问题 - 我有一个 python 函数，它从 excel 读取值，进行计算并将数据写回 excel。在 sg.window 我需要创建一个停止按钮，它会立即终止 python 运行进程。
为什么我需要 - 我的 python 函数将在 .exe 文件中创建，因此用户不能使用 KeyboardInterrupt 和 control+c，这就是为什么我需要创建一个按钮。
我试过 - 我做了一些方法来使用线程，但它没有帮助尝试线程，停止按钮没有停止，也许我做错了什么。我对此知之甚少。请帮我。 愿意使用其他方法和想法
import PySimpleGUI as sg
import time
import pandas as pd
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import numpy as np
from peak_shave.peak_shave_reader import Peakshave_Reader
from Seb.profit_calculator_dataclass_neu import *
from peak_shave.raw_data_setup_profit_calculator import Raw_data_from_Peak_shave, peak_shave_final_data
def Python_profitcalculator_simulation(file_path):
progress_bar.update(10) # 10% of progress for funtion loads
excel_workbook = Peakshave_Reader(file_path)
progress_bar.update(20) # 20% of progress for excel sheet load
# Reading Peak_shave excel
Pv_Profile_Raw = Raw_data_from_Peak_shave.PV_profile_raw(excel_workbook)
Load_Profile_raw = Raw_data_from_Peak_shave.Load_profile_raw(excel_workbook)
Investtabelle_Raw = Raw_data_from_Peak_shave.Investtabelle_raw_data(excel_workbook)
battery_raw_Eingabe_Übersicht_sheet = Raw_data_from_Peak_shave.Raw_data_from_Eingabe_Übersicht_sheet(excel_workbook)
battery_raw_Simulation_sheet = Raw_data_from_Peak_shave.Raw_data_from_Simulation_sheet(excel_workbook)
battery_raw_AdvanceSettingsDatabase_sheet = Raw_data_from_Peak_shave.Raw_data_from_AdvanceSettingsDatabase_sheet(excel_workbook)
battery_raw_Wirtschaftlichkeitsmatrix_sheet = Raw_data_from_Peak_shave.Raw_data_from_Wirtschaftlichkeitsmatrix_sheet(excel_workbook)
Wirtschaftlichkeitsmatrix_Raw = Raw_data_from_Peak_shave.wirtschaftlichkeitsmatrix_sheet_batteriekonfigurationen_values(excel_workbook)
# Convertion of values in SI unit
PV_Profile = peak_shave_final_data.PV_profile_conversion(Pv_Profile_Raw)
Load_Profile = peak_shave_final_data.Load_profile_conversion(Load_Profile_raw)
Eingabe_Übersicht_sheet = peak_shave_final_data.Eingabe_Übersicht_conversion(battery_raw_Eingabe_Übersicht_sheet)
Simulation_sheet = peak_shave_final_data.Simulation_convertsion(battery_raw_Simulation_sheet)
AdvanceSettingsDatabase_sheet = peak_shave_final_data.AdvanceSettingsDatabase_conversion(battery_raw_AdvanceSettingsDatabase_sheet)
Wirtschaftlichkeitsmatrix_sheet = peak_shave_final_data.Wirtschaftlichkeitsmatrix_conversion(battery_raw_Wirtschaftlichkeitsmatrix_sheet)
Wirtschaftlichkeitsmatrix_battery_configuration = peak_shave_final_data.Wirtschaftlichkeitsmatrix_SIunit_converter(Wirtschaftlichkeitsmatrix_Raw)
#profile setup for simulation
p_pv = np.array(PV_Profile['PV_profile'])
p_load = np.array(Load_Profile['Load_profile'])*-1
progress_bar.update(30) # 30% of progress for required values read from excel sheet
#general input
technical_input = dict(
p_cut_consumption_W = Eingabe_Übersicht_sheet.P_cut_consumption_W,
PV_W_peak = Eingabe_Übersicht_sheet.PV_Pinstall,
cp_rate = Eingabe_Übersicht_sheet.Cp_rate,
bat_capacity_E_Wh = Eingabe_Übersicht_sheet.Battery_energy_nominal,
DoD_pu = Simulation_sheet.DoD,
p_reserve_W = Eingabe_Übersicht_sheet.Battery_Pmax_reserve,
efficiency = Eingabe_Übersicht_sheet.Battery_efficiency,
SOC_target_pu = Eingabe_Übersicht_sheet.Battery_soll_soc_1,
SOC_reserve_pu = Eingabe_Übersicht_sheet.Battery_reserve_soc_1
)
eco_input = dict(
cost_pv_per_kWp = Eingabe_Übersicht_sheet.Investment_cost_PV,
cost_bat = Eingabe_Übersicht_sheet.Investment_cost_battery,
equity = Eingabe_Übersicht_sheet.Equity_share,
