From 672ffc218684bb7882ef25da7c3d219bbe801281 Mon Sep 17 00:00:00 2001 From: Tomasini Luca Date: Thu, 12 Dec 2024 11:51:04 +0100 Subject: [PATCH] Fix two basin states issue --- docs/first_stage_baseline.rst | 6 +- .../parameters_docs.csv | 0 .../sets_docs.csv | 0 .../variables_docs.csv | 0 .../baseline/second_stage/sets_docs.csv | 5 +- .../baseline/second_stage/variables_docs.csv | 20 +- scripts/baseline_optimizazion.py | 120 +- .../second_stage/constraints/basin_volume.py | 36 +- .../baseline/second_stage/constraints/flow.py | 76 +- .../second_stage/constraints/power.py | 89 +- .../second_stage/second_stage_pipeline.py | 30 +- .../baseline/second_stage/variables.py | 10 +- src/pyomo_models/input_data_preprocessing.py | 11 +- tests/base_line.ipynb | 46154 ++++++++++++++-- tests/newplot.png | Bin 0 -> 53509 bytes 15 files changed, 41936 insertions(+), 4621 deletions(-) rename docs/tables/baseline/{firste_stage => first_stage}/parameters_docs.csv (100%) rename docs/tables/baseline/{firste_stage => first_stage}/sets_docs.csv (100%) rename docs/tables/baseline/{firste_stage => first_stage}/variables_docs.csv (100%) create mode 100644 tests/newplot.png diff --git a/docs/first_stage_baseline.rst b/docs/first_stage_baseline.rst index c657d46..95cbb56 100644 --- a/docs/first_stage_baseline.rst +++ b/docs/first_stage_baseline.rst @@ -5,7 +5,7 @@ Sets ---- .. csv-table:: - :file: /tables/sets_docs.csv + :file: /tables/first_stage/sets_docs.csv :header-rows: 1 .. automodule:: pyomo_models.baseline.first_stage.sets @@ -18,7 +18,7 @@ Variables :no-index: .. csv-table:: - :file: /tables/variables_docs.csv + :file: /tables/first_stage/variables_docs.csv :header-rows: 1 Parameters @@ -28,7 +28,7 @@ Parameters :no-index: .. csv-table:: - :file: /tables/parameters_docs.csv + :file: /tables/first_stage/parameters_docs.csv :header-rows: 1 Objective diff --git a/docs/tables/baseline/firste_stage/parameters_docs.csv b/docs/tables/baseline/first_stage/parameters_docs.csv similarity index 100% rename from docs/tables/baseline/firste_stage/parameters_docs.csv rename to docs/tables/baseline/first_stage/parameters_docs.csv diff --git a/docs/tables/baseline/firste_stage/sets_docs.csv b/docs/tables/baseline/first_stage/sets_docs.csv similarity index 100% rename from docs/tables/baseline/firste_stage/sets_docs.csv rename to docs/tables/baseline/first_stage/sets_docs.csv diff --git a/docs/tables/baseline/firste_stage/variables_docs.csv b/docs/tables/baseline/first_stage/variables_docs.csv similarity index 100% rename from docs/tables/baseline/firste_stage/variables_docs.csv rename to docs/tables/baseline/first_stage/variables_docs.csv diff --git a/docs/tables/baseline/second_stage/sets_docs.csv b/docs/tables/baseline/second_stage/sets_docs.csv index 733bc3a..ae9bfd0 100644 --- a/docs/tables/baseline/second_stage/sets_docs.csv +++ b/docs/tables/baseline/second_stage/sets_docs.csv @@ -4,5 +4,6 @@ :math:`B`,1,,Water basins :math:`S_B`,2,:math:`B`,State of each basins :math:`S_H`,2,:math:`H`,State of each hydro powerplants (related to upstream basin state) -:math:`F`,2,:math:`H`,State of each hydro powerplant water flow -:math:`S_{BH}`,4,:math:`\{ H; ~B; ~S_H \;~S_B \}`,"Index to make the correspondence between the states, basins and hydro powerplants" +:math:`S_Q`,3,:math:`S_H`,State of each hydro powerplant water flow +:math:`B_{H}`,2,:math:`H`,Index to make the correspondence between hydro powerplants ant their upper stream bassin +:math:`SB_{H}`,3,:math:`S_H`,Index to make the correspondence between basins' and hydro powerplants' states diff --git a/docs/tables/baseline/second_stage/variables_docs.csv b/docs/tables/baseline/second_stage/variables_docs.csv index 49fddd3..0c9f97d 100644 --- a/docs/tables/baseline/second_stage/variables_docs.csv +++ b/docs/tables/baseline/second_stage/variables_docs.csv @@ -1,14 +1,14 @@ Name,Description,Type,Units ":math:`V_\text{BAS}^{t,~b}`",Basins actual water volume,:math:`\mathbb{R}^{+}`,:math:`\mathrm{m}^{3}` ":math:`V_\text{SPIL}^{t,~b}`",Spilled water volumes when basins are