Enable heterogeneous inflows in yaw optimization routines

[misi9170]

Neither Serial Refine nor the scipy minimize routine for yaw angle optimization currently work with a heterogeneous inflow (the issue for Serial Refine is identified in #673). This pull request addresses that.

Additionally, turbine.py is updated to allow power to be extrapolated outside of the specified range in the turbine input file. Sampling with a wind speed outside of the interpolation range returns a power of 0. Finally, a minor update is made to turbine.py to warn the user if the rotor_effective_velocities contains any negative entries, which can happen in situations where turbines are very close together.

To reproduce the existing error with heterogeneous inflows and yaw optimizations, run

# Copyright 2021 NREL

# 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

# 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.

# See https://floris.readthedocs.io for documentation

import numpy as np

from floris.tools import FlorisInterface
from floris.tools.optimization.yaw_optimization.yaw_optimizer_scipy import YawOptimizationScipy
from floris.tools.optimization.yaw_optimization.yaw_optimizer_sr import YawOptimizationSR


"""
This example showcases the heterogeneous inflow capabilities of FLORIS
when multiple wind speeds and direction are considered.
"""


# Define the speed ups of the heterogeneous inflow, and their locations.
# For the 2-dimensional case, this requires x and y locations.
# The speed ups are multipliers of the ambient wind speed.
x_locs = [-300.0, -300.0, 2600.0, 2600.0]
y_locs = [ -300.0, 300.0, -300.0, 300.0]

# Initialize FLORIS with the given input file via FlorisInterface.
# Note the heterogeneous inflow is defined in the input file.
#fi = FlorisInterface("inputs/gch_heterogeneous_inflow.yaml")
fi = FlorisInterface("inputs/gch.yaml")

# Set shear to 0.0 to highlight the heterogeneous inflow
fi.reinitialize(
    wind_shear=0.0,
    wind_speeds=[8.0],
    wind_directions=[270.],
    layout_x=[0, 0],
    layout_y=[-250., 250.],
)

# To change the number of wind directions however it is necessary to make a matching
# change to the dimensions of the het map
speed_multipliers = [[2.0, 1.0, 2.0, 1.0], [2.0, 1.0, 2.0, 1.0]] # Expand to two wind directions
heterogenous_inflow_config = {
    'speed_multipliers': speed_multipliers,
    'x': x_locs,
    'y': y_locs,
}
fi.reinitialize(
    wind_directions=[270.0, 180.0],
    wind_speeds=[8.0],
    heterogenous_inflow_config=heterogenous_inflow_config # Or, None
)
fi.calculate_wake()
turbine_powers = np.round(fi.get_turbine_powers() / 1000.)
print('With wind directions now set to 270 and 180 deg')
print(f'T0: {turbine_powers[:, :, 0].flatten()} kW')
print(f'T1: {turbine_powers[:, :, 1].flatten()} kW')

print("Serial refine:")
yaw_opt = YawOptimizationSR(
    fi=fi,
    minimum_yaw_angle=0.0,  # Allowable yaw angles lower bound
    maximum_yaw_angle=20.0,  # Allowable yaw angles upper bound
    Ny_passes=[5, 4],
    exclude_downstream_turbines=True,
    exploit_layout_symmetry=True,
)

df_opt = yaw_opt.optimize()
print(df_opt)


print("\nScipy optimize:")
yaw_opt = YawOptimizationScipy(
    fi=fi,
    minimum_yaw_angle=0.0,  # Allowable yaw angles lower bound
    maximum_yaw_angle=20.0,  # Allowable yaw angles upper bound
)

df_opt = yaw_opt.optimize()
print(df_opt)

As an example of a negative wind speed raising a power interpolation error, run

import numpy as np

from floris.tools import FlorisInterface

fi = FlorisInterface("inputs/emgauss.yaml")

fi.reinitialize(layout_x = [0, 5*126, 10*126], layout_y = [0, 0, 0], wind_speeds=[3])

# Alter initial wake width to something unreasonably low
fi_dict = fi.floris.as_dict()
fi_dict['wake']['wake_velocity_parameters']['empirical_gauss']\
    ['sigma_0_D'] = 0.01
fi = FlorisInterface(fi_dict)

fi.calculate_wake()

print(fi.get_turbine_powers()/1000)

Closes #673

Ready for review/merge.

[misi9170]

Also addresses #457 (earlier version of #673)

[misi9170]

Also addresses discussion #658

[rafmudaf]

@paulf81 Just checking in whether you want to review this one

[paulf81]

@misi9170 are going to review it together at 1130, thanks for checking!