Tum misalignment model

docs/operation_models_user.ipynb

@@ -460,10 +460,87 @@
     "ax[1].set_ylabel(\"Power [kW]\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "92912bf7",
+   "metadata": {},
+   "source": [
+    "### Controller-dependent model\n",
+    "\n",
+    "User-level name: `\"controller-dependent\"`\n",
+    "\n",
+    "Underlying class: `ControllerDependentTurbine`\n",
+    "\n",
+    "Required data on `power_thrust_table`:\n",
+    "- `rotor_solidity`: (scalar)\n",
+    "- `rated_rpm`: (scalar)\n",
+    "- `generator_efficiency`: (scalar)\n",
+    "- `rated_power`: (scalar)\n",
+    "- `rotor_diameter`: (scalar)\n",
+    "- `beta`: (scalar)\n",
+    "- `cd`: (scalar)\n",
+    "- `cl_alfa`: (scalar)\n",
+    "- `cp_ct_data_file`: (string)\n",
+    "\n",
+    "The `\"controller-dependent\"` operation model is an advanced operation model that uses the turbine's Cp/Ct\n",
+    "surface to optimize performance under yaw misalignment.\n",
+    "\n",
+    "TODO: add description of the model at a high level, and also what each of the parameters listed above (`rotor_solidity`, `rated_rpm`, etc) is used for in the model.\n",
+    "\n",
+    "Details can be found in {cite:t}`tamaro2024beyondcosine`."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "92912bf7",
+   "id": "6e4c5ba2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "N  = 101 # How many steps to cover yaw range in\n",
+    "yaw_max = 30 # Maximum yaw to test\n",
+    "\n",
+    "# Set up the yaw angle sweep\n",
+    "yaw_angles = np.linspace(-yaw_max, yaw_max, N).reshape(-1,1)\n",
+    "\n",
+    "# We can use the same FlorisModel, but we'll set it up for this test\n",
+    "fmodel.set(\n",
+    "    wind_data=TimeSeries(\n",
+    "        wind_speeds=np.ones(N) * 8.0,\n",
+    "        wind_directions=np.ones(N) * 270.0,\n",
+    "        turbulence_intensities=0.06\n",
+    "    ),\n",
+    "    yaw_angles=yaw_angles,\n",
+    ")\n",
+    "\n",
+    "# We'll compare the \"controller-dependent\" model to the standard \"cosine-loss\" model\n",
+    "op_models = [\"cosine-loss\", \"controller-dependent\"]\n",
+    "results = {}\n",
+    "\n",
+    "for op_model in op_models:\n",
+    "    print(f\"Evaluating model: {op_model}\")\n",
+    "    fmodel.set_operation_model(op_model)\n",
+    "\n",
+    "    fmodel.run()\n",
+    "    results[op_model] = fmodel.get_turbine_powers().squeeze()\n",
+    "\n",
+    "fig, ax = plt.subplots()\n",
+    "colors = [\"C0\", \"k\"]\n",
+    "linestyles = [\"solid\", \"dashed\"]\n",
+    "for key, c, ls in zip(results, colors, linestyles):\n",
+    "    central_power = results[key][yaw_angles.squeeze() == 0]\n",
+    "    ax.plot(yaw_angles.squeeze(), results[key]/central_power, label=key, color=c, linestyle=ls)\n",
+    "\n",
+    "ax.grid(True)\n",
+    "ax.legend()\n",
+    "ax.set_xlabel(\"Yaw angle [deg]\")\n",
+    "ax.set_ylabel(\"Normalized turbine power [deg]\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "90d5c155",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -485,7 +562,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.2"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,

docs/references.bib

@@ -299,3 +299,15 @@ @article{SinnerFleming2024grs
 title = {Robust wind farm layout optimization},
 journal = {Journal of Physics: Conference Series},
 }
+
+@Article{tamaro2024beyondcosine,
+AUTHOR = {Tamaro, S. and Campagnolo, F. and Bottasso, C. L.},
+TITLE = {On the power and control of a misaligned rotor -- beyond the cosine law},
+JOURNAL = {Wind Energy Science},
+VOLUME = {9},
+YEAR = {2024},
+NUMBER = {7},
+PAGES = {1547--1575},
+URL = {https://wes.copernicus.org/articles/9/1547/2024/},
+DOI = {10.5194/wes-9-1547-2024}
+}

examples/examples_operation_models/001_compare_yaw_loss.py

@@ -0,0 +1,58 @@
+"""Example: Compare yaw loss
+This example shows demonstrates how the Controller-dependent operation model (developed at TUM)
+alters how a turbine loses power to yaw compared to the standard cosine loss model.
+"""
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+from floris import FlorisModel
+
+
+# Parameters
+N  = 101 # How many steps to cover yaw range in
+yaw_max = 30 # Maximum yaw to test
+
+# Set up the yaw angle sweep
+yaw_angles = np.zeros((N,1))
+yaw_angles[:,0] = np.linspace(-yaw_max, yaw_max, N)
+
+# Create the FLORIS model
+fmodel = FlorisModel("../inputs/gch.yaml")
+
+# Initialize to a simple 1 turbine case with n_findex = N
+fmodel.set(
+    layout_x=[0],
+    layout_y=[0],
+    wind_directions=270 * np.ones(N),
+    wind_speeds=8 * np.ones(N),
+    turbulence_intensities=0.06 * np.ones(N),
+    yaw_angles=yaw_angles,
+)
+
+# Loop over the operational models to compare
+op_models = ["cosine-loss", "controller-dependent"]
+results = {}
+
+for op_model in op_models:
+
+    print(f"Evaluating model: {op_model}")
+    fmodel.set_operation_model(op_model)
+
+    fmodel.run()
+    results[op_model] = fmodel.get_turbine_powers().squeeze()
+
+# Plot the results
+fig, ax = plt.subplots()
+colors = ["C0", "k"]
+linestyles = ["solid", "dashed"]
+for key, c, ls in zip(results, colors, linestyles):
+    central_power = results[key][yaw_angles.squeeze() == 0]
+    ax.plot(yaw_angles.squeeze(), results[key]/central_power, label=key, color=c, linestyle=ls)
+
+ax.grid(True)
+ax.legend()
+ax.set_xlabel("Yaw angle [deg]")
+ax.set_ylabel("Normalized turbine power [deg]")
+
+plt.show()

floris/core/turbine/__init__.py

@@ -1,4 +1,5 @@
 
+from floris.core.turbine.controller_dependent_operation_model import ControllerDependentTurbine
 from floris.core.turbine.operation_models import (
     AWCTurbine,
     CosineLossTurbine,