @@ -244,6 +271,7 @@ def test_calls_funcs_as_intended(
patch("wind_up.ops_curve_shift.calculate_power_curve_shift", return_value=np.nan) as mock_power,
patch("wind_up.ops_curve_shift.calculate_rpm_curve_shift", return_value=np.nan) as mock_rpm,
patch("wind_up.ops_curve_shift.calculate_pitch_curve_shift", return_value=np.nan) as mock_pitch,
patch("wind_up.ops_curve_shift.calculate_wind_speed_curve_shift", return_value=np.nan) as mock_ws,
patch("wind_up.ops_curve_shift.compare_ops_curves_pre_post", return_value=None) as mock_plot_func,
):
mock_wind_up_conf = Mock()
Expand Down Expand Up @@ -272,6 +300,10 @@ def test_calls_funcs_as_intended(
turbine_name=wtg_name, pre_df=_df, post_df=_df, x_col="wind_speed", y_col="pitch"
)

mock_ws.assert_called_once_with(
turbine_name=wtg_name, pre_df=_df, post_df=_df, x_col="power", y_col="wind_speed"
)

mock_plot_func.assert_called_once_with(
pre_df=_df,
post_df=_df,
Expand All @@ -289,6 +321,7 @@ def test_calls_funcs_as_intended(
f"{CurveTypes.POWER_CURVE.value}_shift": np.nan,
f"{CurveTypes.RPM.value}_shift": np.nan,
f"{CurveTypes.PITCH.value}_shift": np.nan,
f"{CurveTypes.WIND_SPEED.value}_shift": np.nan,
}

assert actual == expected
64 changes: 39 additions & 25 deletions wind_up/ops_curve_shift.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -14,24 +14,35 @@
from wind_up.models import PlotConfig, WindUpConfig


class CurveThresholds(Enum):
POWER_CURVE = 0.01
RPM = 0.005
PITCH = 0.1


class CurveTypes(str, Enum):
POWER_CURVE = "powercurve"
RPM = "rpm"
PITCH = "pitch"
WIND_SPEED = "windspeed"


CURVE_CONSTANTS = {
CurveTypes.POWER_CURVE.value: {"warning_threshold": 0.01, "x_bin_width": 1},
CurveTypes.RPM.value: {"warning_threshold": 0.005, "x_bin_width": 0},
CurveTypes.PITCH.value: {"warning_threshold": 0.1, "x_bin_width": 1},
CurveTypes.WIND_SPEED.value: {"warning_threshold": 0.01, "x_bin_width": 1},
}


class CurveConfig(BaseModel):
name: CurveTypes
x_col: str
y_col: str
x_bin_width: int
warning_threshold: float
x_bin_width: int | float | None = None
warning_threshold: float | None = None

@model_validator(mode="after")
def validate_constants(self) -> CurveConfig:
if self.x_bin_width is None:
self.x_bin_width = CURVE_CONSTANTS[self.name]["x_bin_width"]
if self.warning_threshold is None:
self.warning_threshold = CURVE_CONSTANTS[self.name]["warning_threshold"]
return self


class CurveShiftInput(BaseModel):
Expand Down Expand Up @@ -83,6 +94,7 @@ def check_for_ops_curve_shift(
f"{CurveTypes.POWER_CURVE.value}_shift": np.nan,
f"{CurveTypes.RPM.value}_shift": np.nan,
f"{CurveTypes.PITCH.value}_shift": np.nan,
f"{CurveTypes.WIND_SPEED.value}_shift": np.nan,
}

required_cols = OpsCurveRequiredColumns(wind_speed=scada_ws_col, power=pw_col, pitch=pt_col, rpm=rpm_col)
Expand All @@ -104,6 +116,10 @@ def check_for_ops_curve_shift(
turbine_name=wtg_name, pre_df=pre_df, post_df=post_df, x_col=scada_ws_col, y_col=pt_col
)

