def query_entsoe_load(start, end):
client = EntsoePandasClient(api_key=os.environ['ENTSOE_TOKEN'])
data = client.query_load("ES",
start=pd.Timestamp(start, tz='UTC'),
end=pd.Timestamp(end, tz='UTC'))
return data
def query_entsoe_load(start, end):
client = EntsoePandasClient(
api_key='909addb7-e4ae-4702-acc7-6b4f4fd9667b')
data = client.query_load("ES",
start=pd.Timestamp(start, tz='UTC'),
end=pd.Timestamp(end, tz='UTC'))
return data
def get_entsoe_data(key, country='ES', date=None, period=None):
start, end = get_date_range()
client = EntsoePandasClient(api_key=key)
data = client.query_load(country, start=start, end=end)
return data
# =============================================================================
# Get Data from Entso-E
# API Wrapper: https://github.com/EnergieID/entsoe-py
# =============================================================================
#"""
key = str(np.genfromtxt('entsoe.txt', dtype='str'))
client = EntsoePandasClient(api_key=key)
# Time Series
# NoMatchingDataError
# ts_day_ahead = client.query_day_ahead_prices(country_code, start=start,end=end)
ts_load = client.query_load(country_code, start=start, end=end)
ts_load.to_csv('data_base/ts_load.csv')
ts_load_forecast = client.query_load_forecast(country_code,
start=start,
end=end)
ts_load_forecast.to_csv('data_base/ts_load_forecast.csv')
ts_generation_forecast = client.query_generation_forecast(country_code,
start=start,
end=end)
ts_generation_forecast.to_csv('data_base/ts_generation_forecast.csv')
# Dataframes
df_wind_and_solar_forecast = client.query_wind_and_solar_forecast(
start, end = pd.Timestamp('20190101', tz='Europe/Brussels'), pd.Timestamp(
'20190501', tz='Europe/Brussels')
start2, end2 = pd.Timestamp('20200101', tz='Europe/Brussels'), pd.Timestamp(
'20200501', tz='Europe/Brussels')
for country_code in [
'DE-LU', 'BE', 'DK', 'AT', 'BG', 'CH', 'CZ', 'EE', 'ES', 'FI', 'FR',
'GB', 'GR', 'HR', 'HU', 'IE', 'IT', 'NL', 'NO', 'PL', 'PT', 'RO', 'SE'
]:
try:
#download load data
pd.concat([
client.query_load(country_code, start=start, end=end),
client.query_load(country_code, start=start2, end=end2)
]).to_csv('./data/load_' + country_code + '.csv')
#download generation data
pd.concat([
client.query_generation(country_code,
start=start,
end=end,
psr_type=None),
client.query_generation(country_code,
start=start2,
end=end2,
psr_type=None)
]).to_csv('./data/gen' + country_code + '.csv')
except:
from entsoe import EntsoePandasClient
import sqlite3
import pandas as pd
from datetime import date, timedelta
import time
end_date = date.today() + timedelta(days=1)
current_date = end_date.strftime("%Y%m%d")
client = EntsoePandasClient(api_key='444fc771-5d0f-499f-9328-90c05c459219')
start = pd.Timestamp('20201109', tz='Europe/Brussels')
end = pd.Timestamp(current_date, tz='Europe/Brussels')
country_code = 'DE'
generation = client.query_load(country_code, start=start, end=end)
generation1.to_csv('outfile1.csv')
print(generation1)
start = pd.Timestamp('20201109', tz='Europe/Brussels')
end_date = date.today() + timedelta(days=2)
current_date = end_date.strftime("%Y%m%d")
end = pd.Timestamp(current_date, tz='Europe/Brussels')
country_code = 'DE'
generation2 = client.query_load_forecast(country_code, start=start, end=end)
generation2.to_csv('outfile2.csv')
print(generation2)
