def test_initialization_4(self, recwarn):
"""test overwriting and raising warning when number_of_turbines and
total_capacity in wind turbine fleet do not fit"""
wt1 = WindTurbine(**self.test_turbine)
wt2 = WindTurbine(**self.test_turbine_2)
wind_turbine_fleet = pd.DataFrame(
data={
"wind_turbine": [wt1, wt2],
"number_of_turbines": [3, 2],
"total_capacity": [3, np.nan],
},
index=[0, 1],
)
windfarm = WindFarm(wind_turbine_fleet=wind_turbine_fleet)
total_cap_wt1_expected = (
wt1.nominal_power *
wind_turbine_fleet.loc[0, "number_of_turbines"])
assert (windfarm.wind_turbine_fleet.loc[0, "total_capacity"] ==
total_cap_wt1_expected)
total_cap_wt2_expected = (
wt2.nominal_power *
wind_turbine_fleet.loc[1, "number_of_turbines"])
assert (windfarm.wind_turbine_fleet.loc[1, "total_capacity"] ==
total_cap_wt2_expected)
assert recwarn.pop(WindpowerlibUserWarning)
def initialise_wind_turbines():
r"""
Initialises two :class:`~.wind_turbine.WindTurbine` objects.
Function shows two ways to initialise a WindTurbine object. You can either
specify your own turbine, as done below for 'myTurbine', or fetch power
and/or power coefficient curve data from data files provided by the
windpowerlib, as done for the 'enerconE126'.
Execute ``windpowerlib.wind_turbine.get_turbine_types()`` or
``windpowerlib.wind_turbine.get_turbine_types(
filename='power_coefficient_curves.csv')`` to get a list of all wind
turbines for which power and power coefficient curves respectively are
provided.
Returns
-------
Tuple (WindTurbine, WindTurbine)
"""
# specification of own wind turbine (Note: power coefficient values and
# nominal power have to be in Watt)
myTurbine = {
'turbine_name':
'myTurbine',
'nominal_power':
3e6, # in W
'hub_height':
105, # in m
'rotor_diameter':
90, # in m
'power_curve':
pd.DataFrame(
data={
'values':
[p * 1000
for p in [0.0, 26.0, 180.0, 1500.0, 3000.0, 3000.0]], # in W
'wind_speed': [0.0, 3.0, 5.0, 10.0, 15.0, 25.0]
}) # in m/s
}
# initialise WindTurbine object
my_turbine = WindTurbine(**myTurbine)
# specification of wind turbine where power curve is provided
# if you want to use the power coefficient curve change the value of
# 'fetch_curve' to 'power_coefficient_curve'
enerconE126 = {
'turbine_name': 'ENERCON E 126 7500', # turbine name as in register
'hub_height': 135, # in m
'rotor_diameter': 127, # in m
'fetch_curve': 'power_curve' # fetch power curve
}
# initialise WindTurbine object
e126 = WindTurbine(**enerconE126)
return my_turbine, e126
def test_initialization_dataframe(self):
"""test simple initialization with wind turbine fleet dataframe"""
wind_turbine_fleet = pd.DataFrame(
data={
'wind_turbine': [
WindTurbine(**self.test_turbine),
WindTurbine(**self.test_turbine_2)
],
'number_of_turbines': [3, 2]
})
windfarm = WindFarm(wind_turbine_fleet=wind_turbine_fleet)
assert 3 * 4.2e6 + 2 * 2e6 == windfarm.nominal_power
def test_initialization_list(self):
"""test simple initialization with wind turbine fleet list"""
wind_turbine_fleet = [{
'wind_turbine': WindTurbine(**self.test_turbine),
'number_of_turbines': 3
}, {
'wind_turbine':
WindTurbine(**self.test_turbine_2),
'number_of_turbines':
2
}]
windfarm = WindFarm(wind_turbine_fleet=wind_turbine_fleet)
assert 3 * 4.2e6 + 2 * 2e6 == windfarm.nominal_power
def test_initialization_5(self):
"""test catching error when number of turbines cannot be deduced"""
wt = WindTurbine(**self.test_turbine)
wt.nominal_power = None
test_farm = {
"wind_turbine_fleet": [{
"wind_turbine": wt,
"total_capacity": 3e6
}]
}
msg = "Number of turbines of type"
with pytest.raises(ValueError, match=msg):
WindFarm(**test_farm)
def test_initialization_7(self):
"""test catching error when total capacity cannot be deduced"""
wt = WindTurbine(**self.test_turbine)
wt.nominal_power = None
test_farm = {
'wind_turbine_fleet': [{
'wind_turbine': wt,
'number_of_turbines': 3
}]
}
msg = 'Total capacity of turbines of type'
with pytest.raises(ValueError, match=msg):
WindFarm(**test_farm)
def initialize_wind_turbines():
r"""
Initializes three :class:`~.wind_turbine.WindTurbine` objects.
This function shows three ways to initialize a WindTurbine object. You can
either use turbine data from the OpenEnergy Database (oedb) turbine library
that is provided along with the windpowerlib, as done for the
'enercon_e126', or specify your own turbine by directly providing a power
(coefficient) curve, as done below for 'my_turbine', or provide your own
turbine data in csv files, as done for 'dummy_turbine'.
To get a list of all wind turbines for which power and/or power coefficient
curves are provided execute `
`windpowerlib.wind_turbine.get_turbine_types()``.
Returns
-------
Tuple (:class:`~.wind_turbine.WindTurbine`,
:class:`~.wind_turbine.WindTurbine`,
:class:`~.wind_turbine.WindTurbine`)
"""
# ************************************************************************
# **** Data is provided in the oedb turbine library **********************
enercon_e126 = {
"turbine_type": "E-126/4200", # turbine type as in register
"hub_height": 135, # in m
}
e126 = WindTurbine(**enercon_e126)
# ************************************************************************
# **** Specification of wind turbine with your own data ******************
# **** NOTE: power values and nominal power have to be in Watt
my_turbine = {
"nominal_power":
3e6, # in W
"hub_height":
105, # in m
"power_curve":
pd.DataFrame(
data={
"value":
[p * 1000
for p in [0.0, 26.0, 180.0, 1500.0, 3000.0, 3000.0]], # in W
"wind_speed": [0.0, 3.0, 5.0, 10.0, 15.0, 25.0],
}), # in m/s
}
my_turbine = WindTurbine(**my_turbine)
return my_turbine, e126
def test_initialization_3(self):
"""test catching error when wind_turbine not specified in
wind_turbine_fleet"""
wind_turbine_fleet = pd.DataFrame(
data={
'wind_turbines': [
WindTurbine(**self.test_turbine),
WindTurbine(**self.test_turbine_2)
],
'number_of_turbines': [3, 2]
})
msg = 'Missing wind_turbine key/column in wind_turbine_fleet'
with pytest.raises(KeyError, match=msg):
WindFarm(wind_turbine_fleet=wind_turbine_fleet)
def test_initialization_list_2(self):
"""test simple initialization with wind turbine fleet list where
once number of turbines and once total capacity is provided"""
wind_turbine_fleet = [{
'wind_turbine': WindTurbine(**self.test_turbine),
'number_of_turbines': 3
}, {
'wind_turbine':
WindTurbine(**self.test_turbine_2),
'total_capacity':
2 * 2e6
}]
windfarm = WindFarm(wind_turbine_fleet=wind_turbine_fleet)
assert 3 * 4.2e6 + 2 * 2e6 == windfarm.nominal_power
def test_repr(self):
"""Test string representation of WindFarm"""
test_fleet = [{
'wind_turbine': WindTurbine(**self.test_turbine),
'number_of_turbines': 2
}]
assert 'E-126/4200' in repr(WindFarm(wind_turbine_fleet=test_fleet))
def get_wind_turbine(self):
r"""
fetch power and/or power coefficient curve data from the OpenEnergy
Database (oedb)
Execute ``windpowerlib.wind_turbine.get_turbine_types()`` to get a table
including all wind turbines for which power and/or power coefficient curves
are provided.