results_dict[f"{CurveTypes.WIND_SPEED.value}_shift"] = calculate_wind_speed_curve_shift(
turbine_name=wtg_name, pre_df=pre_df, post_df=post_df, x_col=pw_col, y_col=scada_ws_col
)

if plot:
compare_ops_curves_pre_post(
pre_df=pre_df,
Expand All @@ -124,13 +140,7 @@ def check_for_ops_curve_shift(
def calculate_power_curve_shift(
turbine_name: str, pre_df: pd.DataFrame, post_df: pd.DataFrame, x_col: str, y_col: str
) -> float:
curve_config = CurveConfig(
name=CurveTypes.POWER_CURVE.value,
x_col=x_col,
y_col=y_col,
x_bin_width=1,
warning_threshold=CurveThresholds.POWER_CURVE.value,
)
curve_config = CurveConfig(name=CurveTypes.POWER_CURVE.value, x_col=x_col, y_col=y_col)

curve_shift_input = CurveShiftInput(
turbine_name=turbine_name, pre_df=pre_df, post_df=post_df, curve_config=curve_config
Expand All @@ -142,9 +152,7 @@ def calculate_power_curve_shift(
def calculate_rpm_curve_shift(
turbine_name: str, pre_df: pd.DataFrame, post_df: pd.DataFrame, x_col: str, y_col: str
) -> float:
curve_config = CurveConfig(
name=CurveTypes.RPM.value, x_col=x_col, y_col=y_col, x_bin_width=0, warning_threshold=CurveThresholds.RPM.value
)
curve_config = CurveConfig(name=CurveTypes.RPM.value, x_col=x_col, y_col=y_col)

curve_shift_input = CurveShiftInput(
turbine_name=turbine_name, pre_df=pre_df, post_df=post_df, curve_config=curve_config
Expand All @@ -156,14 +164,20 @@ def calculate_rpm_curve_shift(
def calculate_pitch_curve_shift(
turbine_name: str, pre_df: pd.DataFrame, post_df: pd.DataFrame, x_col: str, y_col: str
) -> float:
curve_config = CurveConfig(
name=CurveTypes.PITCH.value,
x_col=x_col,
y_col=y_col,
x_bin_width=1,
warning_threshold=CurveThresholds.PITCH.value,
curve_config = CurveConfig(name=CurveTypes.PITCH.value, x_col=x_col, y_col=y_col)

curve_shift_input = CurveShiftInput(
turbine_name=turbine_name, pre_df=pre_df, post_df=post_df, curve_config=curve_config
)

return _calculate_curve_shift(curve_shift_input=curve_shift_input)


def calculate_wind_speed_curve_shift(
turbine_name: str, pre_df: pd.DataFrame, post_df: pd.DataFrame, x_col: str, y_col: str
) -> float:
curve_config = CurveConfig(name=CurveTypes.WIND_SPEED.value, x_col=x_col, y_col=y_col)

curve_shift_input = CurveShiftInput(
turbine_name=turbine_name, pre_df=pre_df, post_df=post_df, curve_config=curve_config
)
Expand Down Expand Up @@ -194,7 +208,7 @@ def _calculate_curve_shift(curve_shift_input: CurveShiftInput) -> float:
post_df = curve_shift_input.post_df
wtg_name = curve_shift_input.turbine_name

bins = np.arange(0, pre_df[conf.x_col].max() + conf.x_bin_width, conf.x_bin_width) if conf.x_bin_width > 0 else 10
bins = np.arange(0, pre_df[conf.x_col].max() + conf.x_bin_width, conf.x_bin_width) if conf.x_bin_width > 0 else 10 # type: ignore[operator]

mean_curve = pre_df.groupby(pd.cut(pre_df[conf.x_col], bins=bins, retbins=False), observed=True).agg(
x_mean=pd.NamedAgg(column=conf.x_col, aggfunc="mean"),
Expand Down

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