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building-agents
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chenxiaodong 2024-06-25 14:49:04 +08:00
parent b9119fdb29
commit 438dbe5bf6
2 changed files with 10 additions and 4 deletions
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2
plotDRL.py
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@ -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')

12
tools.py
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@ -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