full,:math:`\mathbb{R}^{+}`,:math:`\mathrm{m}^{3}` -":math:`V_\text{BAS, END}^{b}`",,:math:`\mathbb{R}^{+}`,:math:`\mathrm{m}^{3}` -":math:`dV_\text{+}^{t,~b}`",,:math:`\mathbb{R}^{+}`,:math:`\mathrm{m}^{3}` -":math:`dV_\text{-}^{t,~b}`",,:math:`\mathbb{R}^{+}`,:math:`\mathrm{m}^{3}` -":math:`P^{t,~h}`",Electrical power produced (or consumed) by a hydropower plant,:math:`\mathbb{R}^{+}`,:math:`\mathrm{MW}` -":math:`Q^{t,~h}`",Amount of water that flows through a hydropower plant,:math:`\mathbb{R}^{+}`,:math:`\mathrm{m}^{3}/\mathrm{s}` +":math:`V_\text{BAS, END}^{b}`",Basins end volume,:math:`\mathbb{R}^{+}`,:math:`\mathrm{m}^{3}` +":math:`dV_\text{+}^{t,~h}`",Positive difference bertween powered water volume sepoints and calculated,:math:`\mathbb{R}^{+}`,:math:`\mathrm{m}^{3}` +":math:`dV_\text{-}^{t,~h}`",Positive difference bertween powered water volume sepoints and calculated,:math:`\mathbb{R}^{+}`,:math:`\mathrm{m}^{3}` +":math:`P^{t,~h}`",Electrical power produced (or consumed) by a hydropower plant,:math:`\mathbb{R}`,:math:`\mathrm{MW}` +":math:`Q^{t,~h}`",Amount of water that flows through a hydropower plant,:math:`\mathbb{R}`,:math:`\mathrm{m}^{3}/\mathrm{s}` ":math:`S_\text{BAS}^{t,~b,~s_b}`","Binary variable that indicates the basin's volume state derived from its volume: :math:`S_\text{BAS}^{t, b, s_b} = \begin{cases} 1 \text{ if } V_\text{BAS}^{t, b} \in \left[ V_\text{BAS, MIN}^{b,~s_b} ;V_\text{BAS, MAX}^{b,~s_b} \right] \\ 0 \text{ otherwise} \end{cases}`",:math:`\mathbb{B}`, -":math:`S_\text{FLOW}^{t,~h,~s_q}`",Binary variable that indicates the hydo power plant's flow state (for turbine and pump),:math:`\mathbb{B}`, -":math:`P_\text{CAL}^{t,~h,~s_q}`",Calculated electrical power produced (or consumed) by a hydropower plant for each flow state,:math:`\mathbb{R}^{+}`,:math:`\mathrm{MW}` -":math:`Q_\text{CAL}^{t,~h,~s_q}`",Calculated water that flows through a hydropower plant for each flow state,:math:`\mathbb{R}^{+}`,:math:`\mathrm{m}^{3}/\mathrm{s}` -":math:`P_\text{S}^{t,~h,~s_q}`","Real electrical power produced (or consumed) by a hydropower plant for each flow state: :math:`P_\text{S}^{t,~h,~s_q} = \begin{cases} P_\text{CAL}^{t,~h,~s_q} \text{ if } S_\text{FLOW}^{t,~h,~s_q} = 1 \\ 0 \text{ otherwise} \end{cases}`",:math:`\mathbb{R}^{+}`,:math:`\mathrm{m}^{3}/\mathrm{s}` -":math:`Q_\text{S}^{t,~h,~s_q}`","Real amount of water that flows through a pump for each hydro powerplant state: :math:`Q_\text{S}^{t,~h,~s_q} = \begin{cases} Q_\text{CAL}^{t,~h,~s_q} \text{ if } S_\text{FLOW}^{t,~h,~s_q} = 1 \\ 0",:math:`\mathbb{R}^{+}`,:math:`\mathrm{m}^{3}/\mathrm{s}` +":math:`S_\text{FLOW}^{t,~h,~s_h,~s_q}`",Binary variable that indicates the hydo power plant's flow state (for turbine and pump),:math:`\mathbb{B}`, +":math:`P_\text{CAL}^{t,~h,~s_h,~s_q}`",Calculated electrical power produced (or consumed) by a hydropower plant for each flow state,:math:`\mathbb{R}`,:math:`\mathrm{MW}` +":math:`Q_\text{CAL}^{t,~h,~s_h,~s_q}`",Calculated water that flows through a hydropower plant for each flow state,:math:`\mathbb{R}`,:math:`\mathrm{m}^{3}/\mathrm{s}` +":math:`P_\text{S}^{t,~h,~s_h,~s_q}`","Real electrical power produced (or consumed) by a hydropower plant for each flow state: :math:`P_\text{S}^{t,~h,~s_h,~s_q} = \begin{cases} P_\text{CAL}^{t,~h,~s_h,~s_q} \text{ if } S_\text{FLOW}^{t,~h,~s_h,~s_q} = 1 \\ 0 \text{ otherwise} \end{cases}`",:math:`\mathbb{R}`,:math:`\mathrm{MW}` +":math:`Q_\text{S}^{t,~h,~s_h,~s_q}`","Real amount of water that flows through a pump for each hydro powerplant state: :math:`Q_\text{S}^{t,~h,~s_h,~s_q} = \begin{cases} Q_\text{CAL}^{t,~h,~s_h,~s_q} \text{ if } S_\text{FLOW}^{t,~h,~s_h,~s_q} = 1 0 \text{ otherwise} \end{cases}`",:math:`\mathbb{R}`,:math:`\mathrm{m}^{3}/\mathrm{s}` diff --git a/scripts/baseline_optimizazion.py b/scripts/baseline_optimizazion.py index e50c39f..73a0f78 100644 --- a/scripts/baseline_optimizazion.py +++ b/scripts/baseline_optimizazion.py @@ -2,6 +2,8 @@ import json from datetime import timedelta import polars as pl +from typing import Union +from multiprocessing import Pool from polars import col as c import shutil @@ -19,26 +21,48 @@ YEARS = [2020, 2021, 2022, 2023] TURBINE_FACTORS = {0.7, 0.8, 0.9} -SIMULATION_SETTING = { - "1": {"quantile": 0, "buffer": 