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import numpy as np | |
import pandas as pd | |
import pvlib | |
f = pd.read_csv("osm_m_pl_geokod.csv", dtype={'city': 'str', 'county': 'str', 'state': 'str', | |
'lat':np.float64, 'lon':np.float64, | |
'place_id':'Int64', 'osm_id':'Int64', 'display_name':'str'}) | |
# calculate power of pv installation | |
def obtain_pv_power_from_PVGIS(lat, lon): | |
poa, _, _ = pvlib.iotools.get_pvgis_hourly( | |
latitude = lat, | |
longitude = lon, | |
start = pd.Timestamp('2020-01-01'), | |
end = pd.Timestamp('2020-12-31'), | |
raddatabase = 'PVGIS-SARAH2', | |
components = True, | |
surface_tilt = 0, | |
surface_azimuth = 0, | |
pvcalculation = True, | |
peakpower = 1, | |
pvtechchoice = 'crystSi', | |
mountingplace = 'free', | |
loss = 0, | |
trackingtype = 0, | |
url='https://re.jrc.ec.europa.eu/api/v5_2/', | |
) | |
poa['P'] = poa['P'].div(1000) | |
return poa | |
def obtain_power_for_location(lat, lon): | |
try: | |
poa = obtain_pv_power_from_PVGIS(lat, lon) | |
return poa['P'].sum() | |
except: | |
return None | |
places['power'] = places.apply(lambda row: obtain_power_for_location(row.lat,row.lon), axis=1) |
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