57 lines
2.0 KiB
Python
57 lines
2.0 KiB
Python
import pandas as pd
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import numpy as np
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import csv
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sunlight_file_name = 'lightintensity.xlsx'
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factory_demand_file_name = 'factory_power1.xlsx'
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df_sunlight = pd.read_excel(sunlight_file_name, header=None, names=['SunlightIntensity'])
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start_date = '2023-01-01 00:00:00' # 根据数据的实际开始日期调整
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hours = pd.date_range(start=start_date, periods=len(df_sunlight), freq='h')
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df_sunlight['Time'] = hours
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df_sunlight.set_index('Time', inplace=True)
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df_sunlight_resampled = df_sunlight.resample('15min').interpolate()
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df_power = pd.read_excel(factory_demand_file_name,
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header=None,
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names=['FactoryPower'],
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dtype={'FactoryPower': float})
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times = pd.date_range(start=start_date, periods=len(df_power), freq='15min')
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df_power['Time'] = times
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df_power.set_index('Time',inplace=True)
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print(df_power.head())
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df_combined = df_sunlight_resampled.join(df_power)
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df_combined.to_csv('combined_data.csv', index=True, index_label='Time')
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price_data = np.random.uniform(0.3, 0.3, len(times))
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# 创建DataFrame
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price_df = pd.DataFrame(data={'Time': times, 'ElectricityPrice': price_data})
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price_df.set_index('Time', inplace=True)
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# 保存到CSV文件
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price_df.to_csv('electricity_price_data.csv', index=True)
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print(price_df.head())
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print("Electricity price data generated and saved.")
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df_combined2 = df_combined.join(price_df)
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print(df_combined2.head())
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# 保存结果
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with open('combined_data.csv', 'w', newline='') as file:
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writer = csv.writer(file)
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writer.writerow(['time', 'sunlight', 'demand','price'])
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cnt = 0
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for index, row in df_combined2.iterrows():
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time_formatted = index.strftime('%H:%M')
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writer.writerow([time_formatted, row['SunlightIntensity'], row['FactoryPower'],row['ElectricityPrice']])
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print('The file is written to combined_data.csv')
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# combined_data.to_csv('updated_simulation_with_prices.csv', index=False)
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print("Simulation data with electricity prices has been updated and saved.") |