Feature/usability: Allow input of precalculated time series and different SAM SI modules

CHANGELOG.md

@@ -30,6 +30,7 @@ Here is a template for new release sections
 - Add info on energy systems consisting of more than one node in RTD section "scope and limitations" (#293)
 - Added description of the implementation of the stratified thermal storage in pvcompare with a description of the possibilities modeling it (#291)
 - Dokumentation: Update on 'basic_usage', 'parameter description' and 'model assumptions' (#302)
+- Usability: allow the user to provide their own weather data, demand time series, pv time series and SAM SI modules (#317)
 
 ### Changed
 - The inlet temperatures of the heat pump and the stratified thermal storage have been revised in the pvcompare input parameters, adapting them in order to fit typical temperatures of the heating system. Also the pvcompare input parameters of the stratified thermal storage have been revised (#272)

pvcompare/demand.py

@@ -55,6 +55,8 @@ def calculate_load_profiles(
     static_inputs_directory=None,
     user_inputs_pvcompare_directory=None,
     user_inputs_mvs_directory=None,
+    add_electricity_demand=None,
+    add_heat_demand=None,
 ):
     """
     Calculates electricity and heat load profiles and saves them to csv.
@@ -81,6 +83,12 @@ def calculate_load_profiles(
         Default: None.
     user_inputs_mvs_directory : str or None
         Path to mvs input directory. If None: DEFAULT_USER_INPUTS_MVS_DIRECTORY. Default: None.
+    add_electricity_demand: str
+        Path to precalculated hourly electricity demand time series for one year (or the same period
+        of a precalculated PV timeseries)
+    add_heat_demand: str
+        Path to precalculated hourly heat demand time series for one year (or the same period
+        of a precalculated PV timeseries)
 
     Returns
     ------
@@ -105,28 +113,66 @@ def calculate_load_profiles(
     for column in energyConsumption:
         if column != "unit":
             if energyConsumption.at["energyVector", column] == "Heat":
-                calculate_heat_demand(
-                    country=country,
-                    lat=lat,
-                    lon=lon,
-                    storeys=storeys,
-                    year=year,
-                    weather=weather,
-                    static_inputs_directory=static_inputs_directory,
-                    user_inputs_pvcompare_directory=user_inputs_pvcompare_directory,
-                    user_inputs_mvs_directory=user_inputs_mvs_directory,
-                    column=column,
-                )
+
+                if add_heat_demand is not None:
+                    # check if file exists
+                    if os.path.isfile(add_heat_demand):
+                        # save the file name of the time series
+                        # mvs_inputs/elements/csv/energyProduction.csv
+                        check_inputs.add_file_name_to_energy_consumption_file(
+                            column=column,
+                            ts_filename=add_heat_demand,
+                            user_inputs_mvs_directory=user_inputs_mvs_directory,
+                        )
+                    else:
+                        logging.warning(
+                            "The heat demand time series"
+                            " you have entered does not exist. It is"
+                            " thus calculated according to the default"
+                            " method of pvcompare."
+                        )
+                else:
+                    calculate_heat_demand(
+                        country=country,
+                        lat=lat,
+                        lon=lon,
+                        storeys=storeys,
+                        year=year,
+                        weather=weather,
+                        static_inputs_directory=static_inputs_directory,
+                        user_inputs_pvcompare_directory=user_inputs_pvcompare_directory,
+                        user_inputs_mvs_directory=user_inputs_mvs_directory,
+                        column=column,
+                    )
             elif energyConsumption.at["energyVector", column] == "Electricity":
-                calculate_power_demand(
-                    country=country,
-                    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,
-                    column=column,
-                )
+
+                if add_electricity_demand is not None:
+
+                    if os.path.isfile(add_electricity_demand):
+                        # save the file name of the time series
+                        # mvs_inputs/elements/csv/energyProduction.csv
+                        check_inputs.add_file_name_to_energy_consumption_file(
+                            column=column,
+                            ts_filename=add_electricity_demand,
+                            user_inputs_mvs_directory=user_inputs_mvs_directory,
+                        )
+                    else:
+                        logging.warning(
+                            "The electricity demand time series"
+                            " you have entered does not exist. It is"
+                            " thus calculated according to the default"
+                            " method of pvcompare."
+                        )
+                else:
+                    calculate_power_demand(
+                        country=country,
+                        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,
+                        column=column,
+                    )
             else:
                 logging.warning(
                     "the given energyVector in energyConsumption.csv "
@@ -300,7 +346,7 @@ def calculate_power_demand(
     filename = os.path.join(timeseries_directory, el_demand_csv)
     shifted_elec_demand.to_csv(filename, index=False)
 
-    # save the file name of the time series and the nominal value to
+    # save the file name of the time series
     # mvs_inputs/elements/csv/energyProduction.csv
     check_inputs.add_file_name_to_energy_consumption_file(
         column=column,
@@ -502,7 +548,7 @@ def calculate_heat_demand(
     filename = os.path.join(timeseries_directory, h_demand_csv)
 
     shifted_heat_demand.to_csv(filename, index=False)
-    # save the file name of the time series and the nominal value to
+    # save the file name of the time series
     # mvs_inputs/elements/csv/energyProduction.csv
     check_inputs.add_file_name_to_energy_consumption_file(
         column=column,