Returns
-------
WindTurbine
"""
# specification of wind turbine where power curve is provided in the oedb
# if you want to use the power coefficient curve change the value of
# 'fetch_curve' to 'power_coefficient_curve'
wind_turbine = {
'turbine_type': self.turbine_type, # turbine type as in register
'hub_height': self.hub_height, # in m
'rotor_diameter': self.rotor_diameter, # in m
'fetch_curve': self.fetch_curve, # fetch power curve
'data_source':
self.data_source # data source oedb or name of csv file
}
# initialize WindTurbine object
self.wind_turbine = WindTurbine(**wind_turbine)
return self.wind_turbine
def test_repr(self):
"""Test string representation of WindFarm"""
test_fleet = [{
"wind_turbine": WindTurbine(**self.test_turbine),
"number_of_turbines": 2,
}]
assert "E-126/4200" in repr(WindFarm(wind_turbine_fleet=test_fleet))
def test_aggregation_of_power_curve_with_missing_power_curve(self):
"""Test WindFarm.assign_power_curve() with missing power_curve."""
wt1 = WindTurbine(**self.test_turbine)
wt1.power_curve = None
wind_turbine_fleet = [{
'wind_turbine': wt1,
'number_of_turbines': 3
}, {
'wind_turbine':
WindTurbine(**self.test_turbine_2),
'number_of_turbines':
2
}]
windfarm = WindFarm(wind_turbine_fleet=wind_turbine_fleet)
msg = 'For an aggregated wind farm power curve each wind'
with pytest.raises(ValueError, match=msg):
windfarm.assign_power_curve()
def test_mean_hub_height(self):
"""tests mean_hub_height method"""
test_farm = {
"wind_turbine_fleet": [
{
"wind_turbine": WindTurbine(**self.test_turbine),
"number_of_turbines": 2,
},
{
"wind_turbine": WindTurbine(**self.test_turbine_2),
"total_capacity": 3e6,
},
]
}
windfarm = WindFarm(**test_farm)
assert 97.265 == pytest.approx(windfarm.mean_hub_height().hub_height,
1e-3)
def test_mean_hub_height(self):
"""tests mean_hub_height method"""
test_farm = {
'wind_turbine_fleet': [{
'wind_turbine':
WindTurbine(**self.test_turbine),
'number_of_turbines':
2
}, {
'wind_turbine':
WindTurbine(**self.test_turbine_2),
'total_capacity':
3e6
}]
}
windfarm = WindFarm(**test_farm)
assert 97.265 == pytest.approx(windfarm.mean_hub_height().hub_height,
1e-3)
def test_wind_farm_efficiency_with_missing_efficiency(self):
"""Test WindFarm.assign_power_curve() with missing efficiency while
`wake_losses_model` is 'wind_farm_efficiency'."""
