feat: add adjustment factor for models (new) (#611)

* feat: add adjustment factor for models

docs/docs/changelog/next.md

@@ -21,6 +21,7 @@ sidebar_position: -1002
   is any downstream choking, this will happen between the outlet of the last compressor stage and the outlet of the
   compressor train. This means that in a situation with downstream choking, the fluid stream leaving the compressor
   train will have lower e.g. pressure and density than the fluid stream leaving the last compressor stage.
+- `POWER_ADJUSTMENT_FACTOR` for models: Optional factor to adjust the power (MW). Previously only the `POWER_ADJUSTMENT_CONSTANT` has been available for models, now it is possible to adjust/scale the power with a constant and a factor. It can be used to calibrate equipment.
 
 ## Fixes
 

src/libecalc/core/models/compressor/base.py

@@ -130,6 +130,7 @@ def evaluate_turbine_based_on_compressor_model_result(
             load_adjusted = np.where(
                 np.asarray(compressor_energy_function_result.power) > 0,
                 np.asarray(compressor_energy_function_result.power)
+                * self.data_transfer_object.energy_usage_adjustment_factor
                 + self.data_transfer_object.energy_usage_adjustment_constant,
                 np.asarray(compressor_energy_function_result.power),
             )

src/libecalc/core/models/compressor/train/base.py

@@ -136,7 +136,10 @@ def evaluate_rate_ps_pd(
 
         power_mw = np.array([result.power_megawatt for result in train_results])
         power_mw_adjusted = np.where(
-            power_mw > 0, power_mw + self.data_transfer_object.energy_usage_adjustment_constant, power_mw
+            power_mw > 0,
+            power_mw * self.data_transfer_object.energy_usage_adjustment_factor
+            + self.data_transfer_object.energy_usage_adjustment_constant,
+            power_mw,
         )
 
         max_standard_rate = np.full_like(rate, fill_value=INVALID_MAX_RATE, dtype=float)

src/libecalc/core/models/compressor/train/variable_speed_compressor_train_common_shaft_multiple_streams_and_pressures.py

@@ -892,7 +892,10 @@ def evaluate_rate_ps_pint_pd(
 
         power_mw = np.array([time_step.power_megawatt for time_step in train_results])
         power_mw_adjusted = np.where(
-            power_mw > 0, power_mw + self.data_transfer_object.energy_usage_adjustment_constant, power_mw
+            power_mw > 0,
+            power_mw * self.data_transfer_object.energy_usage_adjustment_factor
+            + self.data_transfer_object.energy_usage_adjustment_constant,
+            power_mw,
         )
 
         inlet_stream, outlet_stream, stage_results = CompressorTrainResultSingleTimeStep.from_result_list_to_dto(

src/libecalc/core/models/turbine.py

@@ -40,6 +40,8 @@ def max_power(self) -> Optional[float]:
         )
 
     def evaluate(self, load: NDArray[np.float64], fuel_lower_heating_value: float = 0) -> TurbineResult:
+        # Calibration of turbine load:
+        # Linear adjustment: (1/a)*x + b/a.
         load_adjusted = np.where(
             load > 0,
             (load + self.data_transfer_object.energy_usage_adjustment_constant)

