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Add helix model operation mode (#842)
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examples/examples_control_types/004_helix_active_wake_mixing.py
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# Copyright 2024 NREL | ||
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# Licensed under the Apache License, Version 2.0 (the "License"); you may not | ||
# use this file except in compliance with the License. You may obtain a copy of | ||
# the License at http://www.apache.org/licenses/LICENSE-2.0 | ||
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# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT | ||
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the | ||
# License for the specific language governing permissions and limitations under | ||
# the License. | ||
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# See https://floris.readthedocs.io for documentation | ||
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import matplotlib.pyplot as plt | ||
import numpy as np | ||
import yaml | ||
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import floris.flow_visualization as flowviz | ||
from floris import FlorisModel | ||
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""" | ||
Example to test out using helix wake mixing of upstream turbines. | ||
Helix wake mixing is turned on at turbine 1, off at turbines 2 to 4; | ||
Turbine 2 is in wake turbine 1, turbine 4 in wake of turbine 3. | ||
""" | ||
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# Grab model of FLORIS and update to awc-enabled turbines | ||
fmodel = FlorisModel("../inputs/emgauss_helix.yaml") | ||
fmodel.set_operation_model("awc") | ||
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# Set the wind directions and speeds to be constant over N different helix amplitudes | ||
N = 1 | ||
awc_modes = np.array(["helix", "baseline", "baseline", "baseline"]).reshape(4, N).T | ||
awc_amplitudes = np.array([2.5, 0, 0, 0]).reshape(4, N).T | ||
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# Create 4 WT WF layout with lateral offset of 3D and streamwise offset of 4D | ||
D = 240 | ||
fmodel.set( | ||
layout_x=[0.0, 4*D, 0.0, 4*D], | ||
layout_y=[0.0, 0.0, -3*D, -3*D], | ||
wind_directions=270 * np.ones(N), | ||
wind_speeds=8.0 * np.ones(N), | ||
turbulence_intensities=0.06*np.ones(N), | ||
awc_modes=awc_modes, | ||
awc_amplitudes=awc_amplitudes | ||
) | ||
fmodel.run() | ||
turbine_powers = fmodel.get_turbine_powers() | ||
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# Plot the flow fields for T1 awc_amplitude = 2.5 | ||
horizontal_plane = fmodel.calculate_horizontal_plane( | ||
x_resolution=200, | ||
y_resolution=100, | ||
height=150.0, | ||
awc_modes=awc_modes, | ||
awc_amplitudes=awc_amplitudes | ||
) | ||
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y_plane_baseline = fmodel.calculate_y_plane( | ||
x_resolution=200, | ||
z_resolution=100, | ||
crossstream_dist=0.0, | ||
awc_modes=awc_modes, | ||
awc_amplitudes=awc_amplitudes | ||
) | ||
y_plane_helix = fmodel.calculate_y_plane( | ||
x_resolution=200, | ||
z_resolution=100, | ||
crossstream_dist=-3*D, | ||
awc_modes=awc_modes, | ||
awc_amplitudes=awc_amplitudes | ||
) | ||
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cross_plane = fmodel.calculate_cross_plane( | ||
y_resolution=100, | ||
z_resolution=100, | ||
downstream_dist=720.0, | ||
awc_modes=awc_modes, | ||
awc_amplitudes=awc_amplitudes | ||
) | ||
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# Create the plots | ||
fig, ax_list = plt.subplots(2, 2, figsize=(10, 8), tight_layout=True) | ||
ax_list = ax_list.flatten() | ||
flowviz.visualize_cut_plane( | ||
horizontal_plane, | ||
ax=ax_list[0], | ||
label_contours=True, | ||
title="Horizontal" | ||
) | ||
flowviz.visualize_cut_plane( | ||
cross_plane, | ||
ax=ax_list[2], | ||
