def test_to_weibull_array(self):
wwr = WeibullWindRoseVT()
self.random_fill_up(wwr)
arr = wwr.to_weibull_array()
assert_array_almost_equal(arr[:, 0], wwr.wind_directions)
assert_array_almost_equal(arr[:, 1], wwr.frequency)
assert_array_almost_equal(arr[:, 2], wwr.A)
assert_array_almost_equal(arr[:, 3], wwr.k)
assert_almost_equal(arr[:, 1].sum(), 1.0)
def test_to_weibull_array(self):
wwr = WeibullWindRoseVT()
self.random_fill_up(wwr)
arr = wwr.to_weibull_array()
assert_array_almost_equal(arr[:, 0], wwr.wind_directions)
assert_array_almost_equal(arr[:, 1], wwr.frequency)
assert_array_almost_equal(arr[:, 2], wwr.A)
assert_array_almost_equal(arr[:, 3], wwr.k)
assert_almost_equal(arr[:, 1].sum(), 1.0)
class PlantFromWWH(Component):
"""Create a Plant information from a .wwh WAsP file"""
# Inputs
filename = Str(iotype='in', desc='The .wwh file name')
# Outputs
wt_layout = VarTree(GenericWindFarmTurbineLayout(),
iotype='out',
desc='wind turbine properties and layout')
#wind_rose_array = Array(iotype='out', units='m/s',
# desc='Windrose array [wind_directions, frequency, weibull_A, weibull_k]')
wind_rose_vt = VarTree(WeibullWindRoseVT(),
iotype='out',
desc='wind turbine Weibull wind rose')
def __init__(self, filename=None):
"""
The constructor that can take the wwh filename as optional parameter.
:param filename: wwh file name [optional]
:return: self
"""
super(PlantFromWWH, self).__init__()
if filename is not None:
self.filename = filename
self.execute()
def execute(self):
# Reading the .wwf file
wwh = WWH(self.filename)
iWT = 0
for wt, data in wwh.wind_turbines.iteritems():
turbine = wwh.turbine_descriptions[data['type']]
self.wt_layout.add_wt(
WTPC(name='wt_' + wt,
position=data['position'][:2],
wind_rose=GenericWindRoseVT(
weibull_array=data['wind_rose']),
power_curve=turbine['data'][:, :2],
power_rating=max(turbine['data'][:, 1]),
c_t_curve=turbine['data'][:, [0, 2]],
cut_in_wind_speed=turbine['data'][0, 0],
cut_out_wind_speed=turbine['data'][-1, 0],
air_density=turbine['density'],
rotor_diameter=turbine['rotor_diameter'],
hub_height=data['position'][2]))
self.wind_rose_vt.add(
'wt_' + wt, VarTree((WeibullWindRoseVT(data['wind_rose']))))
def execute(self):
# Reading the .wwf file
wwh = WWH(self.filename)
iWT = 0
for wt, data in wwh.wind_turbines.iteritems():
turbine = wwh.turbine_descriptions[data['type']]
self.wt_layout.add_wt(
WTPC(name='wt_' + wt,
position=data['position'][:2],
wind_rose=GenericWindRoseVT(
weibull_array=data['wind_rose']),
power_curve=turbine['data'][:, :2],
power_rating=max(turbine['data'][:, 1]),
c_t_curve=turbine['data'][:, [0, 2]],
cut_in_wind_speed=turbine['data'][0, 0],
cut_out_wind_speed=turbine['data'][-1, 0],
air_density=turbine['density'],
rotor_diameter=turbine['rotor_diameter'],
hub_height=data['position'][2]))
self.wind_rose_vt.add(
'wt_' + wt, VarTree((WeibullWindRoseVT(data['wind_rose']))))
# The wind rose
weibull_array = np.array(
[[0.00000000e+00, 3.59673400e-02, 9.22422800e+00, 2.38867200e+00],
[3.00000000e+01, 3.94977300e-02, 9.86435600e+00, 2.44726600e+00],
[6.00000000e+01, 5.17838000e-02, 9.65220200e+00, 2.41992200e+00],
[9.00000000e+01, 6.99794900e-02, 9.98217800e+00, 2.58789100e+00],
[1.20000000e+02, 8.36383000e-02, 1.00946000e+01, 2.74804700e+00],
[1.50000000e+02, 6.43412500e-02, 9.64369000e+00, 2.59179700e+00],
[1.80000000e+02, 8.64220000e-02, 9.63377500e+00, 2.58007800e+00],
[2.10000000e+02, 1.17690000e-01, 1.05678600e+01, 2.54492200e+00],
[2.40000000e+02, 1.51555100e-01, 1.14525200e+01, 2.46679700e+00],
[2.70000000e+02, 1.47361100e-01, 1.17423700e+01, 2.60351600e+00],
[3.00000000e+02, 1.00109800e-01, 1.16923200e+01, 2.62304700e+00],
[3.30000000e+02, 5.16542400e-02, 1.01385800e+01, 2.32226600e+00]])
wind_rose = WeibullWindRoseVT()
wind_rose.wind_directions = weibull_array[:, 0]
wind_rose.frequency = weibull_array[:, 1]
wind_rose.k = weibull_array[:, 3]
wind_rose.A = weibull_array[:, 2]
# Minimum distance between turbines
dist_WT_D = 3.0
# #### Plotting the depth
# Some matplotlib options
# In[4]:
#get_ipython().magic(u'matplotlib inline')
# The wind rose
weibull_array = np.array([[ 0.00000000e+00, 3.59673400e-02, 9.22422800e+00, 2.38867200e+00],
[ 3.00000000e+01, 3.94977300e-02, 9.86435600e+00, 2.44726600e+00],
[ 6.00000000e+01, 5.17838000e-02, 9.65220200e+00, 2.41992200e+00],
[ 9.00000000e+01, 6.99794900e-02, 9.98217800e+00, 2.58789100e+00],
[ 1.20000000e+02, 8.36383000e-02, 1.00946000e+01, 2.74804700e+00],
[ 1.50000000e+02, 6.43412500e-02, 9.64369000e+00, 2.59179700e+00],
[ 1.80000000e+02, 8.64220000e-02, 9.63377500e+00, 2.58007800e+00],
[ 2.10000000e+02, 1.17690000e-01, 1.05678600e+01, 2.54492200e+00],
[ 2.40000000e+02, 1.51555100e-01, 1.14525200e+01, 2.46679700e+00],
[ 2.70000000e+02, 1.47361100e-01, 1.17423700e+01, 2.60351600e+00],
[ 3.00000000e+02, 1.00109800e-01, 1.16923200e+01, 2.62304700e+00],
[ 3.30000000e+02, 5.16542400e-02, 1.01385800e+01, 2.32226600e+00]])
wind_rose = WeibullWindRoseVT()
wind_rose.wind_directions = weibull_array[:,0]
wind_rose.frequency = weibull_array[:,1]
wind_rose.k = weibull_array[:,3]
wind_rose.A = weibull_array[:,2]
# Minimum distance between turbines
dist_WT_D = 3.0
# #### Plotting the depth
# Some matplotlib options
# In[4]:
def test_df(self):
wwr = WeibullWindRoseVT()
self.random_fill_up(wwr)
df = wwr.df()
self.assertEqual(df.columns.tolist(), ["wind_direction", "frequency", "A", "k"])
def test_df(self):
wwr = WeibullWindRoseVT()
self.random_fill_up(wwr)
df = wwr.df()
self.assertEqual(df.columns.tolist(),
['wind_direction', 'frequency', 'A', 'k'])