GridPath v2026.1.0

Merge pull request #1327 from blue-marble/develop

Author: anamileva

README.md

@@ -50,35 +50,3 @@ pip install .[all]
 ```
 
 **NOTE:** If you plan to edit the GridPath code, you should install with the `-e` flag.
-
-## Solver
-You will need a solver to use this platform. GridPath assumes you will be using Cbc (Coin-or branch and cut) by default, but you can specify a 
-different solver.
-
-
-# Usage
-
-## The gridpath_run and gridpath_run_e2e commands
-If you install GridPath via the setup script following the instructions above, 
-you can use the command `gridpath_run` to run a scenario from any directory 
--- as long as your GridPath Python environment is enabled -- as follows:
-```bash
-gridpath_run --scenario SCENARIO_NAME --scenario_location 
-/PATH/TO/SCENARIO 
-```
-
-If you are using the database, you can use the command `gridpath_run_e2e` to 
-run GridPath end-to-end, i.e. get inputs for the scenario from the database, 
-solve the scenario problem, import the results into the database, and 
-process them. Refer to the documentation for how to build the database.
-
-```bash
-gridpath_run_e2e --scenario SCENARIO_NAME --scenario_location 
-/PATH/TO/SCENARIO 
-```
-
-To see usage and other optional arguments, e.g. how to specify a 
-solver, check the help menu, e.g.:
-```bash
-gridpath_run --help
-```

data_toolkit/manual_adjustments.py

@@ -25,7 +25,6 @@
     DISAGG_PROJECT_NAME_STR,
 )
 
-
 # Storage durations
 STORAGE_DURATION_DEFAULTS = {"BA": 1, "PS": 12}
 SPEC_CAP_ID_DEFAULT = 1
@@ -162,8 +161,7 @@ def add_battery_durations(
         relevant_projects_df = pd.read_sql(sql, conn)
 
         if not relevant_projects_df.empty:
-            spec_cap_updated_df = duckdb_conn.sql(
-                f"""
+            spec_cap_updated_df = duckdb_conn.sql(f"""
                 CREATE TABLE {tech}_relevant_projects_table
                 AS SELECT * FROM relevant_projects_df
                 ;
@@ -173,15 +171,12 @@ def add_battery_durations(
                 WHERE (project, period) IN (SELECT (project, period) FROM {tech}_relevant_projects_table)
                 AND specified_stor_capacity_mwh IS NULL
                 ;
-                """
-            )
+                """)
 
-    spec_cap_updated_df = duckdb_conn.sql(
-        """
+    spec_cap_updated_df = duckdb_conn.sql("""
         SELECT * FROM spec_cap_table
         ;
-        """
-    ).df()
+        """).df()
 
     spec_cap_updated_df.to_csv(
         os.path.join(csv_location, f"{subscenario_id}_" f"{subscenario_name}.csv"),

data_toolkit/project/availability/outages/create_availability_iteration_input_csvs.py

@@ -384,14 +384,9 @@ def main(args=None):
 
     db = connect_to_database(parsed_args.database)
 
-    projects = [
-        i[0]
-        for i in db.execute(
-            """
+    projects = [i[0] for i in db.execute("""
         SELECT DISTINCT project FROM raw_data_unit_availability_params;
-        """
-        ).fetchall()
-    ]
+        """).fetchall()]
 
     all_files = []
     pool_data = []

data_toolkit/project/capacity_specified/eia860_to_project_specified_capacity_input_csvs.py

@@ -48,7 +48,6 @@
 
 """
 
-
 import csv
 from argparse import ArgumentParser
 import os.path

data_toolkit/project/create_monte_carlo_gen_input_csvs_common.py

@@ -133,8 +133,7 @@ def create_project_csv(
     c = conn.cursor()
 
     # Get all the draws
-    draws = c.execute(
-        f"""
+    draws = c.execute(f"""
                 SELECT weather_iteration, draw_number,
                 {timeseries_name}_year, {timeseries_name}_month,
                 {timeseries_name}_day_of_month
@@ -143,8 +142,7 @@ def create_project_csv(
                 AND weather_draws_id = {weather_draws_id}
                 ORDER BY weather_iteration, draw_number
                 ;
-                """
-    ).fetchall()
+                """).fetchall()
 
     for weather_iteration, draw_number, year, month, day_of_month in draws:
         # For each project, get the weighted cap factor for each of its

data_toolkit/project/opchar/eia860_to_project_opchar_input_csvs.py

@@ -71,7 +71,6 @@
     AGG_PROJECT_NAME_STR,
 )
 
-
 # TODO: add var costs, startup and shutdown costs, and startup fuel use
 
 
@@ -311,6 +310,9 @@ def make_opchar_sql_str(
     load_component_shift_bounds_scenario_id="NULL",
     efficiency_factor="NULL",
     energy_requirement_factor="NULL",
+    losses_factor_in_energy_target="NULL",
+    losses_factor_curtailment="NULL",
+    upward_reserves_to_soc_depletion="NULL",
 ):
     """ """
 
@@ -408,7 +410,10 @@ def make_opchar_sql_str(
