diff --git a/demand_generator/__init__.py b/demand_generator/__init__.py index 428eabcdc44749d42fc2140c00cacb45741aabf5..e6d5f4f49684d721c27aceba42f6d81f912e094b 100644 --- a/demand_generator/__init__.py +++ b/demand_generator/__init__.py @@ -1,6 +1,2 @@ -#!/usr/bin/env python -# -*- coding:utf-8 -*- -# Created by jgn on 30.11.2020. - from .electrical_demand import * from .thermal_demand import * diff --git a/demand_generator/electrical_demand/ElectricalDemand.py b/demand_generator/electrical_demand/ElectricalDemand.py index ef3acb8a330272337075ca3a095a9a22a2a0e0d8..4a5ea5d5e203e5b1f6d216f41db11ec99a6db3dc 100644 --- a/demand_generator/electrical_demand/ElectricalDemand.py +++ b/demand_generator/electrical_demand/ElectricalDemand.py @@ -25,11 +25,11 @@ THE SOFTWARE. # Smoothing factors pkl for household demand calculated with formula from VDEW 1999 # Formula adjusted for accuracy by oemof: https://github.com/oemof/demandlib/blob/master/demandlib/bdew.py +import calendar import datetime import numpy as np -import pandas as pd import os -import calendar +import pandas as pd def add_weekdays2df(time_df, holidays=None, holiday_is_sunday=False): diff --git a/demand_generator/electrical_demand/__init__.py b/demand_generator/electrical_demand/__init__.py index f6a5fb1b0b4465b4326e3d6c04e9fd435a946169..f13315f0c2467f1b6e1ef98191125ad12c99714b 100644 --- a/demand_generator/electrical_demand/__init__.py +++ b/demand_generator/electrical_demand/__init__.py @@ -1,5 +1 @@ -#!/usr/bin/env python -# -*- coding:utf-8 -*- -# Created by jgn on 30.11.2020. - from .ElectricalDemand import ElectricalDemand diff --git a/demand_generator/thermal_demand/ThermalDemand.py b/demand_generator/thermal_demand/ThermalDemand.py index 5136e79e59170f5463eadadf0b54c9ffa860a48c..6b6768b5208e6b091cc913ae0657a8b66a3623a1 100644 --- a/demand_generator/thermal_demand/ThermalDemand.py +++ b/demand_generator/thermal_demand/ThermalDemand.py @@ -21,10 +21,11 @@ LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ + from math import ceil import numpy as np -import pandas as pd import os +import pandas as pd # This is needed if we provide a default temperature pattern ''' diff --git a/demand_generator/thermal_demand/__init__.py b/demand_generator/thermal_demand/__init__.py index bc249bbcc7eb227e6cb262ee5e2fe42e6c4f7618..263bcf570e33ee8d90d71c7e3dfd6c22e84bf83e 100644 --- a/demand_generator/thermal_demand/__init__.py +++ b/demand_generator/thermal_demand/__init__.py @@ -1,5 +1 @@ -#!/usr/bin/env python -# -*- coding:utf-8 -*- -# Created by jgn on 30.11.2020. - from .ThermalDemand import ThermalDemand diff --git a/input_profile_processor/calc_irradiance.py b/input_profile_processor/calc_irradiance.py index d0d47eab7f5b2e86a2a621bae71d522e6bd30448..4a2fa2d9a078d6289222693d3f609742c9b868cf 100644 --- a/input_profile_processor/calc_irradiance.py +++ b/input_profile_processor/calc_irradiance.py @@ -24,7 +24,6 @@ THE SOFTWARE. import numpy as np import pandas as pd -from datetime import timedelta def calc_total_irradiance(irradiance, timer, beta, psi_f, phi, lambda_st, lambda_1, alpha_albedo=0.2, reflection=1, refraction_index=2): """ diff --git a/input_profile_processor/input_profile_processor.py b/input_profile_processor/input_profile_processor.py index c97120cdaf4a07636f0c18470b523aeac856f1d0..6d26a6e0b273ac0171e69d85ebf3c180191c9ee2 100644 --- a/input_profile_processor/input_profile_processor.py +++ b/input_profile_processor/input_profile_processor.py @@ -21,14 +21,15 @@ LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ -import pandas as pd -from datetime import datetime -from datetime import timedelta + from Tooling.demand_generator.electrical_demand.ElectricalDemand import ElectricalDemand from Tooling.demand_generator.thermal_demand.ThermalDemand import ThermalDemand from Tooling.input_profile_processor.calc_irradiance import generate_g_t_series from Tooling.modifier import Modifier +from datetime import datetime, timedelta +import pandas as pd + def process_input_profiles(input_profile_dict, t_start, dynamic): d_step_min = min(dynamic.step_size_p(position) for position in range(dynamic.number_of_steps())) # This entire process assumes four things: