def test_add_strat_tes_calculate_losses_saved_file(self):
original_storage_xx_data = pd.read_csv(
self.filename_storage_xx, header=0, index_col=0
)
sts.add_strat_tes(
weather=self.weather,
lat=self.lat,
lon=self.lon,
user_inputs_pvcompare_directory=TEST_USER_INPUTS_PVCOMPARE,
user_inputs_mvs_directory=TEST_USER_INPUTS_MVS_SECTOR_COUPLING,
overwrite_tes_parameters=False,
)
assert os.path.exists(
os.path.join(
TEST_USER_INPUTS_MVS_SECTOR_COUPLING,
"time_series",
"fixed_thermal_losses_absolute_2017_53.2_13.2_40.0.csv",
)
)
assert os.path.exists(
os.path.join(
TEST_USER_INPUTS_MVS_SECTOR_COUPLING,
"time_series",
"fixed_thermal_losses_relative_2017_53.2_13.2_40.0.csv",
)
)
original_storage_xx_data.to_csv(self.filename_storage_xx, na_rep="NaN")
def test_add_sector_coupling_strat_tes_file_non_existent(self, select_conv_tech):
original_storage_xx_data = pd.read_csv(
self.filename_storage_xx, header=0, index_col=0
)
select_conv_tech(columns="storage capacity")
sts.add_strat_tes(
weather=self.weather_2017,
lat=self.lat,
lon=self.lon,
user_inputs_pvcompare_directory=TEST_USER_INPUTS_PVCOMPARE,
user_inputs_mvs_directory=TEST_USER_INPUTS_MVS_SECTOR_COUPLING,
overwrite_tes_parameters=False,
)
# no file created
filename = os.path.join(
TEST_USER_INPUTS_MVS_SECTOR_COUPLING,
"time_series",
"fixed_thermal_losses_absolute_2018_53.2_13.2_40.0.csv",
)
assert os.path.exists(filename) == False
# filename in storage_TES.csv does not change
df = pd.read_csv(self.filename_storage_xx, header=0, index_col=0)
assert (
"fixed_thermal_losses_absolute_2017_53.2_13.2_40.0.csv"
in df.loc["fixed_thermal_losses_absolute"].item()
) == True
original_storage_xx_data.to_csv(self.filename_storage_xx, na_rep="NaN")
def test_add_sector_coupling_strat_tes_file_const_losses(self, select_conv_tech):
energy_storage_file_path = os.path.join(
TEST_USER_INPUTS_MVS_SECTOR_COUPLING, "csv_elements", "energyStorage.csv"
)
energy_storage_original = pd.read_csv(
energy_storage_file_path, header=0, index_col=0
)
energy_storage = energy_storage_original.copy()
energy_storage.at[
"storage_filename", "storage_TES"
] = "storage_TES_const_losses.csv"
energy_storage.to_csv(energy_storage_file_path, na_rep="NaN")
select_conv_tech(columns="storage capacity")
sts.add_strat_tes(
weather=self.weather,
lat=self.lat,
lon=self.lon,
user_inputs_pvcompare_directory=TEST_USER_INPUTS_PVCOMPARE,
user_inputs_mvs_directory=TEST_USER_INPUTS_MVS_SECTOR_COUPLING,
overwrite_tes_parameters=False,
)
# no file created
filename = os.path.join(
TEST_USER_INPUTS_MVS_SECTOR_COUPLING,
"time_series",
"fixed_thermal_losses_absolute_2017_53.2_13.2_40.0.csv",
)
assert os.path.exists(filename) == False
# check efficiency
df = pd.read_csv(self.filename_storage_TES, header=0, index_col=0)
assert float(df.loc["efficiency"].item()) == 0.99907726890329
assert float(df.loc["fixed_thermal_losses_relative"].item()) == 0.0016
assert float(df.loc["fixed_thermal_losses_absolute"].item()) == 0.0003
energy_storage_original.to_csv(energy_storage_file_path, na_rep="NaN")
def apply_pvcompare(
storeys,
country=None,
latitude=None,
longitude=None,
year=None,
static_inputs_directory=None,
user_inputs_pvcompare_directory=None,
user_inputs_mvs_directory=None,
collections_mvs_inputs_directory=None,
plot=False,
pv_setup=None,
overwrite_grid_parameters=True,
overwrite_pv_parameters=True,
overwrite_heat_parameters=True,
):
r"""
Runs the main functionalities of pvcompare.
Loads weather data for the given year and location, calculates pv feed-in time
series, as well as the nominal values /installation capacities based on the building
parameters. Additionally, COPs are calculated if a heat pump is added to the energy
system.
Parameters
----------
storeys: int
Number of storeys for which the demand is calculated.
country:
Country of the location. Default: None.
latitude: float or None
Latitude of country location in `country`. Default: None.
longitude: float or None
Longitude of country location in `country`. Default: None.
year: int
Year of the simulation. Default: None.
static_inputs_directory: str or None
Path to pvcompare static inputs. If None,
`constants.DEFAULT_STATIC_INPUTS_DIRECTORY` is used.
Default: None.
user_inputs_pvcompare_directory: str or None
Path to user input directory. If None,
`constants.DEFAULT_USER_INPUTS_PVCOMPARE_DIRECTORY` is used.