wind_turbine_fleet = [{
"wind_turbine": WindTurbine(**self.test_turbine),
"number_of_turbines": 3,
}]
windfarm = WindFarm(wind_turbine_fleet=wind_turbine_fleet)
msg = "If you use `wake_losses_model`"
with pytest.raises(ValueError, match=msg):
windfarm.assign_power_curve()
def test_initialization_4(self, recwarn):
"""test overwriting and raising warning when number_of_turbines and
total_capacity in wind turbine fleet do not fit"""
wt1 = WindTurbine(**self.test_turbine)
wt2 = WindTurbine(**self.test_turbine_2)
wind_turbine_fleet = pd.DataFrame(data={
'wind_turbine': [wt1, wt2],
'number_of_turbines': [3, 2],
'total_capacity': [3, np.nan]
},
index=[0, 1])
windfarm = WindFarm(wind_turbine_fleet=wind_turbine_fleet)
total_cap_wt1_expected = \
wt1.nominal_power * wind_turbine_fleet.loc[0, 'number_of_turbines']
assert windfarm.wind_turbine_fleet.loc[0, 'total_capacity'] == \
total_cap_wt1_expected
total_cap_wt2_expected = \
wt2.nominal_power * wind_turbine_fleet.loc[1, 'number_of_turbines']
assert windfarm.wind_turbine_fleet.loc[1, 'total_capacity'] == \
total_cap_wt2_expected
assert recwarn.pop(WindpowerlibUserWarning)
def test_initialization_6(self):
"""test catching error when neither number_of_turbines nor
total_capacity is provided"""
test_farm = {
'wind_turbine_fleet': [{
'wind_turbine':
WindTurbine(**self.test_turbine),
'number_of_turbine':
3e6
}]
}
msg = 'Number of turbines of type '
with pytest.raises(ValueError, match=msg):
WindFarm(**test_farm)
3e6, # in W
'hub_height':
105, # in m
'rotor_diameter':
90, # in m
'power_curve':
pd.DataFrame(
data={
'value':
[p * 1000
for p in [0.0, 26.0, 180.0, 1500.0, 3000.0, 3000.0]], # in W
'wind_speed': [0.0, 3.0, 5.0, 10.0, 15.0, 25.0]
}) # in m/s
}
# initialize WindTurbine object
my_turbine = WindTurbine(**my_turbine)
# specification of wind turbine where power curve is provided
# if you want to use the power coefficient curve change the value of
# 'fetch_curve' to 'power_coefficient_curve'
enercon_e126 = {
'name': 'E-126/4200', # turbine name as in register
'hub_height': 135, # in m
'rotor_diameter': 127, # in m
'fetch_curve': 'power_curve', # fetch power curve #
'data_source': 'oedb' # data source oedb or name of csv file
}
# initialize WindTurbine object
e126 = WindTurbine(**enercon_e126)
##########################################################################
def initialize_wind_turbines():
r"""
Initializes three :class:`~.wind_turbine.WindTurbine` objects.
This function shows three ways to initialize a WindTurbine object. You can
either use turbine data from the OpenEnergy Database (oedb) turbine library
that is provided along with the windpowerlib, as done for the
'enercon_e126', or specify your own turbine by directly providing a power
(coefficient) curve, as done below for 'my_turbine', or provide your own
turbine data in csv files, as done for 'dummy_turbine'.
To get a list of all wind turbines for which power and/or power coefficient
curves are provided execute `
`windpowerlib.wind_turbine.get_turbine_types()``.
Returns
-------
Tuple (:class:`~.wind_turbine.WindTurbine`,
:class:`~.wind_turbine.WindTurbine`,
:class:`~.wind_turbine.WindTurbine`)
"""
# specification of wind turbine where data is provided in the oedb
# turbine library
enercon_e126 = {
'turbine_type': 'E-126/4200', # turbine type as in register
'hub_height': 135 # in m
}
# initialize WindTurbine object
e126 = WindTurbine(**enercon_e126)
# specification of own wind turbine (Note: power values and nominal power
# have to be in Watt)
my_turbine = {
'nominal_power':
3e6, # in W
'hub_height':
105, # in m
'power_curve':
pd.DataFrame(
data={
'value':
[p * 1000
for p in [0.0, 26.0, 180.0, 1500.0, 3000.0, 3000.0]], # in W
