Add scatter plots to scenario evaluation (#284)

* improve scenario evaluation further * implement scatter plots and more kpis * fix pylint on obsolete * code qaly fix * some more tidy up * tidy scenario evaluation up more * renaming * code qualy * restructuring scenario evaluation * restructuring scenario evaluation * renaming * mypy fix * mypy fix
FZJ-IEK3-VSA · Jan 17, 2024 · ec0dca6 · ec0dca6
1 parent 985e145
commit ec0dca6
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Showing 18 changed files with 1,613 additions and 1,448 deletions.
diff --git a/hisim/json_generator.py b/hisim/json_generator.py
@@ -42,7 +42,7 @@ class ConfigFile(JSONWizard):
     component_entries: List[ComponentEntry] = field(default_factory=list)
     my_simulation_parameters: Optional[SimulationParameters] = None
     my_module_config: Optional[Dict[str, Any]] = None
-    pyam_data_information: Optional[Dict[str, Any]] = None
+    scenario_data_information: Optional[Dict[str, Any]] = None
 
 
 class JsonConfigurationGenerator:
@@ -65,11 +65,11 @@ def set_module_config(self, my_module_config_path: str) -> None:
             config_dict = json.load(openfile)
         self.config_file.my_module_config = config_dict
 
-    def set_pyam_data_information_dict(
-        self, pyam_data_information_dict: Dict[str, Any]
+    def set_scenario_data_information_dict(
+        self, scenario_data_information_dict: Dict[str, Any]
     ) -> None:
-        """Sets some pyam information concerning the data."""
-        self.config_file.pyam_data_information = pyam_data_information_dict
+        """Sets some scenario information concerning the result data."""
+        self.config_file.scenario_data_information = scenario_data_information_dict
 
     def add_component(self, config: Type[ConfigBase]) -> ComponentEntry:
         """Adds a component and returns a component entry."""

diff --git a/hisim/postprocessing/compute_kpis.py b/hisim/postprocessing/compute_kpis.py
@@ -14,14 +14,14 @@
 from hisim.simulationparameters import SimulationParameters
 from hisim.utils import HISIMPATH
 from hisim.component_wrapper import ComponentWrapper
-from hisim.components import generic_hot_water_storage_modular
+
 from hisim import log
 from hisim.postprocessing.investment_cost_co2 import compute_investment_cost
 
 
 def building_temperature_control_and_heating_load(
     results: pd.DataFrame, seconds_per_timestep: int, components: List[ComponentWrapper]
-) -> Tuple[Any, Any, float, float, float, float, float]:
+) -> Tuple[Any, Any, float, float, float, float, float, float]:
     """Check the building indoor air temperature.
 
     Check for all timesteps and count the
@@ -45,6 +45,11 @@ def building_temperature_control_and_heating_load(
             heating_load_in_watt = getattr(
                 wrapped_component.my_component, "my_building_information"
             ).max_thermal_building_demand_in_watt
+            # get specific heating load
+            scaled_conditioned_floor_area_in_m2 = getattr(
+                wrapped_component.my_component, "my_building_information"
+            ).scaled_conditioned_floor_area_in_m2
+            specific_heating_load_in_watt_per_m2 = heating_load_in_watt / scaled_conditioned_floor_area_in_m2
             break
 
     for column in results.columns:
@@ -99,6 +104,7 @@ def building_temperature_control_and_heating_load(
         min_temperature_reached_in_celsius,
         max_temperature_reached_in_celsius,
         heating_load_in_watt,
+        specific_heating_load_in_watt_per_m2
     )
 
 
@@ -243,6 +249,7 @@ def compute_consumption_production(
                 in output.postprocessing_flag
             ):
                 consumption_ids.append(index)
+
             elif InandOutputType.CHARGE_DISCHARGE in output.postprocessing_flag:
                 if ComponentType.BATTERY in output.postprocessing_flag:
                     battery_charge_discharge_ids.append(index)
@@ -271,93 +278,6 @@ def compute_consumption_production(
     return postprocessing_results
 
