import pandas as pd
import numpy as np
import csv

sunlight_file_name = 'lightintensity.xlsx'
factory_demand_file_name = 'factory_power1.xlsx'
electricity_price_data = 'electricity_price_data.csv'
electricity_price_data_sell = 'electricity_price_data_sell.csv'

df_sunlight = pd.read_excel(sunlight_file_name, header=None, names=['SunlightIntensity'])

start_date = '2023-01-01 00:00:00'  # 根据数据的实际开始日期调整
hours = pd.date_range(start=start_date, periods=len(df_sunlight), freq='h')
df_sunlight['Time'] = hours
df_sunlight.set_index('Time', inplace=True)

df_sunlight_resampled = df_sunlight.resample('15min').interpolate()

df_power = pd.read_excel(factory_demand_file_name, 
                         header=None, 
                         names=['FactoryPower'], 
                         dtype={'FactoryPower': float})
times = pd.date_range(start=start_date, periods=len(df_power), freq='15min')
df_power['Time'] = times
df_power.set_index('Time',inplace=True)
print(df_power.head())

df_combined = df_sunlight_resampled.join(df_power)

    

price_df = pd.read_csv(electricity_price_data, index_col='Time', usecols=['Time', 'ElectricityBuy'])
price_df.index = pd.to_datetime(price_df.index)
price_df = price_df.reindex(df_combined.index)

print("Electricity price data generated and saved.")
df_combined2 = df_combined.join(price_df)

sell_df = pd.read_csv(electricity_price_data_sell, index_col='Time', usecols=['Time', 'ElectricitySell'])
sell_df.index = pd.to_datetime(sell_df.index)
sell_df = sell_df.reindex(df_combined.index)

df_combined3 = df_combined2.join(sell_df)

with open('combined_data.csv', 'w', newline='') as file:
    writer = csv.writer(file)
    writer.writerow(['time', 'sunlight', 'demand','buy', 'sell'])
    cnt = 0
    for index, row in df_combined3.iterrows():
        time_formatted = index.strftime('%H:%M')
        writer.writerow([time_formatted, row['SunlightIntensity'], row['FactoryPower'],row['ElectricityBuy'], row['ElectricitySell']])
        
    print('The file is written to combined_data.csv')

# combined_data.to_csv('updated_simulation_with_prices.csv', index=False)

print("Simulation data with electricity prices has been updated and saved.")