src/libecalc/presentation/yaml/mappers/model.py

@@ -367,7 +367,7 @@ def _variable_speed_compressor_train_multiple_streams_and_pressures_mapper(
         streams=streams,
         stages=stages,
         energy_usage_adjustment_constant=model_config.get(EcalcYamlKeywords.models_power_adjustment_constant_mw, 0),
-        energy_usage_adjustment_factor=1.0,
+        energy_usage_adjustment_factor=model_config.get(EcalcYamlKeywords.models_power_adjustment_factor_mw, 1),
         calculate_max_rate=model_config.get(EcalcYamlKeywords.calculate_max_rate, False),
         pressure_control=pressure_control,
         maximum_power=model_config.get(EcalcYamlKeywords.models_maximum_power, None),
@@ -451,7 +451,7 @@ def _single_speed_compressor_train_mapper(
         pressure_control=pressure_control,
         maximum_discharge_pressure=maximum_discharge_pressure,
         energy_usage_adjustment_constant=model_config.get(EcalcYamlKeywords.models_power_adjustment_constant_mw, 0),
-        energy_usage_adjustment_factor=1.0,
+        energy_usage_adjustment_factor=model_config.get(EcalcYamlKeywords.models_power_adjustment_factor_mw, 1),
         calculate_max_rate=model_config.get(EcalcYamlKeywords.calculate_max_rate, False),
         maximum_power=model_config.get(EcalcYamlKeywords.models_maximum_power, None),
     )
@@ -521,7 +521,7 @@ def _variable_speed_compressor_train_mapper(
         fluid_model=fluid_model,
         stages=stages,
         energy_usage_adjustment_constant=model_config.get(EcalcYamlKeywords.models_power_adjustment_constant_mw, 0),
-        energy_usage_adjustment_factor=1.0,
+        energy_usage_adjustment_factor=model_config.get(EcalcYamlKeywords.models_power_adjustment_factor_mw, 1),
         calculate_max_rate=model_config.get(EcalcYamlKeywords.calculate_max_rate, False),
         pressure_control=pressure_control,
         maximum_power=model_config.get(EcalcYamlKeywords.models_maximum_power, None),
@@ -583,7 +583,7 @@ def _simplified_variable_speed_compressor_train_mapper(
                 for stage in stages
             ],
             energy_usage_adjustment_constant=model_config.get(EcalcYamlKeywords.models_power_adjustment_constant_mw, 0),
-            energy_usage_adjustment_factor=1.0,
+            energy_usage_adjustment_factor=model_config.get(EcalcYamlKeywords.models_power_adjustment_factor_mw, 1),
             calculate_max_rate=model_config.get(EcalcYamlKeywords.calculate_max_rate, False),
             maximum_power=model_config.get(EcalcYamlKeywords.models_maximum_power, None),
         )
@@ -602,7 +602,7 @@ def _simplified_variable_speed_compressor_train_mapper(
                 remove_liquid_after_cooling=True,
             ),
             energy_usage_adjustment_constant=model_config.get(EcalcYamlKeywords.models_power_adjustment_constant_mw, 0),
-            energy_usage_adjustment_factor=1.0,
+            energy_usage_adjustment_factor=model_config.get(EcalcYamlKeywords.models_power_adjustment_factor_mw, 1),
             calculate_max_rate=model_config.get(EcalcYamlKeywords.calculate_max_rate, False),
             maximum_pressure_ratio_per_stage=train_spec.get(
                 EcalcYamlKeywords.models_type_compressor_train_maximum_pressure_ratio_per_stage
@@ -613,6 +613,7 @@ def _simplified_variable_speed_compressor_train_mapper(
 
 def _turbine_mapper(model_config: Dict, input_models: Dict[str, Any], resources: Resources) -> dto.Turbine:
     energy_usage_adjustment_constant = model_config.get(EcalcYamlKeywords.models_power_adjustment_constant_mw, 0)
+    energy_usage_adjustment_factor = model_config.get(EcalcYamlKeywords.models_power_adjustment_factor_mw, 1)
 
     return dto.Turbine(
         lower_heating_value=model_config.get(EcalcYamlKeywords.fuel_lower_heating_value),
@@ -621,7 +622,7 @@ def _turbine_mapper(model_config: Dict, input_models: Dict[str, Any], resources:
             EcalcYamlKeywords.models_turbine_efficiency_table_efficiency_values
         ),
         energy_usage_adjustment_constant=energy_usage_adjustment_constant,
-        energy_usage_adjustment_factor=1.0,
+        energy_usage_adjustment_factor=energy_usage_adjustment_factor,
     )
 
 
@@ -645,12 +646,13 @@ def _compressor_with_turbine_mapper(
         if attr is None:
             raise ValueError(f"{attr_reference} not found in input models")
     energy_usage_adjustment_constant = model_config.get(EcalcYamlKeywords.models_power_adjustment_constant_mw, 0)
+    energy_usage_adjustment_factor = model_config.get(EcalcYamlKeywords.models_power_adjustment_factor_mw, 1)
 
     return dto.CompressorWithTurbine(
         compressor_train=compressor_train_model,
         turbine=turbine_model,
         energy_usage_adjustment_constant=energy_usage_adjustment_constant,
-        energy_usage_adjustment_factor=1.0,
+        energy_usage_adjustment_factor=energy_usage_adjustment_factor,
     )
 