 
-def compute_hot_water_storage_losses_and_cycles(
-    components: List[ComponentWrapper],
-    all_outputs: List,
-    results: pd.DataFrame,
-    timeresolution: int,
-) -> Tuple[float, float, float, float, float, float]:
-    """Computes hot water storage losses and cycles."""
-
-    # initialize columns consumption, production, battery_charge, battery_discharge, storage
-    charge_sum_dhw = 0.0
-    charge_sum_buffer = 0.0
-    discharge_sum_dhw = 0.0
-    discharge_sum_buffer = 0.0
-    cycle_buffer = None
-    cycle_dhw = None
-
-    # get cycle of water storages
-    for elem in components:
-        if isinstance(
-            elem.my_component, generic_hot_water_storage_modular.HotWaterStorage
-        ):
-            use = elem.my_component.use
-            if use == ComponentType.BUFFER:
-                cycle_buffer = elem.my_component.config.energy_full_cycle
-            elif use == ComponentType.BOILER:
-                cycle_dhw = elem.my_component.config.energy_full_cycle
-
-    for index, output in enumerate(all_outputs):
-        if output.postprocessing_flag is not None:
-            if InandOutputType.CHARGE in output.postprocessing_flag:
-                if InandOutputType.WATER_HEATING in output.postprocessing_flag:
-                    charge_sum_dhw = charge_sum_dhw + compute_energy_from_power(
-                        power_timeseries=results.iloc[:, index],
-                        timeresolution=timeresolution,
-                    )
-                elif InandOutputType.HEATING in output.postprocessing_flag:
-                    charge_sum_buffer = charge_sum_buffer + compute_energy_from_power(
-                        power_timeseries=results.iloc[:, index],
-                        timeresolution=timeresolution,
-                    )
-            elif InandOutputType.DISCHARGE in output.postprocessing_flag:
-                if ComponentType.BOILER in output.postprocessing_flag:
-                    discharge_sum_dhw = discharge_sum_dhw + compute_energy_from_power(
-                        power_timeseries=results.iloc[:, index],
-                        timeresolution=timeresolution,
-                    )
-                elif ComponentType.BUFFER in output.postprocessing_flag:
-                    discharge_sum_buffer = (
-                        discharge_sum_buffer
-                        + compute_energy_from_power(
-                            power_timeseries=results.iloc[:, index],
-                            timeresolution=timeresolution,
-                        )
-                    )
-        else:
-            continue
-        if cycle_dhw is not None:
-            cycles_dhw = charge_sum_dhw / cycle_dhw
-        else:
-            cycles_dhw = 0
-            log.error(
-                "Energy of full cycle must be defined in config of modular hot water storage to compute the number of cycles. "
-            )
-        storage_loss_dhw = charge_sum_dhw - discharge_sum_dhw
-        if cycle_buffer is not None:
-            cycles_buffer = charge_sum_buffer / cycle_buffer
-        else:
-            cycles_buffer = 0
-            log.error(
-                "Energy of full cycle must be defined in config of modular hot water storage to compute the number of cycles. "
-            )
-        storage_loss_buffer = charge_sum_buffer - discharge_sum_buffer
-    if cycle_buffer == 0:
-        building_heating = charge_sum_buffer
-    else:
-        building_heating = discharge_sum_buffer
-
-    return (
-        cycles_dhw,
-        storage_loss_dhw,
-        discharge_sum_dhw,
-        cycles_buffer,
-        storage_loss_buffer,
-        building_heating,
-    )
-
-
 def compute_self_consumption_and_injection(
     postprocessing_results: pd.DataFrame,
 ) -> Tuple[pd.Series, pd.Series]:
@@ -605,20 +525,6 @@ def compute_kpis(
         co2 = co2 + fuel_co2
         price = price + fuel_price
 
-    # (
-    #     cycles_dhw,
-    #     loss_dhw,
-    #     use_dhw,
-    #     cycles_buffer,
-    #     loss_buffer,
-    #     use_heating,
-    # ) = compute_hot_water_storage_losses_and_cycles(
-    #     components=components,
-    #     all_outputs=all_outputs,
-    #     results=results,
-    #     timeresolution=simulation_parameters.seconds_per_timestep,
-    # )
-
     # compute cost and co2 for investment/installation:  # Todo: function compute_investment_cost does not include all components, use capex and opex-results instead
     investment_cost, co2_footprint = compute_investment_cost(components=components)
 
@@ -664,6 +570,7 @@ def compute_kpis(
         min_temperature_reached_in_celsius,
         max_temperature_reached_in_celsius,
         heating_load_in_watt,
+        specific_heating_load_in_watt_per_m2
     ) = building_temperature_control_and_heating_load(
         results=results,
         seconds_per_timestep=simulation_parameters.seconds_per_timestep,
@@ -693,14 +600,6 @@ def compute_kpis(
     table.append(["Self-consumption:", f"{self_consumption_sum:4.0f}", "kWh"])
     table.append(["Injection:", f"{injection_sum:4.0f}", "kWh"])
     table.append(["Battery losses:", f"{battery_losses:4.0f}", "kWh"])
-    # table.append(["DHW storage heat loss:", f"{loss_dhw:4.0f}", "kWh"])
-    # table.append(["DHW storage heat cycles:", f"{cycles_dhw:4.0f}", "Cycles"])
-    # table.append(["DHW energy provided:", f"{use_dhw:4.0f}", "kWh"])
-    # table.append(["Buffer storage heat loss:", f"{loss_buffer:4.0f}", "kWh"])
-    # table.append(["Buffer storage heat cycles:", f"{cycles_buffer:4.0f}", "Cycles"])
-    # table.append(["Heating energy provided:", f"{use_heating:4.0f}", "kWh"])
-    # table.append(["Hydrogen system losses:", f"{h2_system_losses:4.0f}", "kWh"])
-    # table.append(["Hydrogen storage content:", f"{0:4.0f}", "kWh"])
     table.append(["Autarky rate:", f"{autarky_rate:3.1f}", "%"])
     table.append(["Self-consumption rate:", f"{self_consumption_rate:3.1f}", "%"])
     table.append(["Cost for energy use:", f"{price:3.0f}", "EUR"])
@@ -793,6 +692,9 @@ def compute_kpis(
     table.append(
         ["Building heating load:", f"{(heating_load_in_watt):3.0f}", "W"]
     )
+    table.append(
+        ["Specific heating load:", f"{(specific_heating_load_in_watt_per_m2):3.0f}", "W"]
+    )
 
     table.append(["Number of heat pump cycles:", f"{number_of_cycles:3.0f}", "-"])
     table.append(["Seasonal performance factor of heat pump:", f"{spf:3.0f}", "-"])