label_contours=True, | ||
title="Spanwise profile at 3D" | ||
) | ||
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# fig2, ax_list2 = plt.subplots(2, 1, figsize=(10, 8), tight_layout=True) | ||
# ax_list2 = ax_list2.flatten() | ||
flowviz.visualize_cut_plane( | ||
y_plane_baseline, | ||
ax=ax_list[1], | ||
label_contours=True, | ||
title="Streamwise profile, helix" | ||
) | ||
flowviz.visualize_cut_plane( | ||
y_plane_helix, | ||
ax=ax_list[3], | ||
label_contours=True, | ||
title="Streamwise profile, baseline" | ||
) | ||
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# Calculate the effect of changing awc_amplitudes | ||
N = 50 | ||
awc_amplitudes = np.array([ | ||
np.linspace(0, 5, N), | ||
np.zeros(N), np.zeros(N), np.zeros(N) | ||
]).reshape(4, N).T | ||
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# Reset FlorisModel for different helix amplitudes | ||
fmodel.set( | ||
wind_directions=270 * np.ones(N), | ||
wind_speeds=8 * np.ones(N), | ||
turbulence_intensities=0.06*np.ones(N), | ||
awc_modes=awc_modes, | ||
awc_amplitudes=awc_amplitudes | ||
) | ||
fmodel.run() | ||
turbine_powers = fmodel.get_turbine_powers() | ||
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# Plot the power as a function of helix amplitude | ||
fig_power, ax_power = plt.subplots() | ||
ax_power.fill_between( | ||
awc_amplitudes[:, 0], | ||
0, | ||
turbine_powers[:, 0]/1000, | ||
color='C0', | ||
label='Turbine 1' | ||
) | ||
ax_power.fill_between( | ||
awc_amplitudes[:, 0], | ||
turbine_powers[:, 0]/1000, | ||
turbine_powers[:, :2].sum(axis=1)/1000, | ||
color='C1', | ||
label='Turbine 2' | ||
) | ||
ax_power.plot( | ||
awc_amplitudes[:, 0], | ||
turbine_powers[:,:2].sum(axis=1)/1000, | ||
color='k', | ||
label='Farm' | ||
) | ||
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ax_power.set_xlabel("Upstream turbine helix amplitude [deg]") | ||
ax_power.set_ylabel("Power [kW]") | ||
ax_power.legend() | ||
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flowviz.show() |
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name: Emperical Gaussian | ||
description: Three turbines using empirical Gaussian model | ||
floris_version: v4.0 | ||
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logging: | ||
console: | ||
enable: true | ||
level: WARNING | ||
file: | ||
enable: false | ||
level: WARNING | ||
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solver: | ||
type: turbine_grid | ||
turbine_grid_points: 3 | ||
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farm: | ||
layout_x: | ||
- 0.0 | ||
- 630.0 | ||
- 1260.0 | ||
layout_y: | ||
- 0.0 | ||
- 0.0 | ||
- 0.0 | ||
turbine_type: | ||
- iea_15MW | ||
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flow_field: | ||
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 | ||
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wake: | ||
model_strings: | ||
combination_model: sosfs | ||
deflection_model: empirical_gauss | ||
turbulence_model: wake_induced_mixing | ||
velocity_model: empirical_gauss | ||
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enable_secondary_steering: false | ||
enable_yaw_added_recovery: false | ||
enable_active_wake_mixing: true | ||
enable_transverse_velocities: false | ||
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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: 30 | ||
mixing_gain_deflection: 0.0 | ||
yaw_added_mixing_gain: 0.0 | ||
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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 | ||
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 | ||
awc_wake_exp: 1.2 | ||
awc_wake_denominator: 400 | ||
wake_turbulence_parameters: | ||
crespo_hernandez: | ||
initial: 0.1 | ||
constant: 0.5 | ||
ai: 0.8 | ||
downstream: -0.32 | ||
wake_induced_mixing: | ||
atmospheric_ti_gain: 0.0 |
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