Example: Floating turbines

This example demonstrates the impact of floating on turbine power and thrust (not wake behavior).A floating turbine in FLORIS is defined by including a floating_tilt_table in the turbineinput yaml which sets the steady tilt angle of the turbine based on wind speed. This tilt angleis computed for each turbine based on effective velocity. This tilt angle is then passed onto the respective wake model.The value of the parameter ref_tilt is the value of tilt at which the ct/cp curveshave been defined.If correct_cp_ct_for_tilt is True, then the difference between the current tilt asinterpolated from the floating tilt table is used to scale the turbine power and thrust.If correct_cp_ct_for_tilt is False, then it is assumed that the Cp/Ct tables providedalready account for the variation in tilt with wind speed (for example they were computed froma turbine simulator with tilt degree-of-freedom enabled and the floating platform simulated),and no correction is made.In the example below, three single-turbine simulations are run to show the different behaviors.fmodel_fixed: Fixed bottom turbine (no tilt variation with wind speed)fmodel_floating: Floating turbine (tilt varies with wind speed)fmodel_floating_defined_floating: Floating turbine (tilt varies with wind speed, but tilt does not scale cp/ct)

import matplotlib.pyplot as plt
import numpy as np

from floris import FlorisModel, TimeSeries


# Create the Floris instances
fmodel_fixed = FlorisModel("../inputs_floating/gch_fixed.yaml")
fmodel_floating = FlorisModel("../inputs_floating/gch_floating.yaml")
fmodel_floating_defined_floating = FlorisModel(
    "../inputs_floating/gch_floating_defined_floating.yaml"
)

# Calculate across wind speeds, while holding win directions constant
ws_array = np.arange(3.0, 25.0, 1.0)
time_series = TimeSeries(wind_directions=270.0, wind_speeds=ws_array, turbulence_intensities=0.06)
fmodel_fixed.set(wind_data=time_series)
fmodel_floating.set(wind_data=time_series)
fmodel_floating_defined_floating.set(wind_data=time_series)

fmodel_fixed.run()
fmodel_floating.run()
fmodel_floating_defined_floating.run()

# Grab power
power_fixed = fmodel_fixed.get_turbine_powers().flatten() / 1000.0
power_floating = fmodel_floating.get_turbine_powers().flatten() / 1000.0
power_floating_defined_floating = (
    fmodel_floating_defined_floating.get_turbine_powers().flatten() / 1000.0
)

# Grab Ct
ct_fixed = fmodel_fixed.get_turbine_thrust_coefficients().flatten()
ct_floating = fmodel_floating.get_turbine_thrust_coefficients().flatten()
ct_floating_defined_floating = (
    fmodel_floating_defined_floating.get_turbine_thrust_coefficients().flatten()
)

# Grab turbine tilt angles
eff_vels = fmodel_fixed.turbine_average_velocities
tilt_angles_fixed = np.squeeze(fmodel_fixed.core.farm.calculate_tilt_for_eff_velocities(eff_vels))

eff_vels = fmodel_floating.turbine_average_velocities
tilt_angles_floating = np.squeeze(
    fmodel_floating.core.farm.calculate_tilt_for_eff_velocities(eff_vels)
)

eff_vels = fmodel_floating_defined_floating.turbine_average_velocities
tilt_angles_floating_defined_floating = np.squeeze(
    fmodel_floating_defined_floating.core.farm.calculate_tilt_for_eff_velocities(eff_vels)
)

# Plot results

fig, axarr = plt.subplots(4, 1, figsize=(8, 10), sharex=True)

ax = axarr[0]
ax.plot(ws_array, tilt_angles_fixed, color="k", lw=2, label="Fixed Bottom")
ax.plot(ws_array, tilt_angles_floating, color="b", label="Floating")
ax.plot(
    ws_array,
    tilt_angles_floating_defined_floating,
    color="m",
    ls="--",
    label="Floating (cp/ct not scaled by tilt)",
)
ax.grid(True)
ax.legend()
ax.set_title("Tilt angle (deg)")
ax.set_ylabel("Tlit (deg)")

ax = axarr[1]
ax.plot(ws_array, power_fixed, color="k", lw=2, label="Fixed Bottom")
ax.plot(ws_array, power_floating, color="b", label="Floating")
ax.plot(
    ws_array,
    power_floating_defined_floating,
    color="m",
    ls="--",
    label="Floating (cp/ct not scaled by tilt)",
)
ax.grid(True)
ax.legend()
ax.set_title("Power")
ax.set_ylabel("Power (kW)")

ax = axarr[2]
# ax.plot(ws_array, power_fixed, color='k',label='Fixed Bottom')
ax.plot(ws_array, power_floating - power_fixed, color="b", label="Floating")
ax.plot(
    ws_array,
    power_floating_defined_floating - power_fixed,
    color="m",
    ls="--",
    label="Floating (cp/ct not scaled by tilt)",
)
ax.grid(True)
ax.legend()
ax.set_title("Difference from fixed bottom power")
ax.set_ylabel("Power (kW)")

ax = axarr[3]
ax.plot(ws_array, ct_fixed, color="k", lw=2, label="Fixed Bottom")
ax.plot(ws_array, ct_floating, color="b", label="Floating")
ax.plot(
    ws_array,
    ct_floating_defined_floating,
    color="m",
    ls="--",
    label="Floating (cp/ct not scaled by tilt)",
)
ax.grid(True)
ax.legend()
ax.set_title("Coefficient of thrust")
ax.set_ylabel("Ct (-)")

plt.show()
import warnings
warnings.filterwarnings('ignore')

floris.logging_manager.LoggingManager WARNING The current model does not account for vertical wake deflection due to tilt. Corrections to power and thrust coefficient can be included, but no vertical wake deflection will occur.

floris.logging_manager.LoggingManager WARNING The current model does not account for vertical wake deflection due to tilt. Corrections to power and thrust coefficient can be included, but no vertical wake deflection will occur.