def test_power():
N_TURBINES = 4
AIR_DENSITY = 1.225
turbine_data = SampleInputs().turbine
turbine = Turbine.from_dict(turbine_data)
turbine_type_map = np.array(N_TURBINES * [turbine.turbine_type])
turbine_type_map = turbine_type_map[None, None, :]
# Single turbine
wind_speed = 10.0
p = power(
air_density=AIR_DENSITY,
velocities=wind_speed * np.ones((1, 1, 1, 3, 3)),
yaw_angle=np.zeros((1, 1, 1)),
pP=turbine.pP * np.ones((1, 1, 1)),
power_interp=np.array([(turbine.turbine_type, turbine.fCp_interp)]),
turbine_type_map=turbine_type_map[:,:,0]
)
# calculate power again
effective_velocity_trurth = ((AIR_DENSITY/1.225)**(1/3)) * wind_speed
truth_index = turbine_data["power_thrust_table"]["wind_speed"].index(effective_velocity_trurth)
cp_truth = turbine_data["power_thrust_table"]["power"][truth_index]
power_truth = 0.5 * turbine.rotor_area * cp_truth * turbine.generator_efficiency * effective_velocity_trurth ** 3
np.testing.assert_allclose(p,cp_truth,power_truth )
def test_regression_tandem(sample_inputs_fixture):
"""
Tandem turbines
"""
sample_inputs_fixture.floris["wake"]["model_strings"]["velocity_model"] = VELOCITY_MODEL
sample_inputs_fixture.floris["wake"]["model_strings"]["deflection_model"] = DEFLECTION_MODEL
sample_inputs_fixture.floris["wake"]["model_strings"]["combination_model"] = COMBINATION_MODEL
floris = Floris.from_dict(sample_inputs_fixture.floris)
floris.initialize_domain()
floris.steady_state_atmospheric_condition()
n_turbines = floris.farm.n_turbines
n_wind_speeds = floris.flow_field.n_wind_speeds
n_wind_directions = floris.flow_field.n_wind_directions
velocities = floris.flow_field.u
yaw_angles = floris.farm.yaw_angles
test_results = np.zeros((n_wind_directions, n_wind_speeds, n_turbines, 4))
farm_avg_velocities = average_velocity(
velocities,
)
farm_cts = Ct(
velocities,
yaw_angles,
floris.farm.turbine_fCts,
floris.farm.turbine_type_map,
)
farm_powers = power(
floris.flow_field.air_density,
velocities,
yaw_angles,
floris.farm.pPs,
floris.farm.turbine_power_interps,
floris.farm.turbine_type_map,
)
farm_axial_inductions = axial_induction(
velocities,
yaw_angles,
floris.farm.turbine_fCts,
floris.farm.turbine_type_map,
)
for i in range(n_wind_directions):
for j in range(n_wind_speeds):
for k in range(n_turbines):
test_results[i, j, k, 0] = farm_avg_velocities[i, j, k]
test_results[i, j, k, 1] = farm_cts[i, j, k]
test_results[i, j, k, 2] = farm_powers[i, j, k]
test_results[i, j, k, 3] = farm_axial_inductions[i, j, k]
if DEBUG:
print_test_values(
farm_avg_velocities,
farm_cts,
farm_powers,
farm_axial_inductions,
)
assert_results_arrays(test_results[0], baseline)
def test_regression_small_grid_rotation(sample_inputs_fixture):
"""
Where wake models are masked based on the x-location of a turbine, numerical precision
can cause masking to fail unexpectedly. For example, in the configuration here one of
the turbines has these delta x values;
[[4.54747351e-13 4.54747351e-13 4.54747351e-13 4.54747351e-13 4.54747351e-13]
[4.54747351e-13 4.54747351e-13 4.54747351e-13 4.54747351e-13 4.54747351e-13]
[4.54747351e-13 4.54747351e-13 4.54747351e-13 4.54747351e-13 4.54747351e-13]
[4.54747351e-13 4.54747351e-13 4.54747351e-13 4.54747351e-13 4.54747351e-13]
[4.54747351e-13 4.54747351e-13 4.54747351e-13 4.54747351e-13 4.54747351e-13]]
and therefore the masking statement is False when it should be True. This causes the current
turbine to be affected by its own wake. This test requires that at least in this particular
configuration the masking correctly filters grid points.
