[BUGFIX] Improve handling of multidimensional turbine conditions

examples/examples_multidim/003_multi_dimensional_cp_ct_TI.py

@@ -0,0 +1,58 @@
+"""Example: Multi-dimensional Cp/Ct with 2 Hs values
+This example follows the previous example but shows the effect of changing the Hs setting.
+
+NOTE: The multi-dimensional Cp/Ct data used in this example is fictional for the purposes of
+facilitating this example. The Cp/Ct values for the different wave conditions are scaled
+values of the original Cp/Ct data for the IEA 15MW turbine.
+"""
+
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+from floris import FlorisModel, TimeSeries
+
+
+# Initialize FLORIS with the given input file.
+fmodel = FlorisModel("../inputs/gch_multi_dim_cp_ct_TI.yaml")
+
+# Make a second Floris instance with a different setting for Hs.
+# Note the multi-cp-ct file (iea_15MW_multi_dim_Tp_Hs.csv)
+# for the turbine model iea_15MW_floating_multi_dim_cp_ct.yaml
+# Defines Hs at 1 and 5.
+# The value in gch_multi_dim_cp_ct.yaml is 3.01 which will map
+# to 5 as the nearer value, so we set the other case to 1
+# for contrast.
+# fmodel_dict_mod = fmodel.core.as_dict()
+# fmodel_dict_mod["flow_field"]["multidim_conditions"]["TI"] = 0.10
+# # TODO: create a set_multidim_conditions method on fmodel (which reinitializes)
+# # Can check here if it is a valid key
+# # OR: add to set() method. Each value in multidim_conditions dict should be a scalar value
+# fmodel_hs_1 = FlorisModel(fmodel_dict_mod)
+
+# Set both cases to 3 turbine layout
+fmodel.set(layout_x=[0.0, 500.0, 1000.0], layout_y=[0.0, 0.0, 0.0])
+
+# Use a sweep of wind speeds
+wind_speeds = np.arange(5, 20, 1.0)
+time_series = TimeSeries(
+    wind_directions=270.0, wind_speeds=wind_speeds, turbulence_intensities=0.06
+)
+fmodel.set(wind_data=time_series)
+
+fig, axarr = plt.subplots(1, 3, sharex=True, figsize=(12, 4))
+for ti, col in zip([0.06, 0.10], ["k", "r"]):
+    fmodel.set(multidim_conditions={"TI": ti})
+    fmodel.run()
+    turbine_powers = fmodel.get_turbine_powers() / 1000.0
+
+    for t_idx in range(3):
+        ax = axarr[t_idx]
+        ax.plot(wind_speeds, turbine_powers[:, t_idx], color=col, label="TI={0:.2f}".format(ti))
+for t_idx in range(3):
+    axarr[t_idx].grid(True)
+    axarr[t_idx].set_xlabel("Wind Speed (m/s)")
+    axarr[t_idx].set_title(f"Turbine {t_idx}")
+axarr[0].legend()
+
+plt.show()

examples/inputs/gch_multi_dim_cp_ct_TI.yaml

@@ -0,0 +1,113 @@
+
+name: GCH multi dimensional Cp/Ct
+description: Three turbines using GCH model
+floris_version: v4
+
+logging:
+  console:
+    enable: true
+    level: WARNING
+  file:
+    enable: false
+    level: WARNING
+
+solver:
+  type: turbine_grid
+  turbine_grid_points: 3
+
+farm:
+  layout_x:
+  - 0.0
+  - 630.0
+  - 1260.0
+  layout_y:
+  - 0.0
+  - 0.0
+  - 0.0
+  turbine_type:
+  - iea_15MW_multi_dim_TI
+
+flow_field:
+  multidim_conditions:
+    TI: 0.06
+  air_density: 1.225
+  reference_wind_height: -1 # -1 is code for use the hub height
+  turbulence_intensities:
+  - 0.06
+  wind_directions:
+  - 270.0
+  wind_shear: 0.12
+  wind_speeds:
+  - 8.0
+  wind_veer: 0.0
+
+wake:
+  model_strings:
+    combination_model: sosfs
+    deflection_model: gauss
+    turbulence_model: crespo_hernandez
+    velocity_model: gauss
+
+  enable_secondary_steering: true
+  enable_yaw_added_recovery: true
+  enable_transverse_velocities: true
+  enable_active_wake_mixing: false
+
+  wake_deflection_parameters:
+    gauss:
+      ad: 0.0
+      alpha: 0.58
+      bd: 0.0
+      beta: 0.077
+      dm: 1.0
+      ka: 0.38
+      kb: 0.004
+    jimenez:
+      ad: 0.0
+      bd: 0.0
+      kd: 0.05
+    empirical_gauss:
+      horizontal_deflection_gain_D: 3.0
+      vertical_deflection_gain_D: -1
+      deflection_rate: 22
+      mixing_gain_deflection: 0.0
+      yaw_added_mixing_gain: 0.0
+
+  wake_velocity_parameters:
+    cc:
+      a_s: 0.179367259
+      b_s: 0.0118889215
+      c_s1: 0.0563691592
+      c_s2: 0.13290157
+      a_f: 3.11
+      b_f: -0.68
+      c_f: 2.41
+      alpha_mod: 1.0
+    gauss:
+      alpha: 0.58
+      beta: 0.077
+      ka: 0.38
+      kb: 0.004
+    jensen:
+      we: 0.05
+    turbopark:
+      A: 0.04
+      sigma_max_rel: 4.0
+    empirical_gauss:
+      wake_expansion_rates:
+      - 0.023
+      - 0.008
+      breakpoints_D:
+      - 10
+      sigma_0_D: 0.28
+      smoothing_length_D: 2.0
+      mixing_gain_velocity: 2.0
+
+  wake_turbulence_parameters:
+    crespo_hernandez:
+      initial: 0.01
+      constant: 0.9
+      ai: 0.83
+      downstream: -0.25
+    wake_induced_mixing:
+      atmospheric_ti_gain: 0.0

