From 438dbe5bf6f4b4ee185b53ce745f5c67780e7d50 Mon Sep 17 00:00:00 2001 From: chenxiaodong Date: Tue, 25 Jun 2024 14:49:04 +0800 Subject: [PATCH] nothing --- plotDRL.py | 2 +- tools.py | 12 +++++++++--- 2 files changed, 10 insertions(+), 4 deletions(-) diff --git a/plotDRL.py b/plotDRL.py index 2f637b8..cd19b36 100644 --- a/plotDRL.py +++ b/plotDRL.py @@ -133,7 +133,7 @@ def plot_evaluation_information(datasource, directory): axs[1, 1].cla() axs[1, 1].set_ylabel('Costs') axs[1, 1].bar(eval_data['time_step'], eval_data['operation_cost']) - fig.savefig(f"{directory}/Evoluation Information.svg", format='svg', dpi=600, bbox_inches='tight') + fig.savefig(f"{directory}/evaluation_information.svg", format='svg', dpi=600, bbox_inches='tight') print('evaluation figure have been plot and saved') diff --git a/tools.py b/tools.py index dce8362..fe36c26 100644 --- a/tools.py +++ b/tools.py @@ -43,6 +43,8 @@ def optimization_base_result(env, month, day, initial_soc): NUM_GEN = len(DG_parameters.keys()) battery_capacity = env.battery.capacity battery_efficiency = env.battery.efficiency + solar_cofficient = env.solar.opex_cofficient + wind_cofficient = env.wind.opex_cofficient m = gp.Model("UC") @@ -82,8 +84,10 @@ def optimization_base_result(env, month, day, initial_soc): t in range(period) for g in range(NUM_GEN)) cost_grid_import = gp.quicksum(grid_energy_import[t] * price[t] for t in range(period)) cost_grid_export = gp.quicksum(grid_energy_export[t] * price[t] * env.sell_coefficient for t in range(period)) + cost_solar = gp.quicksum(pv[t] * solar_cofficient for t in range(period)) + cost_wind = gp.quicksum(wind[t] * wind_cofficient for t in range(period)) - m.setObjective((cost_gen + cost_grid_import - cost_grid_export), GRB.MINIMIZE) + m.setObjective((cost_gen + cost_grid_import - cost_grid_export + cost_solar + cost_wind), GRB.MINIMIZE) m.optimize() output_record = {'pv': [], 'wind': [], 'price': [], 'load': [], 'netload': [], @@ -95,11 +99,13 @@ def optimization_base_result(env, month, day, initial_soc): for g in range(NUM_GEN)) grid_import_cost = grid_energy_import[t].x * price[t] grid_export_cost = grid_energy_export[t].x * price[t] * env.sell_coefficient + solar_cost = pv[t] * solar_cofficient + wind_cost = wind[t] * wind_cofficient output_record['pv'].append(pv[t]) output_record['wind'].append(wind[t]) output_record['price'].append(price[t]) output_record['load'].append(load[t]) - output_record['netload'].append(load[t] - pv[t]) + output_record['netload'].append(load[t] - pv[t] - wind[t]) output_record['soc'].append(soc[t].x) output_record['battery_energy_change'].append(battery_energy_change[t].x) output_record['grid_import'].append(grid_energy_import[t].x) @@ -107,7 +113,7 @@ def optimization_base_result(env, month, day, initial_soc): output_record['gen1'].append(gen_output[0, t].x) output_record['gen2'].append(gen_output[1, t].x) output_record['gen3'].append(gen_output[2, t].x) - output_record['step_cost'].append(gen_cost + grid_import_cost - grid_export_cost) + output_record['step_cost'].append(gen_cost + grid_import_cost - grid_export_cost + solar_cost + wind_cost) output_record_df = pd.DataFrame.from_dict(output_record) return output_record_df