0.2, "powered_volume_enabled": True, "with_penalty": True}, - "2": {"quantile": 0.15, "buffer": 0.3, "powered_volume_enabled": True, "with_penalty": True}, - "3": {"quantile": 0.25, "buffer": 0.3, "powered_volume_enabled": False, "with_penalty": True}, - # "4": {"quantile": 0, "buffer": 0.2, "powered_volume_enabled": True, "with_penalty": False}, -} +SIMULATION_SETTING = [ + {"quantile": 0, "buffer": 0.2, "powered_volume_enabled": True, "with_penalty": True}, + {"quantile": 0.15, "buffer": 0.3, "powered_volume_enabled": True, "with_penalty": True}, + {"quantile": 0.25, "buffer": 0.3, "powered_volume_enabled": False, "with_penalty": True}, +] +REAL_TIMESTEP = timedelta(hours=1) +FIRST_STAGE_TIMESTEP = timedelta(days=1) +SECOND_STAGE_TIME_SIM = timedelta(days=4) +TIME_LIMIT = 20 # in seconds +VOLUME_FACTOR = 1e-6 + output_file_names: dict[str, str] = json.load(open(settings.OUTPUT_FILE_NAMES)) log = generate_log(name=__name__) +def solve_second_stage_model( + second_stage: BaselineSecondStage, plot_name: str + ) -> tuple[BaselineSecondStage, float]: + + second_stage.solve_model() + income: float = round(second_stage.simulation_results["income"].sum()/1e6, 3) + fig = plot_second_stage_result( + simulation_results=second_stage.simulation_results, time_divider=7*24 + ) + + fig.write_html(plot_name) + return second_stage, income + if __name__=="__main__": baseline_folder = output_file_names["baseline"] if os.path.exists(baseline_folder): shutil.rmtree(baseline_folder) for year in YEARS: - year_folder = f"{baseline_folder}/year_{year}" + plot_folder = f"{baseline_folder}/plots_year_{year}" + + income_result_list: list[dict] = [] + log_book_final: pl.DataFrame = pl.DataFrame() for turbine_factor in TURBINE_FACTORS: - test_folder = f"{year_folder}/turbine_factor_{turbine_factor}" - plot_folder = f"{test_folder}/plots" - log_book_final: pl.DataFrame = pl.DataFrame() + + income_result: dict = {} + income_result["turbine_factor"] = turbine_factor + build_non_existing_dirs(plot_folder) sim_results: dict[str, pl.DataFrame] = dict() @@ -46,63 +70,63 @@ baseline_input: BaseLineInput = BaseLineInput( input_schema_file_name=output_file_names["duckdb_input"], - real_timestep=timedelta(hours=1), + real_timestep=REAL_TIMESTEP, year=year, hydro_power_mask = c("name").is_in(["Aegina hydro"]), - volume_factor=1e-6 + volume_factor=VOLUME_FACTOR ) - baseline_first_stage: BaselineFirstStage = BaselineFirstStage( - baseline_input, timestep=timedelta(days=1), turbine_factor=turbine_factor + first_stage: BaselineFirstStage = BaselineFirstStage( + input_instance=baseline_input, + timestep=timedelta(days=1), + turbine_factor=turbine_factor ) - baseline_first_stage.solve_model() - - sim_results["first_stage"] = baseline_first_stage.simulation_results - - sim_summary.append(["first_stage", baseline_first_stage.simulation_results["income"].sum()]) - value = round(baseline_first_stage.simulation_results["income"].sum()/1e6, 3) - print(f"{year} year, {turbine_factor} turbine_factor and first_stage : {value}") + first_stage.solve_model() + sim_results["first_stage"] = first_stage.simulation_results + income_result["first_stage"] = round(first_stage.simulation_results["income"].sum()/1e6, 3) + fig = plot_first_stage_result( - simulation_results=baseline_first_stage.simulation_results, time_divider=7 + simulation_results=first_stage.simulation_results, time_divider=7 ) - fig.write_html(f"{plot_folder}/first_stage.html") - + fig.write_html(f"{plot_folder}/{turbine_factor}_turbine_factor_first_stage.html") + + optimization_inputs: list[list[Union[BaselineSecondStage, str]]] = [] + income_results: list[dict] = [] - for name, sim_setting in SIMULATION_SETTING.items(): - baseline_second_stage: BaselineSecondStage = BaselineSecondStage( + for model_nb, sim_setting in enumerate(SIMULATION_SETTING): + second_stage: BaselineSecondStage = BaselineSecondStage( input_instance=baseline_input, - first_stage=baseline_first_stage, + first_stage=first_stage, timestep=timedelta(days=4), - time_limit=20, + time_limit=TIME_LIMIT, + model_nb=model_nb, **sim_setting ) - baseline_second_stage.solve_model() - - sim_results[f"second_stage_{name}"] = baseline_second_stage.simulation_results - sim_summary.append([name, baseline_second_stage.simulation_results["income"].sum()]) + fig_path = f"{plot_folder}/{turbine_factor}_turbine_factor_model_{model_nb}.html" + optimization_inputs.append([second_stage, fig_path]) - value = round(baseline_second_stage.simulation_results["income"].sum()/1e6, 3) - print(f"Results for {year} year, {turbine_factor} turbine_factor and second stage {name}\n") - print(f"Total income: {value}") - log_book = baseline_second_stage.log_book + with Pool(processes=len(optimization_inputs)) as pool: + results = pool.starmap(solve_second_stage_model, optimization_inputs) + for result in results: + second_stage, income = result + name = f"second_stage_{second_stage.model_nb}" + sim_results[f"{turbine_factor}_turbine_factor_model_{name}"] = second_stage.simulation_results + income_result[f"model_{name}"] = income + log_book = second_stage.log_book if not log_book.is_empty(): - print(f"Non optimal solutions:\n{log_book.to_pandas().to_string()}") - log_book_final = pl.concat([ log_book_final, log_book.with_columns(pl.lit(name).alias("sim_name")) ], how="diagonal_relaxed") - - fig = plot_second_stage_result( - simulation_results=baseline_second_stage.simulation_results, time_divider=7*24 - ) - - fig.write_html(f"{plot_folder}/second_stage_{name}.html") - - sim_results["summary"] = pl.DataFrame(sim_summary, schema=["name", "income"], orient="row") - sim_results["log_book"] = log_book_final + income_result_list.append(income_result) + + log.info(f"Income results for {year} year:\n{sim_results["income_result"]}") + - dict_to_duckdb(data=sim_results, file_path= f"{test_folder}/optimization_results.duckdb") \ No newline at end of file + sim_results["income_result"] = pl.from_dicts(income_result_list) + sim_results["log_book"] = log_book_final + + dict_to_duckdb(data=sim_results, file_path= f"{baseline_folder}/{year}_year_results.duckdb") \ No newline at end of file diff --git a/src/pyomo_models/baseline/second_stage/constraints/basin_volume.py b/src/pyomo_models/baseline/second_stage/constraints/basin_volume.py index c9fbc61..b242b80 100644 --- a/src/pyomo_models/baseline/second_stage/constraints/basin_volume.py +++ b/src/pyomo_models/baseline/second_stage/constraints/basin_volume.py @@ -120,36 +120,40 @@ def basin_state_constraint(model, t, b): ## Basin volume state constraints used to determine the state of each basin ####################################### ################################################################################################################### - @model.Constraint(model.T, model.BS) # type: ignore - def basin_state_max_active_constraint(model, t, b, s_b): + @model.Constraint(model.T, model.HQS) # type: ignore + def basin_state_max_active_constraint(model, t, h, s_h, s_q): + b = model.B_H[h].first() return ( - model.basin_volume_by_state[t, b, s_b] <= - model.max_basin_volume[b, model.S_B[b].last()] * model.basin_state[t, b, s_b] + model.basin_volume_by_state[t, h, s_h, s_q] <= + model.max_basin_volume[b, model.S_B[b].last()] * model.flow_state[t, h, s_h, s_q] ) - @model.Constraint(model.T, model.BS) # type: ignore - def basin_state_max_inactive_constraint(model, t, b, s_b): + @model.Constraint(model.T, model.HQS) # type: ignore + def basin_state_max_inactive_constraint(model, t, h, s_h, s_q): + b = model.B_H[h].first() return ( - model.basin_volume_by_state[t, b, s_b] >= + model.basin_volume_by_state[t, h, s_h, s_q] >= model.basin_volume[t, b] - - model.max_basin_volume[b, model.S_B[b].last()] * (1 - model.basin_state[t, b, s_b]) + model.max_basin_volume[b, model.S_B[b].last()] * (1 - model.flow_state[t, h, s_h, s_q]) ) - @model.Constraint(model.T, model.BS) # type: ignore - def basin_state_min_active_constraint(model, t, b, s_b): + @model.Constraint(model.T, model.HQS) # type: ignore + def basin_state_min_active_constraint(model, t, h, s_h, s_q): + b = model.B_H[h].first() return ( - model.basin_volume_by_state[t, b, s_b] >= - model.min_basin_volume[b, model.S_B[b].first()] * model.basin_state[t, b, s_b] + model.basin_volume_by_state[t, h, s_h, s_q] >= + model.min_basin_volume[b, model.S_B[b].first()] * model.flow_state[t, h, s_h, s_q] ) - @model.Constraint(model.T, model.BS) # type: