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:

COSMO weather model data (DWD) as NetCDF files (cosmo_d2_2018(9).tar.gz)

COSMO atmospheres for libRadtran (cosmo_atmosphere_libradtran_input.tar.gz)

COSMO surface data for calibration (cosmo_pvcal_output.tar.gz)

Aeronet data as text files (MetPVNet_Aeronet_Input_Data.zip)

Measured data from the MetPVNet measurement campaigns as text files (MetPVNet_Messkampagne_2018(9).tar.gz)

PV power data

Horizontal and tilted irradiance from pyranometers

Longwave irradiance from pyrgeometer

MYSTIC-based lookup table for translated tilted to horizontal irradiance (gti2ghi_lut_v1.nc)

Output data:

Global tilted irradiance (GTI) inferred from PV power plants (with calibration parameters in comments)

Linear temperature model: MetPVNet_gti_cf_inversion_results_linear.tar.gz

Faiman non-linear temperature model: MetPVNet_gti_cf_inversion_results_faiman.tar.gz

Global horizontal irradiance (GHI) inferred from PV power plants

Linear temperature model: MetPVNet_ghi_inversion_results_linear.tar.gz

Faiman non-linear temperature model: MetPVNet_ghi_inversion_results_faiman.tar.gz

Combined GHI averaged to 60 minutes and compared with COSMO data

Linear temperature model: MetPVNet_ghi_inversion_combo_60min_results_linear.tar.gz

Faiman non-linear temperature model: MetPVNet_ghi_inversion_combo_60min_results_faiman.tar.gz

Cloud optical depth inferred from PV power plants

Linear temperature model: MetPVNet_cod_cf_inversion_results_linear.tar.gz

Faiman non-linear temperature model: MetPVNet_cod_cf_inversion_results_faiman.tar.gz

Combined COD averaged to 60 minutes and compared with COSMO and APOLLO_NG data

Linear temperature model: MetPVNet_cod_inversion_combo_60min_results_linear.tar.gz

Faiman non-linear temperature model: MetPVNet_cod_inversion_combo_60min_results_faiman.tar.gz

Validation data:

COSMO cloud optical depth (cosmo_cod_output.tar.gz)

APOLLO_NG cloud optical depth (MetPVNet_apng_extract_all_stations_2018(9).tar.gz)

COSMO irradiance data for validation (cosmo_irradiance_output.tar.gz)

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 pddata = 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

本数据集涵盖论文《太阳能光伏系统的辐照度与云光学特性》中所述算法的全部关联数据，所有算法均在MetPVNet项目框架下开发。

输入数据：

- COSMO气象模式数据（DWD），格式为NetCDF文件（cosmo_d2_2018(9).tar.gz）
- 用于libRadtran的COSMO大气数据（cosmo_atmosphere_libradtran_input.tar.gz）
- 用于校准的COSMO地表数据（cosmo_pvcal_output.tar.gz）
- Aeronet数据，格式为文本文件（MetPVNet_Aeronet_Input_Data.zip）
- MetPVNet观测活动的实测数据，格式为文本文件（MetPVNet_Messkampagne_2018(9).tar.gz）
- 光伏功率数据：总辐射表（pyranometer）测得的水平与倾斜辐照度、长波辐射表（pyrgeometer）测得的长波辐照度
- 基于MYSTIC的倾斜辐照度转水平辐照度查找表（gti2ghi_lut_v1.nc）

输出数据：

- 由光伏电站反演得到的全球倾斜辐照度（Global Tilted Irradiance, GTI），校准参数存于注释中
- 线性温度模型结果：MetPVNet_gti_cf_inversion_results_linear.tar.gz
- 费曼（Faiman）非线性温度模型结果：MetPVNet_gti_cf_inversion_results_faiman.tar.gz
- 由光伏电站反演得到的全球水平辐照度（Global Horizontal Irradiance, GHI）
- 线性温度模型结果：MetPVNet_ghi_inversion_results_linear.tar.gz
- 费曼非线性温度模型结果：MetPVNet_ghi_inversion_results_faiman.tar.gz
- 经60分钟平均后的合并GHI数据，并与COSMO模式数据对比
- 线性温度模型结果：MetPVNet_ghi_inversion_combo_60min_results_linear.tar.gz
- 费曼非线性温度模型结果：MetPVNet_ghi_inversion_combo_60min_results_faiman.tar.gz
- 由光伏电站反演得到的云光学深度（Cloud Optical Depth, COD）
- 线性温度模型结果：MetPVNet_cod_cf_inversion_results_linear.tar.gz
- 费曼非线性温度模型结果：MetPVNet_cod_cf_inversion_results_faiman.tar.gz
- 经60分钟平均后的合并COD数据，并与COSMO和APOLLO_NG数据对比
- 线性温度模型结果：MetPVNet_cod_inversion_combo_60min_results_linear.tar.gz
- 费曼非线性温度模型结果：MetPVNet_cod_inversion_combo_60min_results_faiman.tar.gz

验证数据：

- COSMO云光学深度数据（cosmo_cod_output.tar.gz）
- APOLLO_NG云光学深度数据（MetPVNet_apng_extract_all_stations_2018(9).tar.gz）
- 用于验证的COSMO辐照度数据（cosmo_irradiance_output.tar.gz）
- 用于验证的CAMS辐照度数据（CAMS_irradiation_detailed_MetPVNet_MK_2018(9).zip）

结果导入方法：
结果文件以.dat文本格式存储，采用Python多索引列。若需将数据导入Pandas数据框，请使用以下代码（将[filename]替换为对应文件名）：
python
import pandas as pd
data = pd.read_csv("[filename].dat", comment='#', header=[0,1], delimiter=';', index_col=0, parse_dates=True)

该代码将生成一个多索引数据框，其中索引列为时间戳，第一列标签对应实测变量，第二列标签对应相关传感器。

备注：
本输出数据已更新至与论文最新版本匹配，而输入数据与验证数据仍保持1.0.0版本的内容不变。