51 lines
1.9 KiB
Python
51 lines
1.9 KiB
Python
import pandas as pd
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import numpy as np
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import csv
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pv_yield_file_name = 'read_data/Riyahd.csv'
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factory_demand_file_name = 'factory_power1.xlsx'
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electricity_price_data = 'electricity_price_data.csv'
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electricity_price_data_sell = 'electricity_price_data_sell.csv'
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pv_df = pd.read_csv(pv_yield_file_name, index_col='Time', usecols=['Time', 'PV yield[kW/kWp]'])
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pv_df.index = pd.to_datetime(pv_df.index)
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start_date = '2023-01-01'
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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 = pv_df.join(df_power)
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price_df = pd.read_csv(electricity_price_data, index_col='Time', usecols=['Time', 'ElectricityBuy'])
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price_df.index = pd.to_datetime(price_df.index)
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price_df = price_df.reindex(df_combined.index)
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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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sell_df = pd.read_csv(electricity_price_data_sell, index_col='Time', usecols=['Time', 'ElectricitySell'])
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sell_df.index = pd.to_datetime(sell_df.index)
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sell_df = sell_df.reindex(df_combined.index)
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df_combined3 = df_combined2.join(sell_df)
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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', 'PV yield[kW/kWp]', 'demand','buy', 'sell'])
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cnt = 0
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for index, row in df_combined3.iterrows():
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time_formatted = index.strftime('%H:%M')
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writer.writerow([time_formatted, row['PV yield[kW/kWp]'], row['FactoryPower'],row['ElectricityBuy'], row['ElectricitySell']])
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print('The file is written to combined_data.csv')
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print("Simulation data with electricity prices has been updated and saved.") |