ignore - def basin_state_min_inactive_constraint(model, t, b, s_b): + @model.Constraint(model.T, model.HQS) # type: ignore + def basin_state_min_inactive_constraint(model, t, h, s_h, s_q): + b = model.B_H[h].first() return ( - model.basin_volume_by_state[t, b, s_b] <= + model.basin_volume_by_state[t, h, s_h, s_q] <= model.basin_volume[t, b] - - model.min_basin_volume[b, model.S_B[b].first()] * (1 - model.basin_state[t, b, s_b]) + model.min_basin_volume[b, model.S_B[b].first()] * (1 - model.flow_state[t, h, s_h, s_q]) ) return model \ No newline at end of file diff --git a/src/pyomo_models/baseline/second_stage/constraints/flow.py b/src/pyomo_models/baseline/second_stage/constraints/flow.py index ed48317..5dccea1 100644 --- a/src/pyomo_models/baseline/second_stage/constraints/flow.py +++ b/src/pyomo_models/baseline/second_stage/constraints/flow.py @@ -43,52 +43,54 @@ def flow_state_constraint(model, t, h, s_h): b = model.B_H[h].first() s_b = model.SB_H[h, s_h].first() return ( - sum(model.flow_state[t, h, s_h, s_q] for s_q in model.S_Q[h, s_h]) <= 1 - # model.basin_state[t, b, s_b] + sum(model.flow_state[t, h, s_h, s_q] for s_q in model.S_Q[h, s_h]) <= model.basin_state[t, b, s_b] ) - @model.Constraint(model.T, model.HQS) # type: ignore - def flow_by_state_constraint(model, t, h, s_h, s_q): + @model.Constraint(model.T, model.H) # type: ignore + def discrete_flow_constraint(model, t, h): b = model.B_H[h].first() - s_b = model.SB_H[h, s_h].first() return ( - model.calculated_flow[t, h, s_h, s_q] == - model.basin_state[t, b, s_b] * - (model.min_flow[h, s_h, s_q] - model.d_flow[h, s_h, s_q] * model.min_basin_volume[b, s_b]) + - model.d_flow[h, s_h, s_q] * model.basin_volume_by_state[t, b, s_b] + model.flow[t, h] == + sum( + sum( + model.flow_state[t, h, s_h, s_q] * + (model.min_flow[h, s_h, s_q] - model.d_flow[h, s_h, s_q] * model.min_basin_volume[b, model.SB_H[h, s_h].first()]) + + model.d_flow[h, s_h, s_q] * model.basin_volume_by_state[t, h, s_h, s_q] + for s_q in model.S_Q[h, s_h]) + for s_h in model.S_H[h]) ) - @model.Constraint(model.T, model.HQS) # type: ignore - def flow_state_max_inactive_constraint(model, t, h, s_h, s_q): - return model.flow_by_state[t, h, s_h, s_q] <= model.big_m * model.flow_state[t, h, s_h, s_q] + # @model.Constraint(model.T, model.HQS) # type: ignore + # def flow_state_max_inactive_constraint(model, t, h, s_h, s_q): + # return model.flow_by_state[t, h, s_h, s_q] <= model.big_m * model.flow_state[t, h, s_h, s_q] - @model.Constraint(model.T, model.HQS) # type: ignore - def flow_state_min_inactive_constraint(model, t, h, s_h, s_q): - return model.flow_by_state[t, h, s_h, s_q] >= - model.big_m * model.flow_state[t, h, s_h, s_q] + # @model.Constraint(model.T, model.HQS) # type: ignore + # def flow_state_min_inactive_constraint(model, t, h, s_h, s_q): + # return model.flow_by_state[t, h, s_h, s_q] >= - model.big_m * model.flow_state[t, h, s_h, s_q] - @model.Constraint(model.T, model.HQS) # type: ignore - def flow_state_max_active_constraint(model, t, h, s_h, s_q): - return( - model.flow_by_state[t, h, s_h, s_q] >= - model.calculated_flow[t, h, s_h, s_q] - - model.big_m * (1 - model.flow_state[t, h, s_h, s_q]) - ) + # @model.Constraint(model.T, model.HQS) # type: ignore + # def flow_state_max_active_constraint(model, t, h, s_h, s_q): + # return( + # model.flow_by_state[t, h, s_h, s_q] >= + # model.calculated_flow[t, h, s_h, s_q] - + # model.big_m * (1 - model.flow_state[t, h, s_h, s_q]) + # ) - @model.Constraint(model.T, model.HQS) # type: ignore - def flow_state_min_active_constraint(model, t, h, s_h, s_q): - return( - model.flow_by_state[t, h, s_h, s_q] <= - model.calculated_flow[t, h, s_h, s_q] + - model.big_m * (1 - model.flow_state[t, h, s_h, s_q]) - ) + # @model.Constraint(model.T, model.HQS) # type: ignore + # def flow_state_min_active_constraint(model, t, h, s_h, s_q): + # return( + # model.flow_by_state[t, h, s_h, s_q] <= + # model.calculated_flow[t, h, s_h, s_q] + + # model.big_m * (1 - model.flow_state[t, h, s_h, s_q]) + # ) - @model.Constraint(model.T, model.H) # type: ignore - def flow_constraint(model, t, h): - return( - model.flow[t, h] == - sum( - sum(model.flow_by_state[t, h, s_h, s_q] for