LCOE with Discounted Demand

Added discounted factor

workflow/scripts/osemosys_global/summary/summarise_results.py

@@ -6,7 +6,7 @@
 from configuration import ConfigFile, ConfigPaths
 from osemosys_global.visualisation.utils import transform_ts, powerplant_filter
 from osemosys_global.visualisation.constants import DAYS_PER_MONTH, MONTH_NAMES
-from osemosys_global.utils import apply_timeshift
+from osemosys_global.utils import apply_timeshift, discount_factor 
 pd.set_option('mode.chained_assignment', None)
 
 
@@ -128,7 +128,10 @@ def headline_metrics(input_data: Dict[str,pd.DataFrame], result_data: Dict[str,p
                    'Value'] = (system_cost_total/1000).round(0)
 
     # Cost of electricity generation
-    df_demand = result_data["Demand"]
+    discount_rate = input_data['DiscountRate']
+    years = input_data['YEAR'].VALUE.to_list()
+    discount_fac = discount_factor(['GLOBAL'],years, discount_rate)
+    df_demand = result_data["Demand"].mul(discount_fac)
     demand_total = df_demand.VALUE.sum()  # Total demand in TWh
     df_metrics.loc[df_metrics['Metric'].str.startswith('Cost of electricity'),
                    'Value'] = (system_cost_total/(demand_total*0.2778)).round(0)

workflow/scripts/osemosys_global/utils.py

@@ -34,3 +34,42 @@ def apply_dtypes(df:pd.DataFrame, name: Optional[str]) -> pd.DataFrame:
             else:
                 logging.info(f"Can not set dtype on {col}")
     return df
+
+def discount_factor(
+    regions: list,
+    years: list,
+    discount_rate: pd.DataFrame, 
+) -> pd.DataFrame:
+    """DiscountFactor
+
+    Arguments
+    ---------
+    regions: list
+    years: list
+    discount_rate: pd.DataFrame
+    
+    Notes
+    -----
+    From the formulation::
+
+        param DiscountFactor{r in REGION, y in YEAR} :=
+                (1 + DiscountRate[r]) ^ (y - min{yy in YEAR} min(yy)); 
+    """
+
+    if discount_rate.empty:
+        raise ValueError(
+            "Cannot calculate discount factor due to missing discount rate"
+        )
+
+    discount_rate["YEAR"] = [years] * len(discount_rate)
+    discount_factor = discount_rate.explode("YEAR").reset_index(level="REGION")
+    discount_factor["YEAR"] = discount_factor["YEAR"].astype("int64")
+    discount_factor["NUM"] = discount_factor["YEAR"] - discount_factor["YEAR"].min()
+    discount_factor["RATE"] = discount_factor["VALUE"] + 1
+    discount_factor["VALUE"] = (
+        discount_factor["RATE"].pow(discount_factor["NUM"] + adj).astype(float)
+    )
+    return discount_factor.reset_index()[["REGION", "YEAR", "VALUE"]].set_index(
+        ["REGION", "YEAR"]
+    )
+