 

src/libecalc/presentation/yaml/yaml_keywords.py

@@ -176,6 +176,7 @@ class EcalcYamlKeywords:
     models_turbine_efficiency_table_efficiency_values = "TURBINE_EFFICIENCIES"
     models_type_compressor_with_turbine = "COMPRESSOR_WITH_TURBINE"
     models_power_adjustment_constant_mw = "POWER_ADJUSTMENT_CONSTANT"
+    models_power_adjustment_factor_mw = "POWER_ADJUSTMENT_FACTOR"
     models_maximum_power = "MAXIMUM_POWER"
 
     facility_adjustment = "ADJUSTMENT"

src/libecalc/presentation/yaml/yaml_types/models/yaml_compressor_trains.py

@@ -65,6 +65,11 @@ class YamlSingleSpeedCompressorTrain(YamlCompressorTrainBase):
         description="Constant to adjust power usage in MW",
         title="POWER_ADJUSTMENT_CONSTANT",
     )
+    power_adjustment_factor: float = Field(
+        1.0,
+        description="Factor to adjust power usage in MW",
+        title="POWER_ADJUSTMENT_FACTOR",
+    )
     fluid_model: FluidModelReference = Field(..., description="Reference to a fluid model", title="FLUID_MODEL")
 
     def to_dto(self):
@@ -98,6 +103,11 @@ class YamlVariableSpeedCompressorTrain(YamlCompressorTrainBase):
         description="Constant to adjust power usage in MW",
         title="POWER_ADJUSTMENT_CONSTANT",
     )
+    power_adjustment_factor: float = Field(
+        1.0,
+        description="Factor to adjust power usage in MW",
+        title="POWER_ADJUSTMENT_FACTOR",
+    )
     fluid_model: FluidModelReference = Field(..., description="Reference to a fluid model", title="FLUID_MODEL")
 
     def to_dto(self):
@@ -127,6 +137,11 @@ class YamlSimplifiedVariableSpeedCompressorTrain(YamlCompressorTrainBase):
         description="Constant to adjust power usage in MW",
         title="POWER_ADJUSTMENT_CONSTANT",
     )
+    power_adjustment_factor: float = Field(
+        1.0,
+        description="Factor to adjust power usage in MW",
+        title="POWER_ADJUSTMENT_FACTOR",
+    )
 
     def to_dto(self):
         raise NotImplementedError
@@ -167,6 +182,11 @@ class YamlVariableSpeedCompressorTrainMultipleStreamsAndPressures(YamlCompressor
         description="Constant to adjust power usage in MW",
         title="POWER_ADJUSTMENT_CONSTANT",
     )
+    power_adjustment_factor: float = Field(
+        1.0,
+        description="Factor to adjust power usage in MW",
+        title="POWER_ADJUSTMENT_FACTOR",
+    )
 
     def to_dto(self):
         raise NotImplementedError

src/libecalc/presentation/yaml/yaml_types/models/yaml_compressor_with_turbine.py

@@ -26,6 +26,11 @@ class YamlCompressorWithTurbine(YamlBase):
         description="Constant to adjust power usage in MW",
         title="POWER_ADJUSTMENT_CONSTANT",
     )
+    power_adjustment_factor: float = Field(
+        1.0,
+        description="Factor to adjust power usage in MW",
+        title="POWER_ADJUSTMENT_FACTOR",
+    )
     turbine_model: TurbineModelReference = Field(..., description="Reference to a turbine model", title="TURBINE_MODEL")
     type: Literal[YamlModelType.COMPRESSOR_WITH_TURBINE] = Field(
         ...,

src/libecalc/presentation/yaml/yaml_types/models/yaml_turbine.py

@@ -54,6 +54,11 @@ class YamlTurbine(YamlBase):
         description="Constant to adjust power usage in MW",
         title="POWER_ADJUSTMENT_CONSTANT",
     )
+    power_adjustment_factor: float = Field(
+        1.0,
+        description="Factor to adjust power usage in MW",
+        title="POWER_ADJUSTMENT_FACTOR",
+    )
 
     def to_dto(self):
         raise NotImplementedError

src/tests/libecalc/core/models/compressor_modelling/test_variable_speed_compressor_train_common_shaft.py

