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import requests
import pandas as pd
import json
translation_dict = {
'VindkraftAnleggId': 'WindPowerPlantId',
'Navn': 'Name',
'IdriftsettelseForsteByggetrinn': 'CommissioningFirstPhase',
'AnleggsNr': 'FacilityNumber',
'InstallertEffekt_MW': 'InstalledCapacity_MW',
'HovedEierNavn': 'MainOwnerName',
'HovedEierOrgNr': 'MainOwnerOrgNumber',
'ElspotomraadeNummer': 'ElspotAreaNumber',
'Fylke': 'County',
'Kommune': 'Municipality',
'NormalAArsproduksjon_GWh': 'NormalAnnualProduction_GWh',
'GjsnittGeneratorytelse': 'AvgGeneratorOutput',
'GjsnittNavhoeyde': 'AvgHubHeight',
'GjsnittRotordiameter': 'AvgRotorDiameter',
'EnergiPerSveiptAreal': 'EnergyPerSweptArea',
'AntallOperativeTurbiner': 'NumberOfOperationalTurbines',
'AnlKonsNr_Vind': 'FacilityPermitNumber_Wind',
'AntallTurbiner': 'NumberOfTurbines',
'DatoIdriftsatt': 'CommissioningDate',
'DatoUtavdrift': 'DecommissioningDate',
'ForventetProd_NormalAAr_GWh': 'ExpectedProduction_NormalYear_GWh',
'KR_Saksid': 'NVE_CaseId',
'TurbinID': 'TurbineID',
'TurbinProdusent': 'TurbineManufacturer',
'TurbinStorrelse_kW': 'TurbineSize_kW',
'TurbinType': 'TurbineType',
'TurbintypeID': 'TurbineTypeID',
}
def translate_keys_recursive(obj, translation_dict):
if isinstance(obj, dict):
return {
translation_dict.get(k, k): translate_keys_recursive(v, translation_dict)
for k, v in obj.items()
}
elif isinstance(obj, list):
return [translate_keys_recursive(item, translation_dict) for item in obj]
else:
return obj
def get_power():
output_path = 'data/vindprod2002-2024_kraftverk_utcplus1.xlsx'
url = 'https://www.nve.no/media/18018/vindprod2002-2024_kraftverk_utcplus1.xlsx'
response = requests.get(url)
with open(output_path, 'wb') as f:
f.write(response.content)
print("Power data saved to:", output_path)
def get_metadata():
output_path = 'data/metadata.json'
url = 'https://api.nve.no/web/WindPowerplant/GetWindPowerPlants'
# url = "https://api.nve.no/web/WindPowerplant/GetWindPowerPlantsInOperation"
response = requests.get(url)
data = response.json()
with open(output_path, 'w', encoding='utf-8') as f:
json.dump(data, f, indent=4, ensure_ascii=False)
print("Metadata saved to:", output_path)
def get_geodata():
output_path = 'data/geodata.json'
latlon_wkid = 4326
url = f'https://nve.geodataonline.no/arcgis/rest/services/Vindkraft2/MapServer/0/query?f=json&cacheHint=true&resultOffset=0&resultRecordCount=1000&where=1%3D1&orderByFields=OBJECTID&outFields=*&outSR={latlon_wkid}&spatialRel=esriSpatialRelIntersects'
response = requests.get(url)
data = response.json()
with open(output_path, 'w', encoding='utf-8') as f:
json.dump(data, f, indent=4, ensure_ascii=False)
print("Geodata saved to:", output_path)
def extract_meta():
output_path_1 = 'nve-windpower-metadata.csv'
output_path_2 = 'nve-windpower-metadata-extended.csv'
file_path_1 = 'data/metadata.json'
file_path_2 = 'data/geodata.json'
with open(file_path_1, 'r', encoding='utf-8') as f:
metadata = json.load(f)
with open(file_path_2, 'r', encoding='utf-8') as f:
geodata = json.load(f)
metadata = translate_keys_recursive(metadata, translation_dict)
# Convert to pandas dataframe
metadata_df = pd.DataFrame(metadata)
geodata_df = pd.DataFrame([{'name': park_feature['attributes']['anleggNavn'],
'code': park_feature['attributes']['anleggsNr'],
'capacity_MW': park_feature['attributes']['effekt_MW'],
'no_turbines': park_feature['attributes']['antallTurbiner'],
'start_date': pd.to_datetime(park_feature['attributes']['forsteIdriftDato'], unit='ms'),
'lat': park_feature['geometry']['y'],
'lon': park_feature['geometry']['x']
}
for park_feature in geodata['features']])
metadata_df = metadata_df.set_index('FacilityNumber')
geodata_df = geodata_df.set_index('code')
# Add lat and lon from geodata_df
metadata_df['lat'] = geodata_df['lat']
metadata_df['lon'] = geodata_df['lon']
# Reset index
metadata_df = metadata_df.reset_index()
# Set colums as int
for c in ['WindPowerPlantId','FacilityNumber','MainOwnerOrgNumber','ElspotAreaNumber','NumberOfOperationalTurbines']:
metadata_df[c] = pd.to_numeric(metadata_df[c], errors='coerce').astype('Int64')
# Remove column with turbine meta
metadata_df1 = metadata_df.copy()
metadata_df1 = metadata_df1.drop('Turbiner', axis=1)
metadata_df1 = metadata_df1.set_index('WindPowerPlantId').sort_index()
# Explode turbine list
df_exploded = metadata_df.explode('Turbiner').reset_index(drop=True)
# Normalize turbine dictionaries into columns
data_normalized = pd.json_normalize(df_exploded['Turbiner'])
# Combine with original dataframe (without the old turbine column)
metadata_df2 = pd.concat([df_exploded.drop(columns='Turbiner'), data_normalized], axis=1)
metadata_df2 = metadata_df2.set_index('WindPowerPlantId').sort_index()
# Save dataframe as cvs
metadata_df1.to_csv(output_path_1, index=True)
metadata_df2.to_csv(output_path_2, index=True)
def extract_power():
output_path = 'nve-windpower-timeseries.csv'
file_path = 'data/vindprod2002-2024_kraftverk_utcplus1.xlsx'
power = pd.read_excel(file_path, header=1, skiprows=[2])
power = power.rename(columns={'kraftverknr':'datetime'})
power = power.set_index('datetime')
power.index = pd.to_datetime(power.index, utc=True)
# Sort by park id
power = power[sorted(power.columns)]
# Save dataframe as cvs
power.to_csv(output_path, index=True)
if __name__ == '__main__':
get_power()
get_metadata()
extract_meta()
extract_power()
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