Datasets for "Irradiance and cloud optical properties from solar photovoltaic systems" (final version)

This dataset contains all the relevant data for the algorithms described in the paper "Irradiance and cloud optical properties from solar photovoltaic systems", which were developed within the framework of the MetPVNet project.

Input data:

1. COSMO weather model data (DWD) as NetCDF files (cosmo_d2_2018(9).tar.gz)
   1. COSMO atmospheres for libRadtran (cosmo_atmosphere_libradtran_input.tar.gz)
   2. COSMO surface data for calibration (cosmo_pvcal_output.tar.gz)
2. Aeronet data as text files (MetPVNet_Aeronet_Input_Data.zip)
3. Measured data from the MetPVNet measurement campaigns as text files (MetPVNet_Messkampagne_2018(9).tar.gz)
   1. PV power data
   2. Horizontal and tilted irradiance from pyranometers
   3. Longwave irradiance from pyrgeometer
4. MYSTIC-based lookup table for translated tilted to horizontal irradiance (gti2ghi_lut_v1.nc)

Output data:

1. Global tilted irradiance (GTI) inferred from PV power plants (with calibration parameters in comments)
   1. Linear temperature model: MetPVNet_gti_cf_inversion_results_linear.tar.gz
   2. Faiman non-linear temperature model: MetPVNet_gti_cf_inversion_results_faiman.tar.gz
2. Global horizontal irradiance (GHI) inferred from PV power plants
   1. Linear temperature model: MetPVNet_ghi_inversion_results_linear.tar.gz
   2. Faiman non-linear temperature model: MetPVNet_ghi_inversion_results_faiman.tar.gz
3. Combined GHI averaged to 60 minutes and compared with COSMO data
   1. Linear temperature model: MetPVNet_ghi_inversion_combo_60min_results_linear.tar.gz
   2. Faiman non-linear temperature model: MetPVNet_ghi_inversion_combo_60min_results_faiman.tar.gz
4. Cloud optical depth inferred from PV power plants
   1. Linear temperature model: MetPVNet_cod_cf_inversion_results_linear.tar.gz
   2. Faiman non-linear temperature model: MetPVNet_cod_cf_inversion_results_faiman.tar.gz
5. Combined COD averaged to 60 minutes and compared with COSMO and APOLLO_NG data
   1. Linear temperature model: MetPVNet_cod_inversion_combo_60min_results_linear.tar.gz
   2. Faiman non-linear temperature model: MetPVNet_cod_inversion_combo_60min_results_faiman.tar.gz

Validation data:

1. COSMO cloud optical depth (cosmo_cod_output.tar.gz)
2. APOLLO_NG cloud optical depth (MetPVNet_apng_extract_all_stations_2018(9).tar.gz)
3. COSMO irradiance data for validation (cosmo_irradiance_output.tar.gz)
4. CAMS irradiance data for validation (CAMS_irradiation_detailed_MetPVNet_MK_2018(9).zip)

How to import results:

The results files are stored as text files ".dat", using Python multi-index columns. In order to import the data into a Pandas dataframe, use the following lines of code (replace [filename] with the relevant file name):

import pandas as pd
data = pd.read_csv("[filename].dat",comment='#',header=[0,1],delimiter=';',index_col=0,parse_dates=True)

This gives a multi-index Dataframe with the index column the timestamp, the first column label corresponds to the measured variable and the second column to the relevant sensor

Note:

The output data has been updated to match the latest version of the paper, whereas the input and validation data remains the same as in Version 1.0.0