duration_funding_years = Eingabe_Übersicht_sheet.Financing_period,
duration_operation_years = Eingabe_Übersicht_sheet.Observation_period
)
general = {
'technical_input' : technical_input,
'eco_input' : eco_input
}
#advanced input
tech_param = dict(
SOC_start_pu= AdvanceSettingsDatabase_sheet.Battery_soc_start,
degradation = AdvanceSettingsDatabase_sheet.Degredation,
pv_deg_per_year = AdvanceSettingsDatabase_sheet.PV_degradation_per_year, #/a
bat_deg_per_year = AdvanceSettingsDatabase_sheet.Battery_degradation
)
maintanance_spare = dict(
maintained = AdvanceSettingsDatabase_sheet.Maintained,
pv_maintain_per_akWp = AdvanceSettingsDatabase_sheet.Maintenance_cost_PV,
bat_maintain_per_akWh = AdvanceSettingsDatabase_sheet.Maintenance_cost_battery,
pv_spare_per_akWp = AdvanceSettingsDatabase_sheet.PV_spare_per_kWp,
bat_spare_per_akWh = AdvanceSettingsDatabase_sheet.Bat_spare_per_kWh
)
insurance = dict(
pv_insured = AdvanceSettingsDatabase_sheet.Consider_insurance_PV,
pv_insurance_per_akWp = AdvanceSettingsDatabase_sheet.PV_insurance, #/kWp * a
bat_insured = AdvanceSettingsDatabase_sheet.Consider_insurance_bat,
bat_insurance_per_akWh = AdvanceSettingsDatabase_sheet.Battery_insurance #/kWp * a
)
finance = dict(
borrowed_interest = AdvanceSettingsDatabase_sheet.Borrowing_rate
)
tax = dict(
corporate_tax = AdvanceSettingsDatabase_sheet.Corporate_tax,
trade_tax = AdvanceSettingsDatabase_sheet.Trade_tax
)
discount = dict(
discounted = AdvanceSettingsDatabase_sheet.Consider_discounting,
discounting = AdvanceSettingsDatabase_sheet.Discount
)
price_per_unit = dict(
cost_current_jbd_below_per_kWh = AdvanceSettingsDatabase_sheet.Electricity_price_jbd_above_per_kWp,
cost_current_jbd_above_per_kWh = AdvanceSettingsDatabase_sheet.Electricity_price_jbd_below_per_kWp,
cost_power_jbd_below_per_kW = Eingabe_Übersicht_sheet.Power_price_jbd_above_per_kWp,
cost_power_jbd_above_per_kW = Eingabe_Übersicht_sheet.Power_price_jbd_below_per_kWp,
revenue_injected_current_per_kWh = Eingabe_Übersicht_sheet.Feedin_with_PPA_Direct_feedin_PV,
staggering_current_per_year = AdvanceSettingsDatabase_sheet.Electricity_price_increase_rate
)
lease = dict(
leased = AdvanceSettingsDatabase_sheet.Consider_lease,
needed_space_pv_ha_per_MWp = AdvanceSettingsDatabase_sheet.PV_space_requirement,
needed_space_bat_ha_per_MWh = AdvanceSettingsDatabase_sheet.Battery_space_requirement,
lease_pv_per_ha = AdvanceSettingsDatabase_sheet.PV_lease,
lease_bat_per_ha = AdvanceSettingsDatabase_sheet.Battery_lease
)
advanced = {
'tech_param': tech_param,
'maintanance_spare' : maintanance_spare,
'insurance' : insurance,
'finance' : finance,
'tax' : tax,
'discount' : discount,
'price_per_unit' : price_per_unit,
'lease' : lease
}
#other input not important
other_input = dict(
abschreibung_pv = 25_000,
abschreibung_bat = 13_750.66
)
profit_calc_params = {
'general' : general,
'advanced' : advanced,
'other_input' : other_input
}
W_matrix = {'energy_column_1': Wirtschaftlichkeitsmatrix_battery_configuration.energy_column_1,
'energy_column_2' : Wirtschaftlichkeitsmatrix_battery_configuration.energy_column_2,
'energy_column_3': Wirtschaftlichkeitsmatrix_battery_configuration.energy_column_3,
'energy_column_4' :Wirtschaftlichkeitsmatrix_battery_configuration.energy_column_4,
'energy_column_5': Wirtschaftlichkeitsmatrix_battery_configuration.energy_column_5,
'energy_column_6': Wirtschaftlichkeitsmatrix_battery_configuration.energy_column_6,