@@ -363,3 +363,24 @@ def test_variable_speed_compressor_train_vs_unisim_methane(variable_speed_compre
     np.testing.assert_allclose(result.outlet_stream.temperature_kelvin, expected_outlet_temperature, rtol=0.05)
     np.testing.assert_allclose(result.outlet_stream.pressure, expected_outlet_pressure, rtol=0.06)
     np.testing.assert_allclose(result.stage_results[0].polytropic_efficiency, expected_efficiency, rtol=0.03)
+
+
+def test_adjustment_constant_and_factor_one_compressor(variable_speed_compressor_train_one_compressor):
+    compressor_train = variable_speed_compressor_train_one_compressor
+    adjustment_constant = 10
+    adjustment_factor = 1.5
+    result = compressor_train.evaluate_rate_ps_pd(
+        rate=np.asarray([7000]),
+        suction_pressure=np.asarray([30]),
+        discharge_pressure=np.asarray([100.0]),
+    )
+
+    compressor_train.data_transfer_object.energy_usage_adjustment_factor = adjustment_factor
+    compressor_train.data_transfer_object.energy_usage_adjustment_constant = adjustment_constant
+
+    result_adjusted = compressor_train.evaluate_rate_ps_pd(
+        rate=np.asarray([7000]),
+        suction_pressure=np.asarray([30]),
+        discharge_pressure=np.asarray([100.0]),
+    )
+    assert result_adjusted.power[0] == result.power[0] * 1.5 + adjustment_constant

src/tests/libecalc/core/models/test_turbine.py

@@ -38,10 +38,35 @@ def test_turbine_with_power_adjustment_constant(turbine: TurbineModel):
 
 
 def test_turbine_with_power_adjustment_factor(turbine: TurbineModel):
-    energy_usage_adjustment_factor = 0.9
-    result_comparison = turbine.evaluate(load=np.asarray([2.352 / 2, 11.399]))
+    # Result without any adjustment:
+    result = turbine.evaluate(load=np.asarray([2.352 / 2, 11.399]))
 
+    # Set adjustment factor
+    energy_usage_adjustment_factor = 0.9
     turbine.data_transfer_object.energy_usage_adjustment_factor = energy_usage_adjustment_factor
+
+    # Result with adjustment:
+    result_adjusted = turbine.evaluate(load=np.asarray([2.352 / 2, 11.399]))
+
+    # Compare: linear transformation is used to adjust (y = a*x + b. In this case b=0).
+    np.testing.assert_allclose(np.asarray(result.load) / energy_usage_adjustment_factor, result_adjusted.load)
+
+
+def test_turbine_with_power_adjustment_constant_and_factor(turbine: TurbineModel):
+    # Result without any adjustment:
     result = turbine.evaluate(load=np.asarray([2.352 / 2, 11.399]))
 
-    np.testing.assert_allclose(np.asarray(result_comparison.load) / energy_usage_adjustment_factor, result.load)
+    # Set adjustment constant and factor
+    energy_usage_adjustment_constant = 1
+    energy_usage_adjustment_factor = 2
+    turbine.data_transfer_object.energy_usage_adjustment_factor = energy_usage_adjustment_factor
+    turbine.data_transfer_object.energy_usage_adjustment_constant = energy_usage_adjustment_constant
+
+    # Result with adjustment:
+    result_adjusted = turbine.evaluate(load=np.asarray([2.352 / 2, 11.399]))
+
+    # Compare: linear transformation is used to adjust (y = a*x + b).
+    np.testing.assert_allclose(
+        (np.asarray(result.load) + energy_usage_adjustment_constant) / energy_usage_adjustment_factor,
+        result_adjusted.load,
+    )