In this document
We will teach you how to perform a solar radiation data quality check on your dataset.
Solar radiation data quality check (QC) must be performed to ensure the integrity and reliability of the measured solar irradiance data. Without these checks, issues such as sensor faults, shading, miscalibration, or data anomalies may remain undetected, leading to misleading results in downstream energy yield assessments and performance analyses. This quality control step ensures the dataset accurately reflects site conditions and meets data validation standards before further processing.
Key points to remember:
Correct time reference checks must be done first to ensure there are no time shifts left in the dataset.
This check utilises test groups usually defined in the Metadata editor, but you can still create and edit them in the solar radiation data check window.
The solar radiation data QC may take some time depending on the size of the tested dataset.
A flag column for each parameter will be added to the dataset upon this check to store the flags.
Flags are numbered, each representing different data issue, and these numbers are added to the flag columns when flagging the data. Zooming the chart also considers the selected height as well. You can use this advantage when selecting data range with low values which would otherwise appear close to zero in the chart.
Solar radiation data QC tool
You can open the solar radiation data check tool from the main menu via Quality/Solar radiation or by using the 
quick access icon located below the main menu. The window interface offers the following (after the check has been performed):
Run automatic checks: Execute the solar radiation data quality checks. The results will be displayed in the plot section and suspicious data flagged.
Visualization and summary tabs: Toggle between different visualizations to examine the flagged data or view the quality control summary.
Data visualization: Provides visual insights into where the data inconsistencies happen and what the detected issue was. The flags legend is located above the charts.
Test groups: These are used to group measurements from instruments in close proximity where values are expected to correlate. Test groups and how to work with them are described here.
Plot settings and parameter selector: Select which parameter to display for examination and set how to visualize the data.
Executing the solar radiation data quality check
When you open the solar radiation data QC tool, its interface may be empty, containing no visualizations. You must run the tests first to display the test results in the interface. To do this, click the “Run” button at the bottom-right of the window.
Important: This test will add new flag columns to the dataset for each solar parameter. These columns serve to add flags to particular values in the dataset.
Test groups
The solar radiation data QC works with test groups that help it to compare and evaluate related parameters for better accuracy. We recommend ensuring that the test groups are configured properly before proceeding to solar radiation checks.
Test groups are usually created automatically in the metadata editor, but you can edit and change them here in the solar radiation QC tool. You can learn how to work with the test groups here.
Examining the solar radiation data QC results
You can examine the results and view the flags added to the dataset once the system finishes the checks. There are several visualizations at hand to help you analyze the datasets and flagged data, and you can navigate them using the top navigation menu:
Heatmap flag plot: View the flags in a timeline chart. The correct data are displayed in green, night values (zero) are shown in grey, and the visualizations are separated by year.
Time series flag plot: Lets you view the flags in two charts: time series and the percentage of data points per month.
Consistency plots: Identifies consistency between different solar parameters. Available only if at least three solar radiation parameters are present in the dataset.
Quality control summary: Provides a summary of the checks performed in the dataset, separated by test groups.
Tip: Use the toolbar controls to work with the charts and examine the flags closely. You can learn how to work with them here.
Heatmap flag plot
The heatmap flag plot is the default tab you will see after the solar radiation QC finishes. It gives you a first look at the data and flags that have been automatically added to the identified values. It can help you quickly evaluate the data quality.
Heatmap: Shows the color-coded data and flags in a timeline. The Y axis represents 24-hour cycle, and X axis represents the timeline of the dataset. One heatmap contains one year of data by default. Green color represents correct values, grey night values, and various color points depict the flags in the timeline.
Identified flags: Flags that have been identified for the selected parameter, their respective color in the heatmap, and what they represent.
Parameter selector: Select the parameter you want to display in the heatmap flag plot.
Time series flag plot
The time series flag plot tab lets you examine the flags in two ways - in a time series chart, where you can zoom and see particular flags, and in a QC results monthly statistics chart, where you can visually compare amounts of different flags.
Flaged data: Color-coded flagged data.
Flags list: A color-coded list of flags that were identified in the dataset for the selected parameter. The same applies to the second chart.
Monthly statistics visualization: Each color represents a single flag. The amount of each flag is depicted in percent. This can help you quickly spot how much good data (green) is available for each month.
Parameter selector: Select the parameter you want to display in the charts.
Consistency plots
Consistency plots work only if there are at least three of the following parameters: GHI, DNI, DIF, and GTI. They are then compared and evaluated by calculations to determine the data accuracy. Each of the available parameters is displayed in a separate chart per testing group.
Consistency chart: Displays the data consistency for the given parameter. Color-coded points show passed vs values flagged with the consistency flag. Other flags are hidden in this case.
Test group selector: Select any test group to view the consistency charts for its parameters.
Quality control summary
The quality control summary tab provides a comprehensive breakdown of all solar radiation quality checks that have been carried out per test group.
Finishing solar radiation data check
Once you are done with the solar radiation data checks, use the “Save flags” button to apply the changes and add solar radiation QC status to the dataset.