pvcompare/main.py

@@ -36,6 +36,11 @@ def apply_pvcompare(
     overwrite_grid_parameters=True,
     overwrite_pv_parameters=True,
     overwrite_heat_parameters=True,
+    add_weather_file=None,
+    add_sam_si_module=None,
+    add_electricity_demand=None,
+    add_heat_demand=None,
+    add_pv_timeseries=None,
 ):
     """
     Runs the main functionalities of pvcompare.
@@ -92,6 +97,37 @@ def apply_pvcompare(
         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.
+    add_weather_data: str or None
+        Path to hourly csv weather time series with columns: [time, latitude, longitude
+        ,ghi, wind_speed, temp_air, precipitable_water, dni, dhi]
+        Default: None. If None, the ERA5 data is used instead.
+    add_sam_si_module: dict or None
+        Dictionary with library (’CECMod’  or "SandiaMod") as key and module name as value.
+        E.g. {"cecmod":'Canadian_Solar_Inc__CS5P_220M'}.
+        Note that the SI module is only considered if there is the technology "SI" in
+        'user_inputs/mvs_inputs/pvcompare_inputs/pv_setup.csv'
+    add_electricity_demand: str or None
+        Path to precalculated hourly electricity demand time series for one year (or the same period
+        of a precalculated PV timeseries)
+        Note that that the demand is only considered is a column "Electricity demand" is added to
+        'user_inputs/mvs_inputs/csv_elements/energyConsumption.csv'
+    add_heat_demand: str or None
+        Path to precalculated hourly heat demand time series for one year (or the same period
+        of a precalculated PV timeseries)
+        Note that that the demand is only considered is a column "Heat demand" is added to
+        'user_inputs/mvs_inputs/csv_elements/energyConsumption.csv'
+    add_pv_timeseries: dict or None
+        Dictionary with {"PV1" : ["filename": >path_to_time_series< , "module_size": >module_size in m²<,
+        "module_peak_power": >peak power of the module in kWp<, "surface_type": >surface_type for PV installation<],
+        "PV2" : [...], ...}. If you want to consider more PV time series, more PV keys can be added.
+        The PV time series itself needs to be be an normalized hourly time series in kW/kWp
+        (normalized by the peak power of the module). The facades can be one of: [
+            "flat_roof", "gable_roof", "south_facade", "east_facade", "west_facade"].
+        Note that you need to add more specific PV parameters of your module (name, costs, lifetime etc.) in
+        'user_inputs/mvs_inputs/csv_elements/energyProduction.csv'. The columns in energyProduction.csv
+        should be named "PV"+ key (e.g. "PV SI1")
+         When providing your own time series, overwrite_pv_parameters should be
+        set to false. When add_pv_timeseries is used, the pv_setup.csv is disregarded.
 
     Returns
     -------
@@ -130,39 +166,55 @@ def apply_pvcompare(
             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,)
+    if add_weather_file is not None:
+        weather = pd.read_csv(add_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)
+        # 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:
+            # download ERA5 weather data
+            weather = era5.load_era5_weatherdata(lat=latitude, lon=longitude, year=year)
+            # save to csv
+            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,
-    )
+    # check if add_pv_time_series is True
+    if add_pv_timeseries is not None:
+        pv_feedin.add_pv_timeseries(
+            add_pv_timeseries=add_pv_timeseries,
+            storeys=storeys,
+            user_inputs_mvs_directory=user_inputs_mvs_directory,
+            user_inputs_pvcompare_directory=user_inputs_pvcompare_directory,
+        )
+
+    else:
+        # 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_sam_si_module=add_sam_si_module,
+        )
 
     # add sector coupling in case heat pump or chiller exists in energyConversion.csv
     # note: chiller was not tested, yet.
@@ -185,6 +237,8 @@ def apply_pvcompare(
         user_inputs_pvcompare_directory=user_inputs_pvcompare_directory,
         user_inputs_mvs_directory=user_inputs_mvs_directory,
         weather=weather,
+        add_electricity_demand=add_electricity_demand,
+        add_heat_demand=add_heat_demand,
     )
 
     stratified_thermal_storage.add_strat_tes(
@@ -276,18 +330,33 @@ def apply_mvs(
     year = 2018
     storeys = 5
     country = "Spain"
-    scenario_name = "Scenario_B2"
+    scenario_name = "Scenario_TEST_weatherdata"
 
     apply_pvcompare(
         latitude=latitude,
         longitude=longitude,
         year=year,
         storeys=storeys,
         country=country,
+        # add_pv_timeseries={
+        #     "PV1": {
+        #         "filename": "/home/inia/Dokumente/greco_env/pvcompare/pvcompare/data/user_inputs/mvs_inputs/time_series/cpv_90_0_2013_40.416775_-3.70379.csv",
+        #         "module_size": 1,
+        #         "module_peak_power": 50,
+        #         "surface_type": "flat_roof",
+        #     },
+        #     "PV2": {
+        #         "filename": "/home/inia/Dokumente/greco_env/pvcompare/pvcompare/data/user_inputs/mvs_inputs/time_series/cpv_90_0_2013_40.416775_-3.70379.csv",
+        #         "module_size": 1,
+        #         "module_peak_power": 50,
+        #         "surface_type": "flat_roof",
+        #     },
+        # },
+        add_sam_si_module={"cecmod": "Advance_Solar_Hydro_Wind_Power_API_180"},
     )
-
-    # apply_mvs(
-    #     scenario_name=scenario_name,
-    #     outputs_directory=None,
-    #     user_inputs_mvs_directory=None,
-    # )
+#    'Canadian_Solar_CS5P_220M___2009_']
+# apply_mvs(
+#     scenario_name=scenario_name,
+#     outputs_directory=None,
+#     user_inputs_mvs_directory=None,
+# )