Create run_pownet.py

Author: phumthep

scripts/run_pownet.py

@@ -0,0 +1,123 @@
+from datetime import datetime
+from pownet.core import (
+    DataProcessor,
+    SystemInput,
+    ModelBuilder,
+    SystemRecord,
+    OutputProcessor,
+    Visualizer,
+)
+from pownet.data_utils import create_init_condition
+
+##### User inputs #####
+to_process_inputs = True
+sim_horizon = 24
+model_name = "RegionAB"
+steps_to_run = 3  # Default is None
+do_plot = True
+#######################
+
+if to_process_inputs:
+    data_processor = DataProcessor(
+        input_folder="../model_library", model_name=model_name, year=2016, frequency=50
+    )
+    data_processor.execute_data_pipeline()
+
+inputs = SystemInput(
+    input_folder="../model_library",
+    model_name=model_name,
+    year=2016,
+    sim_horizon=sim_horizon,
+    spin_reserve_factor=0.15,
+    load_shortfall_penalty_factor=1000,
+    load_curtail_penalty_factor=1,
+    spin_shortfall_penalty_factor=1000,
+)
+inputs.load_and_check_data()
+
+
+model_builder = ModelBuilder(inputs)
+record = SystemRecord(inputs)
+
+build_times = []
+opt_times = []
+objvals = []
+init_conditions = create_init_condition(inputs.thermal_units)
+
+if steps_to_run is None:
+    steps_to_run = 10  # 365 - (sim_horizon // 24 - 1)
+
+for step_k in range(1, steps_to_run):
+    start_time = datetime.now()
+    if step_k == 1:
+        power_system_model = model_builder.build(
+            step_k=step_k,
+            init_conds=init_conditions,
+        )
+    else:
+        power_system_model = model_builder.update(
+            step_k=step_k,
+            init_conds=init_conditions,
+        )
+    build_times.append((datetime.now() - start_time).total_seconds())
+
+    power_system_model.optimize(mipgap=0.001)
+
+    # Raise an error if the model is not feasible
+    if not power_system_model.check_feasible():
+        raise ValueError("Model is not feasible.")
+
+    objvals.append(power_system_model.get_objval())
+    opt_times.append(power_system_model.get_runtime())
+
+    record.keep(
+        runtime=power_system_model.get_runtime(),
+        objval=power_system_model.get_objval(),
+        solution=power_system_model.get_solution(),
+        lmp=power_system_model.solve_for_lmp(),
+        step_k=step_k,
+    )
+    init_conditions = record.get_init_conds()
+
+
+# Process the results
+output_processor = OutputProcessor(inputs)
+node_var_df = record.get_node_variables()
+output_processor.load_from_dataframe(node_var_df)
+
+# Visualize the results
+if do_plot:
+    visualizer = Visualizer(inputs.model_id)
+    if steps_to_run <= 3:
+        visualizer.plot_fuelmix_bar(
+            dispatch=output_processor.get_hourly_dispatch(),
+            demand=output_processor.get_hourly_demand(),
+        )
+    else:
+        visualizer = Visualizer(inputs.model_id)
+        visualizer.plot_fuelmix_area(
+            dispatch=output_processor.get_daily_dispatch(),
+            demand=output_processor.get_daily_demand(),
+        )
+
+# # Save other modeling statistics
+# import os
+# from pownet.folder_utils import get_output_dir
+# import pandas as pd
+
+# folder_dir = get_output_dir()
+# prefix_name = "warmstart"
+# df = pd.DataFrame(
+#     {
+#         "build_time": build_times,
+#         "opt_time": opt_times,
+#         "objval": objvals,
+#     }
+# )
+# df.to_csv(
+#     os.path.join(
+#         folder_dir,
+#         f"branch{prefix_name}_{inputs.model_name}_{sim_horizon}_modelstats.csv",
+#     ),
+#     index=False,
+# )