Default: None.
user_inputs_mvs_directory: str or None
Path to input directory containing files that describe the energy
system and that are an input to MVS. If None,
`constants.DEFAULT_USER_INPUTS_MVS_DIRECTORY` is used.
Default: None.
collections_mvs_inputs_directory: str or None
Path to input data collection. Used in
:py:func:`~.check_inputs.overwrite_mvs_energy_production_file`, there
if None, it is set to `constants.DEFAULT_COLLECTION_MVS_INPUTS_DIRECTORY`.
plot: bool
If True, plots of the PV feed-in time series are created in
:py:func:`~.pv_feedin.create_pv_components`. Default: False.
pv_setup: dict or None
Specifies the PV technologies and their installation details used in the
simulation. The dictionary contains columns: surface_type, technology,
surface_azimuth, surface_tilt.
A tilt of 0 resembles a vertical orientation.
If `pv_setup` is None, it is loaded from the `user_inputs_pvcompare_directory/pv_setup.cvs`.
Default: None.
overwrite_grid_parameters: bool
If True, the following grid parameters are inserted into the
MVS input csvs automatically: electricity price, feed-in tariff,
CO2 emissions, renewable share, gas price.
Default: True.
overwrite_pv_parameters: bool
If True, the pv components in 'energyProduction.csv' are
overwritten with default values from 'data/user_inputs_collection/'
according to the pv plants defined in 'pv_setup'.
Default: True.
overwrite_heat_parameters: bool
If True, existing COP time series of the heat pump will be
overwritten with calculated time series of COP and existing fixed thermal losses
absolute and relative will be overwritten with calculated time series of fixed thermal
losses relative and absolute.
Default: True.
Returns
-------
None
Saves calculated time series to `timeseries` folder in `user_inputs_mvs_directory` and
updates csv files in `csv_elements` folder.
"""
if static_inputs_directory == None:
static_inputs_directory = constants.DEFAULT_STATIC_INPUTS_DIRECTORY
if user_inputs_pvcompare_directory == None:
user_inputs_pvcompare_directory = (
constants.DEFAULT_USER_INPUTS_PVCOMPARE_DIRECTORY)
if user_inputs_mvs_directory == None:
user_inputs_mvs_directory = constants.DEFAULT_USER_INPUTS_MVS_DIRECTORY
# add location and year to project data
(
latitude,
longitude,
country,
year,
) = check_inputs.add_location_and_year_to_project_data(
user_inputs_mvs_directory,
static_inputs_directory,
latitude,
longitude,
country,
year,
)
# add grid parameters specified by country
if overwrite_grid_parameters == True:
check_inputs.add_local_grid_parameters(
static_inputs_directory=static_inputs_directory,
user_inputs_mvs_directory=user_inputs_mvs_directory,
)
# check if weather data already exists
weather_file = os.path.join(
static_inputs_directory,
f"weatherdata_{latitude}_{longitude}_{year}.csv")
if os.path.isfile(weather_file):
weather = pd.read_csv(
weather_file,
index_col=0,
)
else:
# if era5 import works this line can be used
weather = era5.load_era5_weatherdata(lat=latitude,
lon=longitude,
year=year)
weather.to_csv(weather_file)
# add datetimeindex
weather.index = pd.to_datetime(weather.index)
# check energyProduction.csv file for the correct pv technology
check_inputs.overwrite_mvs_energy_production_file(
pv_setup=pv_setup,
user_inputs_mvs_directory=user_inputs_mvs_directory,
user_inputs_pvcompare_directory=user_inputs_pvcompare_directory,
collections_mvs_inputs_directory=collections_mvs_inputs_directory,
overwrite_pv_parameters=overwrite_pv_parameters,
)
pv_feedin.create_pv_components(
lat=latitude,
lon=longitude,
weather=weather,
storeys=storeys,
pv_setup=pv_setup,
plot=plot,
user_inputs_pvcompare_directory=user_inputs_pvcompare_directory,
user_inputs_mvs_directory=user_inputs_mvs_directory,
year=year,
normalization=True,
)
# add sector coupling in case heat pump or chiller exists in energyConversion.csv
# note: chiller was not tested, yet.
heat_pump_and_chiller.add_sector_coupling(
user_inputs_mvs_directory=user_inputs_mvs_directory,
user_inputs_pvcompare_directory=user_inputs_pvcompare_directory,
weather=weather,
lat=latitude,
lon=longitude,
overwrite_hp_parameters=overwrite_heat_parameters,
)
demand.calculate_load_profiles(
country=country,
lat=latitude,
lon=longitude,
storeys=storeys,
year=year,
static_inputs_directory=static_inputs_directory,
user_inputs_pvcompare_directory=user_inputs_pvcompare_directory,
user_inputs_mvs_directory=user_inputs_mvs_directory,
weather=weather,
)
stratified_thermal_storage.add_strat_tes(
weather=weather,
lat=latitude,
lon=longitude,
user_inputs_pvcompare_directory=user_inputs_pvcompare_directory,
user_inputs_mvs_directory=user_inputs_mvs_directory,
overwrite_tes_parameters=overwrite_heat_parameters,
)