'energy_column_7' : Wirtschaftlichkeitsmatrix_battery_configuration.energy_column_7,
'energy_column_8' : Wirtschaftlichkeitsmatrix_battery_configuration.energy_column_8,
'energy_column_9' : Wirtschaftlichkeitsmatrix_battery_configuration.energy_column_9,
'energy_column_10' : Wirtschaftlichkeitsmatrix_battery_configuration.energy_column_10}
W_matrix_bool = {'energy_column_1': Wirtschaftlichkeitsmatrix_battery_configuration.energy_column_1_bool,
'energy_column_2' : Wirtschaftlichkeitsmatrix_battery_configuration.energy_column_2_bool,
'energy_column_3': Wirtschaftlichkeitsmatrix_battery_configuration.energy_column_3_bool,
'energy_column_4' :Wirtschaftlichkeitsmatrix_battery_configuration.energy_column_4_bool,
'energy_column_5': Wirtschaftlichkeitsmatrix_battery_configuration.energy_column_5_bool,
'energy_column_6': Wirtschaftlichkeitsmatrix_battery_configuration.energy_column_6_bool,
'energy_column_7' : Wirtschaftlichkeitsmatrix_battery_configuration.energy_column_7_bool,
'energy_column_8' : Wirtschaftlichkeitsmatrix_battery_configuration.energy_column_8_bool,
'energy_column_9' : Wirtschaftlichkeitsmatrix_battery_configuration.energy_column_9_bool,
'energy_column_10' : Wirtschaftlichkeitsmatrix_battery_configuration.energy_column_10_bool}
W_matrix_C_rate = {'C_Rate_row_1' : Wirtschaftlichkeitsmatrix_battery_configuration.C_Rate_row_1,
'C_Rate_row_2' : Wirtschaftlichkeitsmatrix_battery_configuration.C_Rate_row_2,
'C_Rate_row_3' : Wirtschaftlichkeitsmatrix_battery_configuration.C_Rate_row_3,
'C_Rate_row_4' : Wirtschaftlichkeitsmatrix_battery_configuration.C_Rate_row_4,
'C_Rate_row_5' : Wirtschaftlichkeitsmatrix_battery_configuration.C_Rate_row_5}
W_matrix_C_rate_bool = {'C_Rate_row_1' : Wirtschaftlichkeitsmatrix_battery_configuration.C_Rate_row_1_bool,
'C_Rate_row_2' : Wirtschaftlichkeitsmatrix_battery_configuration.C_Rate_row_2_bool,
'C_Rate_row_3' : Wirtschaftlichkeitsmatrix_battery_configuration.C_Rate_row_3_bool,
'C_Rate_row_4' : Wirtschaftlichkeitsmatrix_battery_configuration.C_Rate_row_4_bool,
'C_Rate_row_5' : Wirtschaftlichkeitsmatrix_battery_configuration.C_Rate_row_5_bool}
# Investtabelle battery cost setup
bats = []
for key in W_matrix:
if W_matrix_bool[key] == 'berechnen':
bats.append(W_matrix[key])
rates = []
for key in W_matrix_C_rate:
if W_matrix_C_rate_bool[key] == 'berechnen':
rates.append(W_matrix_C_rate[key])
investtable = pd.DataFrame(index = rates, columns = bats)
for bat in bats:
for rate in rates:
if Eingabe_Übersicht_sheet.Battery_type == 'Generisch':
battery_type_key = 'PB300'
else:
battery_type_key = Eingabe_Übersicht_sheet.Battery_type
try:
investtable[bat][rate] = Investtabelle_Raw[Eingabe_Übersicht_sheet.Battery_module][battery_type_key][Eingabe_Übersicht_sheet.Installation_site]['energy'+'_'+str(int(bat/1000))+'_C_rate_'+str(rate)]
except KeyError:
investtable[bat][rate]= 0
print("KeyError:", rate)
battery_type = Eingabe_Übersicht_sheet.Battery_type
SOC_res1 = Eingabe_Übersicht_sheet.Battery_reserve_soc_1
SOC_res2 = Eingabe_Übersicht_sheet.Battery_reserve_soc_2
SOC1_max = Wirtschaftlichkeitsmatrix_sheet.Soll_soc_1_max
SOC1_min = Wirtschaftlichkeitsmatrix_sheet.Soll_soc_1_min
SOC2_max = Wirtschaftlichkeitsmatrix_sheet.Soll_soc_2_max
SOC2_min = Wirtschaftlichkeitsmatrix_sheet.Soll_soc_2_min
SOC_step_percent = Wirtschaftlichkeitsmatrix_sheet.Step_size_soc
accuracy = Wirtschaftlichkeitsmatrix_sheet.Break_off_precision_peakshaving