'wind_speed': [0.0, 3.0, 5.0, 10.0, 15.0, 25.0]
}) # in m/s
}
# initialize WindTurbine object
my_turbine = WindTurbine(**my_turbine)
# specification of wind turbine where power coefficient curve and nominal
# power is provided in an own csv file
csv_path = os.path.join(os.path.dirname(__file__), 'data')
dummy_turbine = {
'turbine_type': "DUMMY 1",
'hub_height': 100, # in m
'rotor_diameter': 70, # in m
'path': csv_path
}
# initialize WindTurbine object
dummy_turbine = WindTurbine(**dummy_turbine)
return my_turbine, e126, dummy_turbine
def __init__(
self,
wind_turbines: list = [],
pv_arrays: list = [],
latitude: float = 57.6568,
longitude: float = -3.5818,
altitude: float = 10,
roughness_length: float = 0.15, # roughness length (bit of a guess)
hellman_exp: float = 0.2):
""" Set up the renewable energy generation
"""
# This needs to be repeated in every forecast
self.roughness_length = roughness_length
# Initialise empty forecast dataframe, just so nothing complains
self.wind_forecast = pd.DataFrame()
self.pv_forecast = pd.DataFrame()
# Wind turbine(s)
turbines = []
for turbine in wind_turbines:
turbines.append({
'wind_turbine':
WindTurbine(turbine['name'],
turbine['hub_height'],
nominal_power=turbine['nominal_power'],
rotor_diameter=turbine['rotor_diameter'],
power_curve=turbine['power_curve']),
'number_of_turbines':
turbine['qty']
})
local_wind_farm = WindFarm('Local windfarm', turbines,
[latitude, longitude])
# TODO - check for learned local data & overwrite power_curve
self.wind_modelchain = TurbineClusterModelChain(
local_wind_farm,
smoothing=False,
hellman_exp=hellman_exp,
)
# Initialise PV models
self.pv_location = Location(latitude=latitude,
longitude=longitude,
altitude=altitude)
# Now set up the PV array & system.
cec_pv_model_params = pvlib.pvsystem.retrieve_sam('CECMod')
sandia_pv_model_params = pvlib.pvsystem.retrieve_sam('SandiaMod')
cec_inverter_model_params = pvlib.pvsystem.retrieve_sam('CECInverter')
adr_inverter_model_params = pvlib.pvsystem.retrieve_sam('ADRInverter')
self.pv_modelchains = {}
for pv_array in pv_arrays:
# Try to find the module names in the libraries
if pv_array['module_name'] in cec_pv_model_params:
pv_array['module_parameters'] = cec_pv_model_params[
pv_array['module_name']]
elif pv_array['module_name'] in sandia_pv_model_params:
pv_array['module_parameters'] = sandia_pv_model_params[
pv_array['module_name']]
else:
raise RenewablesException('Could not retrieve PV module data')
# Do the same with the inverter(s)
if pv_array['inverter_name'] in cec_inverter_model_params:
pv_array['inverter_parameters'] = cec_inverter_model_params[
pv_array['inverter_name']]
elif pv_array['inverter_name'] in adr_inverter_model_params:
pv_array['inverter_parameters'] = adr_inverter_model_params[
pv_array['inverter_name']]
else:
raise RenewablesException('Could not retrieve PV module data')
self.pv_modelchains[pv_array['name']] = ModelChain(
PVSystem(**pv_array),
self.pv_location,
aoi_model='physical',
spectral_model='no_loss')
def initialize_wind_turbines():
r"""
Initializes three :class:`~.wind_turbine.WindTurbine` objects.
This function shows three ways to initialize a WindTurbine object. You can
either use turbine data from the OpenEnergy Database (oedb) turbine library
that is provided along with the windpowerlib, as done for the
'enercon_e126', or specify your own turbine by directly providing a power
(coefficient) curve, as done below for 'my_turbine', or provide your own
turbine data in csv files, as done for 'my_turbine2'.
To get a list of all wind turbines for which power and/or power coefficient
curves are provided execute `
`windpowerlib.wind_turbine.get_turbine_types()``.
