Calculate EFFICIENCY_GENSET_TIMESERIES

- Add `EFFICIENCY_GENSET_TIMESERIES` to `constants.py
- Create function `G3.get_efficiency_genset` to calculate the effective
generator efficiency. In case that multiple generators are present, it
represents the average efficiency, as it is based on the aggregated
generator dispatch.
- Store timeseries to `electricity-mg`-csv but exclude from energy
dispatch plot
- If `GENSET_WITH_EFFICIENCY_CURVE==True` store additionally a plot of
the generator efficiency curve over the installed capacity. This curve
is only exact if a single generator is used!

src/G0_oemof_simulate.py

@@ -176,6 +176,8 @@ def run(experiment, case_dict):
             case_dict, oemof_results, electricity_bus_ac, e_flows_df
         )
 
+        e_flows_df = timeseries.get_efficiency_genset(e_flows_df)
+
         e_flows_df = timeseries.get_national_grid(
             case_dict,
             oemof_results,

src/G3_oemof_evaluate.py

@@ -118,6 +118,7 @@
     DEMAND_AC,
     DEMAND_DC,
     CONSUMPTION_FUEL_TIMESERIES_KWH,
+    EFFICIENCY_GENSET_TIMESERIES,
 )
 
 
@@ -524,6 +525,24 @@ def get_fuel(case_dict, oemof_results, results, e_flows_df):
     return e_flows_df
 
 
+def get_efficiency_genset(e_flows_df):
+    if (
+        CONSUMPTION_FUEL_TIMESERIES_KWH in e_flows_df.columns
+        and GENSET_GENERATION in e_flows_df.columns
+    ):
+        logging.debug("Evaluate diesel generator efficiency:")
+        efficiency_timeseries = (
+            e_flows_df[GENSET_GENERATION] / e_flows_df[CONSUMPTION_FUEL_TIMESERIES_KWH]
+        )
+        average_efficiency = efficiency_timeseries.values.mean()
+        e_flows_df = join_e_flows_df(
+            efficiency_timeseries, EFFICIENCY_GENSET_TIMESERIES, e_flows_df
+        )
+        logging.debug(
+            f"The average efficiency of the diesel generators is {average_efficiency}. Please note that this is based on the aggregated generation of all diesel generators, and may or may not include a fix efficiency, minimal loading or efficiency curve. Check column {EFFICIENCY_GENSET_TIMESERIES} in the csv output of the electricity side of the MG for details."
+        )
+    return e_flows_df
+
 
 def get_storage(case_dict, oemof_results, experiment, results, e_flows_df):
     logging.debug("Evaluate flow: storage")

src/G4_output_functions.py

@@ -65,6 +65,8 @@
     SUFFIX_STORAGE_PNG,
     SUFFIX_STORAGE_4DAYS_PNG,
     CONSUMPTION_FUEL_TIMESERIES_KWH,
+    EFFICIENCY_GENSET_TIMESERIES,
+    GENSET_WITH_EFFICIENCY_CURVE,
 )
 
 
@@ -112,6 +114,7 @@ def save_mg_flows(experiment, case_dict, e_flows_df, filename):
         GENSET_GENERATION,
         GRID_AVAILABILITY,
         CONSUMPTION_FUEL_TIMESERIES_KWH,
+        EFFICIENCY_GENSET_TIMESERIES,
     ]
 
     negative_list = [
@@ -136,12 +139,11 @@ def save_mg_flows(experiment, case_dict, e_flows_df, filename):
         STORAGE_CHARGE_AC,
         STORAGE_CHARGE_DC,
         CONSUMPTION_FUEL_TIMESERIES_KWH,
+        EFFICIENCY_GENSET_TIMESERIES,
     ]
 
     mg_flows = pd.DataFrame(
-        e_flows_df[DEMAND].values,
-        columns=[DEMAND],
-        index=e_flows_df[DEMAND].index,
+        e_flows_df[DEMAND].values, columns=[DEMAND], index=e_flows_df[DEMAND].index,
     )
     for entry in flows_connected_to_electricity_mg_bus:
         if entry in e_flows_df.columns:
@@ -191,6 +193,32 @@ def save_mg_flows(experiment, case_dict, e_flows_df, filename):
             + filename
             + SUFFIX_ELECTRICITY_MG_CSV
         )
+    if (
+        experiment[SAVE_TO_PNG_FLOWS_ELECTRICITY_MG] is True
+        and case_dict[GENSET_WITH_EFFICIENCY_CURVE] is True
+    ):
+        if (
+            EFFICIENCY_GENSET_TIMESERIES in e_flows_df.columns
+            and GENSET_GENERATION in e_flows_df.columns
+        ):
+            logging.debug(f"Plotting efficiency curve of the diesel generator.")
+            plt.scatter(
+                x=e_flows_df[GENSET_GENERATION],
+                y=e_flows_df[EFFICIENCY_GENSET_TIMESERIES],
+            )
+            plt.xlabel(GENSET_GENERATION)
+            plt.ylabel("Generator efficiency curve")
+            plt.savefig(
+                experiment[OUTPUT_FOLDER]
+                + "/electricity_mg/"
+                + case_dict[CASE_NAME]
+                + filename
+                + "_efficiency_curve_genset.png",
+                bbox_inches="tight",
+            )
+            plt.close()
+            plt.clf()
+            plt.cla()
 
     if experiment[SAVE_TO_PNG_FLOWS_ELECTRICITY_MG] is True:
         number_of_subplots = 0

src/constants.py

@@ -416,6 +416,7 @@
 TRANSFORMER_GENSET_1 = "transformer_genset_1"
 GENSET_1_GENERATION = "Genset 1 generation"
 CONSUMPTION_FUEL_TIMESERIES_KWH = "consumption_fuel_kWh"
+EFFICIENCY_GENSET_TIMESERIES = "efficiency_generator"
 CONSUMPTION_FUEL_ANNUAL_KWH = "consumption_fuel_annual_kWh"
 CAPACITY = "capacity"
 TOTAL_STORAGE_THOUGHPUT_KWH = "total_storage_throughput_kWh"