s_q in model.S_Q[h, s_h]) - for s_h in model.S_H[h]) - ) + # @model.Constraint(model.T, model.H) # type: ignore + # def flow_constraint(model, t, h): + # return( + # model.flow[t, h] == + # sum( + # sum(model.flow_by_state[t, h, s_h, s_q] for s_q in model.S_Q[h, s_h]) + # for s_h in model.S_H[h]) + # ) return model \ No newline at end of file diff --git a/src/pyomo_models/baseline/second_stage/constraints/power.py b/src/pyomo_models/baseline/second_stage/constraints/power.py index 99fb868..638f5fd 100644 --- a/src/pyomo_models/baseline/second_stage/constraints/power.py +++ b/src/pyomo_models/baseline/second_stage/constraints/power.py @@ -37,50 +37,63 @@ def power_constraints(model): #################################################################################################################### ### basin volume per state constraints used to determine the state of each basin ################################### #################################################################################################################### - - @model.Constraint(model.T, model.HQS) # type: ignore - def power_by_state_constraint(model, t, h, s_h, s_q): + @model.Constraint(model.T, model.H) # type: ignore + def discrete_power_constraint(model, t, h): b = model.B_H[h].first() - s_b = model.SB_H[h, s_h].first() return ( - model.calculated_power[t, h, s_h, s_q] == - model.basin_state[t, b, s_b] * - (model.min_power[h, s_h, s_q] - model.d_power[h, s_h, s_q] * model.min_basin_volume[b, s_b]) + - model.d_power[h, s_h, s_q] * model.basin_volume_by_state[t, b, s_b] + model.power[t, h] == + sum( + sum( + model.flow_state[t, h, s_h, s_q] * + (model.min_power[h, s_h, s_q] - model.d_power[h, s_h, s_q] * model.min_basin_volume[b, model.SB_H[h, s_h].first()]) + + model.d_power[h, s_h, s_q] * model.basin_volume_by_state[t, h, s_h, s_q] + for s_q in model.S_Q[h, s_h]) + for s_h in model.S_H[h]) ) - @model.Constraint(model.T, model.HQS) # type: ignore - def power_state_max_inactive_constraint(model, t, h, s_h, s_q): - return model.power_by_state[t, h, s_h, s_q] <= model.big_m * model.flow_state[t, h, s_h, s_q] + # @model.Constraint(model.T, model.HQS) # type: ignore + # def power_by_state_constraint(model, t, h, s_h, s_q): + # b = model.B_H[h].first() + # s_b = model.SB_H[h, s_h].first() + # return ( + # model.calculated_power[t, h, s_h, s_q] == + # model.basin_state[t, b, s_b] * + # (model.min_power[h, s_h, s_q] - model.d_power[h, s_h, s_q] * model.min_basin_volume[b, s_b]) + + # model.d_power[h, s_h, s_q] * model.basin_volume_by_state[t, b, s_b] + # ) + + # @model.Constraint(model.T, model.HQS) # type: ignore + # def power_state_max_inactive_constraint(model, t, h, s_h, s_q): + # return model.power_by_state[t, h, s_h, s_q] <= model.big_m * model.power_state[t, h, s_h, s_q] - @model.Constraint(model.T, model.HQS) # type: ignore - def power_state_min_inactive_constraint(model, t, h, s_h, s_q): - return model.power_by_state[t, h, s_h, s_q] >= - model.big_m * model.flow_state[t, h, s_h, s_q] + # @model.Constraint(model.T, model.HQS) # type: ignore + # def power_state_min_inactive_constraint(model, t, h, s_h, s_q): + # return model.power_by_state[t, h, s_h, s_q] >= - model.big_m * model.power_state[t, h, s_h, s_q] - @model.Constraint(model.T, model.HQS) # type: ignore - def power_state_max_active_constraint(model, t, h, s_h, s_q): - return( - model.power_by_state[t, h, s_h, s_q] >= - model.calculated_power[t, h, s_h, s_q] - - model.big_m * (1 - model.flow_state[t, h, s_h, s_q]) - ) + # @model.Constraint(model.T, model.HQS) # type: ignore + # def power_state_max_active_constraint(model, t, h, s_h, s_q): + # return( + # model.power_by_state[t, h, s_h, s_q] >= + # model.calculated_power[t, h, s_h, s_q] - + # model.big_m * (1 - model.power_state[t, h, s_h, s_q]) + # ) - @model.Constraint(model.T, model.HQS) # type: ignore - def power_state_min_active_constraint(model, t, h, s_h, s_q): - return( - model.power_by_state[t, h, s_h, s_q] <= - model.calculated_power[t, h, s_h, s_q] + - model.big_m * (1 - model.flow_state[t, h, s_h, s_q]) - ) + # @model.Constraint(model.T, model.HQS) # type: ignore + # def