Returns
-------
Tuple (:class:`~.wind_turbine.WindTurbine`,
:class:`~.wind_turbine.WindTurbine`,
:class:`~.wind_turbine.WindTurbine`)
"""
# ************************************************************************
# **** Data is provided in the oedb turbine library **********************
enercon_e126 = {
"turbine_type": "E-126/4200", # turbine type as in register
"hub_height": 135, # in m
}
e126 = WindTurbine(**enercon_e126)
# ************************************************************************
# **** Specification of wind turbine with your own data ******************
# **** NOTE: power values and nominal power have to be in Watt
my_turbine = {
"nominal_power":
3e6, # in W
"hub_height":
105, # in m
"power_curve":
pd.DataFrame(
data={
"value":
[p * 1000
for p in [0.0, 26.0, 180.0, 1500.0, 3000.0, 3000.0]], # in W
"wind_speed": [0.0, 3.0, 5.0, 10.0, 15.0, 25.0],
}), # in m/s
}
my_turbine = WindTurbine(**my_turbine)
# ************************************************************************
# **** Specification of wind turbine with data in own file ***************
# Read your turbine data from your data file using functions like
# pandas.read_csv().
# >>> import pandas as pd
# >>> my_data = pd.read_csv("path/to/my/data/file")
# >>> my_power = my_data["my_power"]
# >>> my_wind_speed = my_data["my_wind_speed"]
my_power = pd.Series(
[0.0, 39000.0, 270000.0, 2250000.0, 4500000.0, 4500000.0])
my_wind_speed = (0.0, 3.0, 5.0, 10.0, 15.0, 25.0)
my_turbine2 = {
"nominal_power":
6e6, # in W
"hub_height":
115, # in m
"power_curve":
create_power_curve(wind_speed=my_wind_speed, power=my_power),
}
my_turbine2 = WindTurbine(**my_turbine2)
return my_turbine, e126, my_turbine2
def initialize_wind_turbines():
r"""
Initializes two :class:`~.wind_turbine.WindTurbine` objects.
Function shows three ways to initialize a WindTurbine object. You can
either specify your own turbine, as done below for 'my_turbine', or fetch
power and/or power coefficient curve data from the OpenEnergy Database
(oedb), as done for the 'enercon_e126', or provide your turbine data in csv
files as done for 'dummy_turbine' with an example file.
Execute ``windpowerlib.wind_turbine.get_turbine_types()`` to get a table
including all wind turbines for which power and/or power coefficient curves
are provided.
Returns
-------
Tuple (WindTurbine, WindTurbine, WindTurbine)
"""
# specification of own wind turbine (Note: power values and nominal power
# have to be in Watt)
my_turbine = {
'name':
'myTurbine',
'nominal_power':
3e6, # in W
'hub_height':
105, # in m
'rotor_diameter':
90, # in m
'power_curve':
pd.DataFrame(
data={
'value':
[p * 1000
for p in [0.0, 26.0, 180.0, 1500.0, 3000.0, 3000.0]], # in W
'wind_speed': [0.0, 3.0, 5.0, 10.0, 15.0, 25.0]
}) # in m/s
}
# initialize WindTurbine object
my_turbine = WindTurbine(**my_turbine)
# specification of wind turbine where power curve is provided in the oedb
# if you want to use the power coefficient curve change the value of
# 'fetch_curve' to 'power_coefficient_curve'
enercon_e126 = {
'name': 'E-126/4200', # turbine type as in register #
'hub_height': 135, # in m
'rotor_diameter': 127, # in m
'fetch_curve': 'power_curve', # fetch power curve #
'data_source': 'oedb' # data source oedb or name of csv file
}
# initialize WindTurbine object
e126 = WindTurbine(**enercon_e126)
# specification of wind turbine where power coefficient curve is provided
# by a csv file
csv_file = os.path.join(os.path.dirname(__file__), 'data',
'example_power_coefficient_curves.csv')
dummy_turbine = {
'name': 'DUMMY 1', # turbine type as in file #
'hub_height': 100, # in m
'rotor_diameter': 70, # in m
'fetch_curve': 'power_coefficient_curve', # fetch cp curve #
'data_source': csv_file # data source
}
# initialize WindTurbine object
dummy_turbine = WindTurbine(**dummy_turbine)
return my_turbine, e126, dummy_turbine