Yaw optimization with disabled turbines

[MiguelMarante]

Hello everyone,

I want to implement yaw optimization for a time-series, taking into account that different turbines are not operational at different time records.

Below is an example for a time-series with two records: the mid-stream turbine is disabled in the first record, and the upstream turbine is disabled in the second. The results show that this information is ignored in the optimization procedure.

Is there a workaround to ensure these turbines are completely excluded from the optimization?

Note: I am using Floris v4.1 in this example.

Best regards,
Miguel Marante

CODE:

import numpy as np

from floris import FlorisModel
from floris.optimization.yaw_optimization.yaw_optimizer_sr import YawOptimizationSR

# Create floris object
yaml_file = 'inputs/emgauss.yaml'
fmodel = FlorisModel(yaml_file)

# Set wind conditions
fmodel.set(wind_directions=[270.]*2, wind_speeds=[8.]*2, turbulence_intensities=[.06]*2)

# Disable turbines
fmodel.set_operation_model('mixed')
fmodel.set(disable_turbines=np.array([[False, True, False], [True, False, False]]))

# Run optimization and print results
yaw_opt = YawOptimizationSR(fmodel)
df_opt = yaw_opt.optimize()
print(df_opt)