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Data_Base_Creation.py
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Oct 16 12:30:09 2019
@author: balderrama
"""
import pandas as pd
data = pd.DataFrame()
#Status = pd.read_excel('status1.xls', index_col=0, Header=None)
for i in range(50,570,50):
for n in range(150):
path = 'Results/Results_' + str(i) + '_'+ str(n) + '.xls'
name = str(i) + '_'+ str(n)
print(name)
# renewable source data
Data_Renewable = pd.read_excel(path, index_col=0, Header=None, sheet_name='Data Renewable')
data.loc[name, 'Renewable Invesment Cost'] = Data_Renewable['Source 1']['Invesment (USD)']
data.loc[name, 'Renewable OyM Cost'] = Data_Renewable['Source 1']['OyM Cost (USD)']
data.loc[name, 'Renewable Capacity'] = Data_Renewable['Source 1']['Total Nominal Capacity (W)']
# Battery data
Data_Battery = pd.read_excel(path, index_col=0, Header=None, sheet_name='Battery Data')
data.loc[name, 'Battery Invesment Cost'] = Data_Battery['Battery']['Invesment Cost (USD)']
data.loc[name, 'Battery OyM Cost'] = Data_Battery['Battery']['OyM Cost (USD)']
data.loc[name, 'Battery Capacity'] = Data_Battery['Battery']['Nominal Capacity (Wh)']
# Battery_Discharge_Rate = Data_Battery['Battery']['Nominal Capacity (Wh)']
# generator data
Data_Generator = pd.read_excel(path, index_col=0, Header=None, sheet_name='Generator Data')
data.loc[name, 'Generator Invesment Cost'] = Data_Generator['Generator 1']['Invesment Generator (USD)']
data.loc[name, 'Generator OyM Cost'] = Data_Generator['Generator 1']['OyM Cost (USD)']
# Time Series Data
Data_Time_series = pd.read_excel(path, index_col=0, Header=None, sheet_name='Time Series')
data.loc[name, 'Max Demand'] = Data_Time_series['Energy Demand 1 (Wh)'].max()
data.loc[name, 'Mean Demand'] = Data_Time_series['Energy Demand 1 (Wh)'].mean()
data.loc[name, 'Total Demand'] = Data_Time_series['Energy Demand 1 (Wh)'].sum()
Renewable_Energy = Data_Time_series['Renewable Energy 1 (Wh)'].sum()
Generator_Energy = Data_Time_series['Gen energy 1 (Wh)'].sum()
Renewable_Penetration = Renewable_Energy/(Renewable_Energy+Generator_Energy)
data.loc[name, 'Renewable Penetration'] = Renewable_Penetration
Curtailment = Data_Time_series['Curtailment 1 (Wh)'].sum()
data.loc[name, 'Curtailment Percentage'] = (Curtailment/(Renewable_Energy+Generator_Energy))*100
Battery_Energy = Data_Time_series['Battery Flow Out 1 (Wh)'].sum()
data.loc[name, 'Battery Usage Percentage'] = (Battery_Energy/data.loc[name, 'Total Demand'])*100
# Solar time series
Data_Renewable_series = pd.read_excel(path, index_col=0, Header=None, sheet_name='Renewable Energy Time Series')
data.loc[name, 'Renewable Energy Unit Total'] = Data_Renewable_series['Renewable unit 1 1 (Wh)'].sum()
Results = pd.read_excel(path, index_col=0, Header=None, sheet_name='Results')
data.loc[name, 'NPC'] = Results['Data']['NPC (USD)']
data.loc[name, 'LCOE'] = Results['Data']['LCOE (USD/kWh)']
data.loc[name, 'Operation Cost'] = Results['Data']['Present Operation Cost Weighted (USD)']
# Variables independientes
data.loc[name, 'Renewable Unitary Invesment Cost'] = Data_Renewable['Source 1']['Investment Cost (USD/W)']
data.loc[name, 'Battery Unitary Invesment Cost'] = Data_Battery['Battery']['Unitary Invesment Cost (USD/Wh)']
data.loc[name, 'Deep of Discharge'] = Data_Battery['Battery']['Deep of Discharge']
data.loc[name, 'Battery Cycles'] = Data_Battery['Battery']['Battery Cycles']
data.loc[name, 'GenSet Unitary Invesment Cost'] = Data_Generator['Generator 1']['Generator Invesment Cost (USD/W)']
data.loc[name, 'Generator Efficiency'] = Data_Generator['Generator 1']['Generator Efficiency']
data.loc[name, 'Low Heating Value'] = Data_Generator['Generator 1']['Low Heating Value (Wh/l)']
data.loc[name, 'Fuel Cost'] = Data_Generator['Generator 1']['Fuel Cost (USD/l)']
data.loc[name, 'Generator Nominal capacity'] = Data_Generator['Generator 1']['Generator Nominal Capacity (W)']
data.loc[name, 'Generator Number'] = Data_Generator['Generator 1']['Number of Generators']
data.loc[name,'HouseHolds'] = i
# data.loc[name,'Gap'] = Status.loc[name, 'Gap']
# data.loc[name,'Time'] = Status.loc[name, 'Time']
# data.loc[name,'Y'] = -Status.loc[name, 'Y_deg']
data = round(data,2)
data.to_excel('Data_Base.xls')