import os
import numpy as np
from matplotlib import pyplot as plt
import wflopg
import wflopg.visualization as vis
os.chdir("../../../documents/IEA37_CS1+2/")
plt.rc('text', usetex=True)
plt.rc('font', family='serif', serif='Times')
plt.rc('axes', titlesize=10)
# %% set up problem
o = wflopg.Owflop()
o.load_problem("problem-IEA37_Optimization_Case_Study-small.yaml",
wind_resource="wind_resource-from_West.yaml")
o.calculate_wakeless_power()
o.calculate_deficit()
o.calculate_power()
o.calculate_relative_wake_loss_vector()
# %% save initial layout figure
fig = plt.figure()
ax = plt.subplot(111)
vis.site_setup(ax, o.minimal_proximity)
vis.draw_boundaries(ax, o.boundaries)
vis.draw_turbines(ax, o._ds.layout, o.rotor_radius_adim, o.minimal_proximity)
fig.savefig('IEA37C1W_16-layout_initial.pdf', bbox_inches="tight")
'iterations': 30,
'kwargs': {
'multiplier': 1.3,
'scaling': [.5, .99]
}
},
64: {
'size': "large",
'iterations': 30,
'kwargs': {
'multiplier': 3,
'scaling': [.9, 2]
}
}
}.items():
os[n] = wflopg.Owflop()
os[n].load_problem(
f"problem-IEA37_Optimization_Case_Study-{params['size']}.yaml")
os[n].calculate_wakeless_power()
histories[n] = opt.step_iterator(os[n],
max_iterations=params['iterations'],
**params['kwargs'])
# %% create and save figure giving overview of optimizations
fig = plt.figure(figsize=(3.4, 5.))
gs = fig.add_gridspec(ncols=2,
nrows=3,
wspace=0.,
hspace=0.,
width_ratios=[1] * 2,
height_ratios=[1.1, .9, .9])