floris/core/turbine/turbine.py

@@ -62,15 +62,18 @@ def select_multidim_condition(
 
     # Find the nearest key to the specified conditions.
     specified_conditions = np.array(specified_conditions)
+    if len(specified_conditions.shape) == 1: # Single specified condition
+        specified_conditions = specified_conditions.reshape(-1, 1)
 
     # Find the nearest key to the specified conditions.
     nearest_condition = np.zeros_like(condition)
     for i, c in enumerate(condition):
+        # specified_conditions[:,i] assumes two dimensions, which isn't necessarily the case.
         nearest_condition[i] = (
             specified_conditions[:, i][np.absolute(specified_conditions[:, i] - c).argmin()]
         )
 
-    return tuple(nearest_condition)
+    return tuple(nearest_condition)# if len(specified_conditions)
 
 
 def power(
@@ -560,6 +563,8 @@ def _initialize_multidim_power_thrust_table(self):
         for key in df2.index.unique():
             # Select the correct ws/Cp/Ct data
             data = df2.loc[key]
+            if type(key) is not tuple:
+                key = (key,)
 
             # Build the interpolants
             power_thrust_table_.update(
@@ -585,14 +590,16 @@ def check_power_thrust_table(self, instance: attrs.Attribute, value: dict) -> No
         """
 
         if self.multi_dimensional_cp_ct:
-            if isinstance(list(value.keys())[0], tuple):
-                value = list(value.values())[0] # Check the first entry of multidim
-            elif "power_thrust_data_file" in value.keys():
+            if "power_thrust_data_file" in value.keys():
                 return None
             else:
-                raise ValueError(
-                    "power_thrust_data_file must be defined if multi_dimensional_cp_ct is True."
-                )
+                key_types = [type(k) for k in value.keys()]
+                if key_types[0] in (tuple, float, int):
+                    value = list(value.values())[0] # Check the first entry of multidim
+                else:
+                    raise ValueError(
+                        "power_thrust_data_file must be defined if multi_dimensional_cp_ct is True."
+                    )
 
         if not {"wind_speed", "power", "thrust_coefficient"} <= set(value.keys()):
             raise ValueError(

floris/floris_model.py

@@ -133,6 +133,7 @@ def _reinitialize(
         solver_settings: dict | None = None,
         heterogeneous_inflow_config=None,
         wind_data: type[WindDataBase] | None = None,
+        multidim_conditions: dict | None = None,
     ):
         """
         Instantiate a new Floris object with updated conditions set by arguments. Any parameters
@@ -245,6 +246,8 @@ def _reinitialize(
 
             flow_field_dict["heterogeneous_inflow_config"] = heterogeneous_inflow_config
 
+        if multidim_conditions is not None:
+            flow_field_dict["multidim_conditions"] = multidim_conditions
 
 
         if solver_settings is not None:
@@ -382,6 +385,7 @@ def set(
         awc_amplitudes: NDArrayFloat | list[float] | list[float, None] | None = None,
         awc_frequencies: NDArrayFloat | list[float] | list[float, None] | None = None,
         disable_turbines: NDArrayBool | list[bool] | None = None,
+        multidim_conditions: dict | None = None,
     ):
         """
         Set the wind conditions and operation setpoints for the wind farm.
@@ -437,6 +441,7 @@ def set(
             solver_settings=solver_settings,
             heterogeneous_inflow_config=heterogeneous_inflow_config,
             wind_data=wind_data,
+            multidim_conditions=multidim_conditions,
         )
 
         # If the yaw angles or power setpoints are not the default, set them back to the

floris/turbine_library/iea_15MW_multi_dim_TI.csv

@@ -0,0 +1,109 @@
+TI,ws,power,thrust_coefficient
+0.06,0.0,0.0,0.0
+0.06,2.9,0.0,0.0
+0.06,3.0,42.733312,0.80742173
+0.06,3.54953237,292.585981,0.784655297
+0.06,4.067900771,607.966543,0.781771245
+0.06,4.553906848,981.097693,0.785377072
+0.06,5.006427063,1401.98084,0.788045584
+0.06,5.424415288,1858.67086,0.789922119
+0.06,5.806905228,2337.575997,0.790464625
+0.06,6.153012649,2824.097302,0.789868339
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floris/turbine_library/iea_15MW_multi_dim_TI.yaml

@@ -0,0 +1,11 @@
+turbine_type: 'iea_15MW_floating'
+hub_height: 150.0
+rotor_diameter: 242.24
+TSR: 8.0
+multi_dimensional_cp_ct: True
+power_thrust_table:
+  ref_air_density: 1.225
+  ref_tilt: 6.0
+  cosine_loss_exponent_yaw: 1.88
+  cosine_loss_exponent_tilt: 1.88
+  power_thrust_data_file: 'iea_15MW_multi_dim_TI.csv'