"""
sample_inputs_fixture.floris["wake"]["model_strings"]["velocity_model"] = VELOCITY_MODEL
sample_inputs_fixture.floris["wake"]["model_strings"]["deflection_model"] = DEFLECTION_MODEL
sample_inputs_fixture.floris["wake"]["model_strings"]["combination_model"] = COMBINATION_MODEL
X, Y = np.meshgrid(
6.0 * 126.0 * np.arange(0, 5, 1),
6.0 * 126.0 * np.arange(0, 5, 1)
)
X = X.flatten()
Y = Y.flatten()
sample_inputs_fixture.floris["farm"]["layout_x"] = X
sample_inputs_fixture.floris["farm"]["layout_y"] = Y
floris = Floris.from_dict(sample_inputs_fixture.floris)
floris.initialize_domain()
floris.steady_state_atmospheric_condition()
# farm_avg_velocities = average_velocity(floris.flow_field.u)
velocities = floris.flow_field.u
yaw_angles = floris.farm.yaw_angles
farm_powers = power(
floris.flow_field.air_density,
velocities,
yaw_angles,
floris.farm.pPs,
floris.farm.turbine_power_interps,
floris.farm.turbine_type_map,
)
# A "column" is oriented parallel to the wind direction
# Columns 1 - 4 should have the same power profile
# Column 5 leading turbine is completely unwaked
# and the rest of the turbines have a partial wake from their immediate upstream turbine
assert np.allclose(farm_powers[2,0,0:5], farm_powers[2,0,5:10])
assert np.allclose(farm_powers[2,0,0:5], farm_powers[2,0,10:15])
assert np.allclose(farm_powers[2,0,0:5], farm_powers[2,0,15:20])
assert np.allclose(farm_powers[2,0,20], farm_powers[2,0,0])
assert np.allclose(farm_powers[2,0,21], farm_powers[2,0,21:25])
def test_regression_secondary_steering(sample_inputs_fixture):
"""
Tandem turbines with the upstream turbine yawed and secondary steering enabled
"""
sample_inputs_fixture.floris["wake"]["model_strings"]["velocity_model"] = VELOCITY_MODEL
sample_inputs_fixture.floris["wake"]["model_strings"]["deflection_model"] = DEFLECTION_MODEL
sample_inputs_fixture.floris["wake"]["enable_transverse_velocities"] = True
sample_inputs_fixture.floris["wake"]["enable_secondary_steering"] = True
sample_inputs_fixture.floris["wake"]["enable_yaw_added_recovery"] = False
floris = Floris.from_dict(sample_inputs_fixture.floris)
yaw_angles = np.zeros((N_WIND_DIRECTIONS, N_WIND_SPEEDS, N_TURBINES))
yaw_angles[:,:,0] = 5.0
floris.farm.yaw_angles = yaw_angles
floris.initialize_domain()
floris.steady_state_atmospheric_condition()
n_turbines = floris.farm.n_turbines
n_wind_speeds = floris.flow_field.n_wind_speeds
n_wind_directions = floris.flow_field.n_wind_directions
velocities = floris.flow_field.u
yaw_angles = floris.farm.yaw_angles
test_results = np.zeros((n_wind_directions, n_wind_speeds, n_turbines, 4))
farm_avg_velocities = average_velocity(
velocities,
)
farm_cts = Ct(
velocities,
yaw_angles,
floris.farm.turbine_fCts,
floris.farm.turbine_type_map,
)
farm_powers = power(
floris.flow_field.air_density,
velocities,
yaw_angles,
floris.farm.pPs,
floris.farm.turbine_power_interps,
floris.farm.turbine_type_map,
)
farm_axial_inductions = axial_induction(
velocities,
yaw_angles,
floris.farm.turbine_fCts,
floris.farm.turbine_type_map,
)
for i in range(n_wind_directions):
for j in range(n_wind_speeds):
for k in range(n_turbines):
test_results[i, j, k, 0] = farm_avg_velocities[i, j, k]
test_results[i, j, k, 1] = farm_cts[i, j, k]
test_results[i, j, k, 2] = farm_powers[i, j, k]
test_results[i, j, k, 3] = farm_axial_inductions[i, j, k]
if DEBUG:
print_test_values(
farm_avg_velocities,
farm_cts,
farm_powers,
farm_axial_inductions,
)
assert_results_arrays(test_results[0], secondary_steering_baseline)
