Add num_sim_days as input arg

This change allows more flexibility when creating input files.

Author: phumthep

scripts/run_quickstart.py

@@ -12,7 +12,7 @@ def main():
     input_folder = "..//model_library"
     output_folder = "..//temptemp"
 
-    model_name = "solar_ess"
+    model_name = "dummy"
     model_year = 2016
 
     # Simulation parameters

src/pownet/core/data_processor.py

@@ -285,9 +285,10 @@ def _create_derate_factors(
         else:
             return
 
+        num_hrs_in_year = 8760
         temp_df = pd.DataFrame(
             derate_factor,
-            index=range(0, 8760),  # Consider making 8760 a constant or parameter
+            index=range(0, num_hrs_in_year),
             columns=units,
         )
         setattr(

src/pownet/core/input.py

@@ -20,6 +20,7 @@ def __init__(
         model_name: str,
         year: int,
         sim_horizon: int,
+        num_sim_days: int = 365,
         use_spin_var: bool = True,
         dc_opf: str = "kirchhoff",
         spin_reserve_factor: float = 0.15,
@@ -36,6 +37,10 @@ def __init__(
         self.model_dir: str = os.path.join(input_folder, model_name)
         self.year: int = year
         self.sim_horizon: int = sim_horizon
+
+        self.num_sim_days: int = num_sim_days
+        self.num_sim_hours: int = num_sim_days * 24
+
         self.use_spin_var: bool = use_spin_var
 
         # The timestamp is used to create a unique folder for the model
@@ -433,9 +438,11 @@ def _load_contract_costs(self):
             "contract_cost.csv", header_levels=0
         )
 
-        # Check that the contract costs timeseries is of length 8760
-        if len(contract_costs_df) not in [0, 8760]:
-            raise ValueError("PowNet: Marginal cost timeseries must be of length 8760.")
+        # Check that the contract costs timeseries is of length num_sim_hours
+        if len(contract_costs_df) not in [0, self.num_sim_hours]:
+            raise ValueError(
+                f"PowNet: Marginal cost timeseries must be of length {self.num_sim_hours}."
+            )
 
         self.contract_costs = {
             (col, idx): value
@@ -517,7 +524,7 @@ def _create_timeseries_of_edges(self, data: list, column_name: str) -> pd.DataFr
             columns=[column_name],
         ).T
         # Repeat values for every hour of the year
-        df = df.loc[df.index.repeat(365 * 24)].reset_index(drop=True)
+        df = df.loc[df.index.repeat(self.num_sim_hours)].reset_index(drop=True)
         df.index += 1
         return df
 
@@ -699,7 +706,7 @@ def load_data(self):
         #################
         if self.spin_reserve_mw is not None:
             self.spin_requirement = pd.Series(
-                self.spin_reserve_mw, index=range(1, 8761)
+                self.spin_reserve_mw, index=range(1, self.num_sim_hours + 1)
             )
         else:
             self.spin_requirement = self.demand.sum(axis=1) * self.spin_reserve_factor
@@ -782,8 +789,10 @@ def check_data(self):
         # Timeseries have the correct length
         ##################################
 
-        if len(self.demand) != 8760:
-            raise ValueError("PowNet: Demand timeseries must be of length 8760.")
+        if len(self.demand) != self.num_sim_hours:
+            raise ValueError(
+                f"PowNet: Demand timeseries must be of length {self.num_sim_hours} but got {len(self.demand)}."
+            )
 
         attrs_to_check = [
             "solar_capacity",
@@ -795,12 +804,14 @@ def check_data(self):
         ]
         for attr in attrs_to_check:
             temp_df = getattr(self, attr)
-            if (not temp_df.empty) and (len(temp_df) != 8760):
-                raise ValueError(f"PowNet: {attr} must be of length 8760.")
+            if (not temp_df.empty) and (len(temp_df) != self.num_sim_hours):
+                raise ValueError(
+                    f"PowNet: {attr} must be of length {self.num_sim_hours} but got {len(temp_df)}."
+                )
 
-        if len(self.daily_hydro_capacity) not in [0, 365]:
+        if len(self.daily_hydro_capacity) not in [0, self.num_sim_days]:
             raise ValueError(
-                "PowNet: Daily hydropower timeseries must be of length 365."
+                f"PowNet: Daily hydropower timeseries must be of length {self.num_sim_days}."
             )
 
         ##################################
@@ -941,6 +952,7 @@ def print_summary(self):
 
         ---- Modeling parameters ----
         {'Simulation horizon':<25} = {self.sim_horizon} hours
+        {'Number of simulation days':<25} = {self.num_sim_days}
         {'Use spin variable':<25} = {self.use_spin_var}
         {'Power flow':<25} = {self.dc_opf}
         {'Spin reserve factor:':<25} = {self.spin_reserve_factor if self.spin_reserve_mw is None else 'Use an absolute value in MW.'}

src/pownet/core/simulation.py

@@ -75,6 +75,7 @@ def run(
         self,
         sim_horizon: int,
         steps_to_run: int,
+        num_sim_days: int = 365,
         to_process_inputs: bool = True,
         solver: str = "gurobi",
         log_to_console: bool = True,
@@ -101,7 +102,7 @@ def run(
         """
 
         if steps_to_run is None:
-            steps_to_run = 365 - (sim_horizon // 24 - 1)
+            steps_to_run = num_sim_days - (sim_horizon // 24 - 1)
 
         # To create files with "pownet_" prefix
         if to_process_inputs:
@@ -118,6 +119,7 @@ def run(
             model_name=self.model_name,
             year=self.model_year,
             sim_horizon=sim_horizon,
+            num_sim_days=num_sim_days,
             use_spin_var=self.use_spin_var,
             dc_opf=self.dc_opf,
             spin_reserve_factor=self.spin_reserve_factor,
@@ -130,6 +132,7 @@ def run(
         )
         # Produce an error if the data is not making sense
         self.inputs.load_and_check_data()
+        self.inputs.print_summary()
 
         ####################### Simulation
         self.system_record = SystemRecord(self.inputs)

src/pownet/data_utils.py

@@ -12,14 +12,14 @@
 from .folder_utils import get_database_dir
 
 
-def get_dates(year):
+def get_dates(year, num_days=365):
     """Return a dataframe of dates for the given year. The dataframe will have
     365 rows, one for each day of the year. The columns are 'date' and 'hour'.
     Exclude 29th February.
     """
     # Create dates to concatenate with the new dataframes
     dates = pd.DataFrame(
-        {"date": pd.date_range(start=str(year), periods=366, freq="D")}
+        {"date": pd.date_range(start=str(year), periods=num_days + 1, freq="D")}
     )
     # Remove 29th Feb because we do not deal with them
     dates = dates.loc[dates.date.dt.strftime("%m-%d") != "02-29"]
@@ -28,7 +28,7 @@ def get_dates(year):
 
     # In case we need three columns: date, hour, and day
     dates = dates.loc[dates.index.repeat(24)]
-    dates["hour"] = np.tile(range(1, 25), 365)
+    dates["hour"] = np.tile(range(1, 25), num_days)
     dates = dates.reset_index(drop=True)
     return dates