"""Example: Reference turbines
For each reference wind turbine in the turbine library, make a small figure
showing its power and thrust coefficient curves and demonstrate its power loss
to yaw.
"""
import matplotlib.pyplot as plt
import numpy as np
from floris import FlorisModel
ws_array = np.arange(0.1, 30, 0.2)
wd_array = 270.0 * np.ones_like(ws_array)
turbulence_intensities = 0.06 * np.ones_like(ws_array)
yaw_angles = np.linspace(-30, 30, 60)
wind_speed_to_test_yaw = 11
# Grab the gch model
fmodel = FlorisModel("../inputs/gch.yaml")
# Make one turbine simulation
fmodel.set(layout_x=[0], layout_y=[0])
# Apply wind directions and wind speeds
fmodel.set(
wind_speeds=ws_array, wind_directions=wd_array, turbulence_intensities=turbulence_intensities
)
# Get a list of available turbine models provided through FLORIS, and remove
# multi-dimensional power/thrust coefficient turbine definitions as they require different handling
turbines = [
t.stem
for t in fmodel.core.farm.internal_turbine_library.iterdir()
if t.suffix == ".yaml" and ("multi_dim" not in t.stem)
]
# Declare a set of figures for comparing cp and ct across models
fig_pow_ct, axarr_pow_ct = plt.subplots(2, 1, sharex=True, figsize=(10, 10))
# For each turbine model available plot the basic info
for t in turbines:
# Set t as the turbine
fmodel.set(turbine_type=[t])
fmodel.reset_operation() # Remove any previously applied yaw angles
# Since we are changing the turbine type, make a matching change to the reference wind height
fmodel.assign_hub_height_to_ref_height()
# Plot power and ct onto the fig_pow_ct plot
axarr_pow_ct[0].plot(
fmodel.core.farm.turbine_map[0].power_thrust_table["wind_speed"],
fmodel.core.farm.turbine_map[0].power_thrust_table["power"],
label=t,
)
axarr_pow_ct[0].grid(True)
axarr_pow_ct[0].legend()
axarr_pow_ct[0].set_ylabel("Power (kW)")
axarr_pow_ct[1].plot(
fmodel.core.farm.turbine_map[0].power_thrust_table["wind_speed"],
fmodel.core.farm.turbine_map[0].power_thrust_table["thrust_coefficient"],
label=t,
)
axarr_pow_ct[1].grid(True)
axarr_pow_ct[1].legend()
axarr_pow_ct[1].set_ylabel("Ct (-)")
axarr_pow_ct[1].set_xlabel("Wind Speed (m/s)")
# Create a figure
fig, axarr = plt.subplots(1, 2, figsize=(10, 5))
# Try a few density
for density in [1.15, 1.225, 1.3]:
fmodel.set(air_density=density)
# POWER CURVE
ax = axarr[0]
fmodel.set(
wind_speeds=ws_array,
wind_directions=wd_array,
turbulence_intensities=turbulence_intensities,
)
fmodel.reset_operation() # Remove any previously applied yaw angles
fmodel.run()
turbine_powers = fmodel.get_turbine_powers().flatten() / 1e3
if density == 1.225:
ax.plot(ws_array, turbine_powers, label="Air Density = %.3f" % density, lw=2, color="k")
else:
ax.plot(ws_array, turbine_powers, label="Air Density = %.3f" % density, lw=1)
ax.grid(True)
ax.legend()
ax.set_xlabel("Wind Speed (m/s)")
ax.set_ylabel("Power (kW)")
# Power loss to yaw, try a range of yaw angles
ax = axarr[1]
fmodel.set(
wind_speeds=[wind_speed_to_test_yaw],
wind_directions=[270.0],
turbulence_intensities=[0.06],
)
yaw_result = []
for yaw in yaw_angles:
fmodel.set(yaw_angles=np.array([[yaw]]))
fmodel.run()
turbine_powers = fmodel.get_turbine_powers().flatten() / 1e3
yaw_result.append(turbine_powers[0])
if density == 1.225:
ax.plot(yaw_angles, yaw_result, label="Air Density = %.3f" % density, lw=2, color="k")
else:
ax.plot(yaw_angles, yaw_result, label="Air Density = %.3f" % density, lw=1)
# ax.plot(yaw_angles,yaw_result,label='Air Density = %.3f' % density)
ax.grid(True)
ax.legend()
ax.set_xlabel("Yaw Error (deg)")
ax.set_ylabel("Power (kW)")
ax.set_title("Wind Speed = %.1f" % wind_speed_to_test_yaw)
# Give a suptitle
fig.suptitle(t)
plt.show()
import warnings
warnings.filterwarnings('ignore')