finanzierung = Wirtschaftlichkeitsmatrix_sheet.Financing
SOC_start = AdvanceSettingsDatabase_sheet.Battery_soc_start
year_list = get_year_list(Eingabe_Übersicht_sheet.Battery_soll_soc_2_start,Eingabe_Übersicht_sheet.Battery_soll_soc_2_end)
timestep =0.25 #=15min
progress_bar.update(50) # 50% of progress for pre process done and simulation is starting
# Simulation
amount_SOCs = Wirtschaftlichkeitsmatrix_sheet.Number_of_SOCs
algorithm = Wirtschaftlichkeitsmatrix_sheet.Algorithm_for_12_SOCs
simulation = Wirtschaftlichkeitsmatrix_sheet.Year_simulation_of_the_best_system
if amount_SOCs == 2:
w_matrix, wartung = w_matrix_modular_excel(p_load, p_pv,0,SOC_res1, SOC_res2, SOC_start, SOC1_min, SOC1_max, SOC2_min, SOC2_max,SOC_step_percent, accuracy, Wirtschaftlichkeitsmatrix_sheet.Consideration_case,finanzierung,bats,rates, profit_calc_params, investtable, battery_type,year_list, timestep)
else:
if algorithm == 'dispatcher':
algo = 1
elif algorithm == 'brute-force':
algo = 2
else:
algo = 3
w_matrix = w_matrix_modular_monthly(algo, p_load, p_pv, SOC_start, SOC1_min, SOC1_max, SOC_step_percent, Wirtschaftlichkeitsmatrix_sheet.Consideration_case,finanzierung,bats,rates, profit_calc_params, investtable, battery_type, timestep)
system,bat_capacity_E,c_rate = get_most_profitable_system(w_matrix)
progress_bar.update(80) # 80% of progress for Simulation done and writing results
if simulation == 'EXCEL' and amount_SOCs == 2:
Peakshave_Reader.write_Best_system_to_excel(excel_workbook,matrix_data=system,bat_energie=bat,c_rate=c_rate)
Peakshave_Reader.write_matrixdata_SOCs_to_excel(excel_workbook,number_of_SOCs=amount_SOCs,Profit_calculator_matrix_result=w_matrix)
##just write the data back, no simulatioon
elif simulation == 'BETSI':
pass
#results = GlobalFactory
#write it back
else:
results = do_simulation_with_numba(p_load, p_pv, system, bat_capacity_E, c_rate, battery_type, SOC_start, year_list)
Peakshave_Reader.write_Best_system_to_excel(excel_workbook,matrix_data=system,bat_energie=bat,c_rate=c_rate)
Peakshave_Reader.write_data_to_excel(excel_workbook,data=results)
Peakshave_Reader.write_matrixdata_SOCs_to_excel(excel_workbook,number_of_SOCs=amount_SOCs,Profit_calculator_matrix_result=w_matrix)
#write it back
progress_bar.update(100) # 100% process completed
# Define GUI layout
layout = [[sg.Text("Select Excel file:")], # For title
[sg.Input(key="-FILE-"), sg.FileBrowse(file_types=(("Excel Files", "*.xlsb"),))], # Browse button configuration
[sg.ProgressBar(100, orientation='h', size=(20, 20), key='-PROGRESS-')], # progress bar configuration
[sg.Button("Process"), sg.Button("Stop")]] # cancel button & process button configuration
# Create GUI window
window = sg.Window("Peak Shave Simualtion", layout ,icon="C:\Env\Profit_calculator\Tricera-logo.ico") # main window configuration
progress_bar = window['-PROGRESS-']
# Event loop
while True:
event, values = window.read()
if event == sg.WIN_CLOSED or event == 'Cancel': # if closed or click on cancel button window will close
break
elif event == 'Process':
file_path = values['-FILE-']
start_time = time.time()
Python_profitcalculator_simulation(file_path)
end_time = time.time()
sg.popup(f"Processing complete!\nSimulation total time: {(f'{((end_time - start_time)/60):.2f} minutes' if (end_time - start_time) >= 60 else f'{(end_time - start_time):.2f} seconds')}")
break
elif event == 'Stop':
**What should i write here**
# Close GUI window
window.close()