power_state_min_active_constraint(model, t, h, s_h, s_q): + # return( + # model.power_by_state[t, h, s_h, s_q] <= + # model.calculated_power[t, h, s_h, s_q] + + # model.big_m * (1 - model.power_state[t, h, s_h, s_q]) + # ) - @model.Constraint(model.T, model.H) # type: ignore - def power_constraint(model, t, h): - return( - model.power[t, h] == - sum( - sum( - model.power_by_state[t, h, s_h, s_q] - for s_q in model.S_Q[h, s_h]) - for s_h in model.S_H[h]) - ) + # @model.Constraint(model.T, model.H) # type: ignore + # def power_constraint(model, t, h): + # return( + # model.power[t, h] == + # sum( + # sum( + # model.power_by_state[t, h, s_h, s_q] + # for s_q in model.S_Q[h, s_h]) + # for s_h in model.S_H[h]) + # ) return model \ No newline at end of file diff --git a/src/pyomo_models/baseline/second_stage/second_stage_pipeline.py b/src/pyomo_models/baseline/second_stage/second_stage_pipeline.py index f897796..3cb6f37 100644 --- a/src/pyomo_models/baseline/second_stage/second_stage_pipeline.py +++ b/src/pyomo_models/baseline/second_stage/second_stage_pipeline.py @@ -34,7 +34,7 @@ class BaselineSecondStage(BaseLineInput): def __init__( - self, input_instance: BaseLineInput, first_stage: BaselineFirstStage, timestep: timedelta, + self, input_instance: BaseLineInput, first_stage: BaselineFirstStage, timestep: timedelta, model_nb: int = 1, buffer: float = 0.2, big_m: float = 1e6, error_threshold: float = 0.1, powered_volume_enabled: bool = True, quantile: float = 0.15, spilled_factor: float = 1e2, with_penalty: bool = True, log_solver_info: bool = False, global_price: bool = False, time_limit:float = 120 @@ -43,6 +43,7 @@ def __init__( self.big_m: float = big_m self.sim_nb = 0 self.sim_tot = 0 + self.model_nb = model_nb self.error_threshold = error_threshold self.buffer: float = buffer self.powered_volume_enabled = powered_volume_enabled @@ -285,11 +286,26 @@ def generate_model_instance(self): hydropower_state: pl.DataFrame = self.index["state"].drop_nulls("H") self.data["T"] = {None: self.index["datetime"].filter(c("sim_nb") == self.sim_nb)["T"].to_list()} - self.data["S_B"] = pl_to_dict(self.index["state"].unique("S", keep="first").group_by("B", maintain_order=True).agg("S")) - self.data["S_H"] = pl_to_dict(hydropower_state.unique("S", keep="first").group_by("H", maintain_order=True).agg("S")) - self.data["S_Q"] = pl_to_dict_with_tuple(hydropower_state.group_by(["HS"], maintain_order=True).agg("S_Q")) + self.data["S_B"] = pl_to_dict( + self.index["state"].unique("S", keep="first") + .group_by("B", maintain_order=True).agg("S") + .with_columns(c("S").list.sort()) + ) + self.data["S_H"] = pl_to_dict( + hydropower_state.unique("S", keep="first") + .group_by("H", maintain_order=True) + .agg("S") + .with_columns(c("S").list.sort()) + ) + self.data["S_Q"] = pl_to_dict_with_tuple( + hydropower_state + .group_by(["HS"], maintain_order=True).agg("S_Q") + .with_columns(c("S_Q").list.sort()) + ) + self.data["B_H"] = pl_to_dict(hydropower_state.group_by("H").agg(c("B").unique())) self.data["SB_H"] = pl_to_dict_with_tuple(hydropower_state.group_by("HS").agg(c("S").unique())) + self.data["start_basin_volume"] = pl_to_dict( self.start_basin_volume.filter(c("sim_nb") == self.sim_nb)[["B", "start_basin_volume"]]) self.data["remaining_volume"] = pl_to_dict(self.remaining_volume.filter(c("sim_nb") == self.sim_nb)[["H", "remaining_volume"]]) @@ -385,7 +401,11 @@ def finalizes_results_processing(self): def solve_model(self): logging.getLogger('pyomo.core').setLevel(logging.ERROR) - for sim_nb in tqdm.tqdm(range(self.sim_tot + 1), desc="Solving second stage optimization problem"): + for sim_nb in tqdm.tqdm( + range(self.sim_tot + 1), + desc=f"Solving second stage optimization model number {self.model_nb}", + position=self.model_nb + ): self.sim_nb = sim_nb self.generate_state_index() self.generate_model_instance() diff --git a/src/pyomo_models/baseline/second_stage/variables.py b/src/pyomo_models/baseline/second_stage/variables.py index 066dc39..246404e 100644 --- a/src/pyomo_models/baseline/second_stage/variables.py +++ b/src/pyomo_models/baseline/second_stage/variables.py @@ -15,12 +15,12 @@ def baseline_variables(model): model.basin_state = pyo.Var(model.T, model.BS, within=pyo.Binary) model.flow_state = pyo.Var(model.T, model.HQS, within=pyo.Binary) - model.calculated_flow = pyo.Var(model.T, model.HQS, within=pyo.Reals) # m^3 - model.calculated_power = pyo.Var(model.T, model.HQS, within=pyo.Reals) # m^3 + # model.calculated_flow = pyo.Var(model.T, model.HQS, within=pyo.Reals) # m^3 + # model.calculated_power = pyo.Var(model.T, model.HQS, within=pyo.Reals) # m^3 - model.flow_by_state = pyo.Var(model.T, model.HQS, within=pyo.Reals) # m^3 - model.power_by_state = pyo.Var(model.T, model.HQS, within=pyo.Reals) # m^3 + # model.flow_by_state = pyo.Var(model.T, model.HQS, within=pyo.Reals) # m^3 + # model.power_by_state = pyo.Var(model.T, model.HQS, within=pyo.Reals) # m^3 - model.basin_volume_by_state = pyo.Var(model.T, model.BS, within=pyo.NonNegativeReals) # m^3 + model.basin_volume_by_state = pyo.Var(model.T, model.HQS, within=pyo.NonNegativeReals) # m^3 return model \ No newline at end of file diff --git a/src/pyomo_models/input_data_preprocessing.py b/src/pyomo_models/input_data_preprocessing.py index 15e9aef..40a3270 100644 --- a/src/pyomo_models/input_data_preprocessing.py +++ b/src/pyomo_models/input_data_preprocessing.py @@ -225,7 +225,7 @@ def generate_second_stage_state( data: pl.DataFrame = filter_data_with_next( data=performance_table["power_performance"], col="volume", boundaries=boundaries) y_cols = data.select(cs.starts_with(name) for name in ["flow", "electrical"]).columns - state_name_list = set(map(lambda x : x.split("_")[-1], y_cols)) + state_name_list = list(set(map(lambda x : x.split("_")[-1], y_cols))) data = define_state(data=data, x_col="volume", y_cols=y_cols, error_threshold=error_threshold)\ .with_row_index(offset=start_state, name="S")\ @@ -234,14 +234,9 @@ def generate_second_stage_state( pl.lit(performance_table["B"]).alias("B") ).with_columns( pl.struct(cs.ends_with(col_name)).name.map_fields(lambda x: "_".join(x.split("_")[:-1])).alias(col_name) - for col_name in list(state_name_list) - ).with_columns( - pl.struct( - pl.lit(0).alias(col_name) - for col_name in ["flow","d_flow", "electrical_power", "d_electrical_power" ] - ).alias("off") + for col_name in state_name_list ).unpivot( - on=list(state_name_list) + ["off"], index= ["volume", "S", "H", "B"], value_name="data", variable_name="state" + on=state_name_list, index= ["volume", "S", "H", "B"], value_name="data", variable_name="state" ).unnest("data").drop("state") state_index = pl.concat([state_index, data], how="diagonal") diff --git a/tests/base_line.ipynb b/tests/base_line.ipynb index fb1b273..eab1757 100644 --- a/tests/base_line.ipynb +++ b/tests/base_line.ipynb @@ -59,24 +59,16 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "Read and validate tables from small_flex_input_data.db file: 25%|█████████████▎ | 3/12 [00:00<00:00, 26.73it/s]" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Read and validate tables from small_flex_input_data.db file: 100%|████████████████████████████████████████████████████| 12/12 [00:01<00:00, 7.80it/s]\n", - "Solving first stage optimization problem: 100%|██████████| 1/1 [00:01<00:00, 1.73s/it]\n", - "Solving second stage optimization problem: 1%| | 1/92 [00:00<00:14, 6.41it/s]2024-12-11 15:59:26 B01BPC15 pyomo.core[92869] WARNING Loading a SolverResults object with an 'aborted' status, but containing a solution\n", - "Solving second stage optimization problem: 2%|▏ | 2/92 [00:20<18:00, 12.01s/it]" + "Read and validate tables from small_flex_input_data.db file: 100%|████████████████████████████████████████████████████| 12/12 [00:01<00:00, 10.15it/s]\n", + "Solving first stage optimization problem: 100%|██████████| 1/1 [00:17<00:00, 17.58s/it]\n", + "Solving second stage optimization problem: 100%|██████████| 92/92 [00:29<00:00, 3.09it/s]\n" ] } ], @@ -87,7 +79,7 @@ "baseline_input = BaseLineInput(\n", " input_schema_file_name=output_file_names[\"duckdb_input\"],\n", " real_timestep=timedelta(hours=1),\n", - " year=2022,\n", + " year=2023,\n", " hydro_power_mask = c(\"name\").is_in([\"Aegina hydro\"]),\n", " volume_factor=1e-6,\n", ")\n", @@ -109,85 +101,9 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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