      {load_component_shift_bounds_scenario_id} AS 
      load_component_shift_bounds_scenario_id,
      {efficiency_factor} AS efficiency_factor,
-     {energy_requirement_factor} AS energy_requirement_factor
+     {energy_requirement_factor} AS energy_requirement_factor,
+     {losses_factor_in_energy_target} AS losses_factor_in_energy_target,
+     {losses_factor_curtailment} AS losses_factor_curtailment,
+     {upward_reserves_to_soc_depletion} AS upward_reserves_to_soc_depletion
     """
 
     return opchar_sql_str

data_toolkit/project/opchar/fuels/eia860_to_project_fuel_input_csvs.py

@@ -53,7 +53,6 @@
 
 """
 
-
 import csv
 from argparse import ArgumentParser
 import os.path

data_toolkit/project/opchar/heat_rates/eia860_to_project_heat_rate_input_csvs.py

@@ -130,14 +130,12 @@ def get_project_heat_rates(
         min_load_fraction,
     ) in c.execute(sql).fetchall():
         c2 = conn.cursor()
-        min_load_heat_rate_coefficient = c2.execute(
-            f"""
+        min_load_heat_rate_coefficient = c2.execute(f"""
             SELECT average_heat_rate_coefficient
             FROM user_defined_heat_rate_curve
             WHERE load_point_fraction = {min_load_fraction}
             ;
-            """
-        ).fetchone()[0]
+            """).fetchone()[0]
         with open(
             os.path.join(
                 csv_location,

data_toolkit/project/opchar/hydro/create_hydro_iteration_input_csvs.py

@@ -52,7 +52,6 @@
 
 from db.common_functions import connect_to_database
 
-
 # TODO: leap years
 # TODO: hydro bins -- pick bin at random, pick year from bin at random; match
 #  month
@@ -120,24 +119,14 @@ def calculate_from_project_year_month_data(
     conn = connect_to_database(db_path=db_path)
     c = conn.cursor()
 
-    hydro_years = [
-        y[0]
-        for y in c.execute(
-            """
+    hydro_years = [y[0] for y in c.execute("""
             SELECT DISTINCT year FROM raw_data_hydro_years;
-    """
-        ).fetchall()
-    ]
+    """).fetchall()]
 
-    bt_horizons = [
-        bt_h
-        for bt_h in c.execute(
-            """
+    bt_horizons = [bt_h for bt_h in c.execute("""
             SELECT DISTINCT balancing_type, horizon 
             FROM user_defined_balancing_type_horizons;
-            """
-        ).fetchall()
-    ]
+            """).fetchall()]
 
     if overwrite:
         filename = get_filename(
@@ -154,15 +143,13 @@ def calculate_from_project_year_month_data(
     # Create hydro inputs for each year and balancing type
     for yr in hydro_years:
         for bt, h in bt_horizons:
-            hr_start, hr_end = c.execute(
-                f"""
+            hr_start, hr_end = c.execute(f"""
                     SELECT hour_ending_of_year_start, hour_ending_of_year_end
                     FROM user_defined_balancing_type_horizons
                     WHERE balancing_type = '{bt}'
                     AND horizon = {h}
                     ;
-                """
-            ).fetchone()
+                """).fetchone()
 
             month_weights = {}
             total = 0
@@ -193,17 +180,15 @@ def calculate_from_project_year_month_data(
             weighted_avg, weighted_min, weighted_max = 0, 0, 0
             for month in month_weights.keys():
                 weight = month_weights[month]
-                avg, min, max = c.execute(
-                    f"""
+                avg, min, max = c.execute(f"""
                     SELECT average_power_fraction, min_power_fraction, 
                     max_power_fraction
                     FROM raw_data_project_hydro_opchars_by_year_month
                     WHERE project = '{prj}'
                     AND hydro_year = {yr}
                     AND month = {month}
                     ;
-                """
-                ).fetchone()
+                """).fetchone()
 
                 weighted_avg += weight * avg
                 weighted_min += weight * min
@@ -291,15 +276,10 @@ def main(args=None):
     db = connect_to_database(parsed_args.database)
 
     c = db.cursor()
-    projects = [
-        prj[0]
-        for prj in c.execute(
-            """
+    projects = [prj[0] for prj in c.execute("""
                 SELECT DISTINCT project
                 FROM raw_data_project_hydro_opchars_by_year_month;
-            """
-        ).fetchall()
-    ]
+            """).fetchall()]
     pool_data = tuple(
         [
             [

data_toolkit/project/opchar/var_profiles/create_sync_var_gen_input_csvs.py

@@ -44,7 +44,6 @@
 
 """
 
-
 from argparse import ArgumentParser
 from multiprocessing import get_context
 import os.path