Features

Solargis Analyst offers data visualizations for multiple datasets/columns with various display options. These visualizations include time series representations of multiple parameters showing timeline graphs, heatmaps, histograms, and cumulative distribution function plots.

Analyst allows the analysis of specific aspects of solar resource data. Under this group of visualizations, users can generate Kt Graphs, yearly/monthly diurnal profiles, multiyear analysis plots, and trend graphs with linear, polynomial, or moving average trend lines.

Tools for visualizing and statistics of two datasets over concurrent periods are also provided within Analyst. This allows the representation of the differences found across datasets with a set of graphs like scatterplots, histograms, and cumulative distribution plots.

In Analyst, visualizations are accompanied by key numbers characterizing the results. At the level of single datasets, users can easily obtain min, max, mean values, percentiles, etc. For comparisons between datasets, Analyst calculates bias, RMSD, MAD, and correlation coefficients, among other statistics.

A time reference check tool is included in Analyst for the identification and correction of time shifts, time drifts, and other time-related issues based on testing diurnal symmetry, critical for all subsequent quality tests.  The user can manually identify the shifts and also run the auto-detection mode.

The module for irradiance quality check brings a set of tests commonly used by solar data experts. These include the detection of issues and flagging invalid values related to nighttime/daytime, artificial static values, breaking physical limits, and consistency of irradiance components. This module allows test groups of single and multi-component tests.

Automatic quality control of meteorological parameters allows the user to run the automatic tests applied to meteorological parameters as well. This includes the detection of invalid values, consecutive static values, and data below/above the physical minimum/maximum.

This tool enables to perform a manual quality assessment for the selected dataset by manually selecting data or by entering an expression for flags. Flagged data values can be explored in a plot, selected, and assigned to a new flag value.

In addition to quality control checks, Analyst provides a specific set of visualizations for the detection of other specific data problems, such as instrument shading.

Solargis Analyst can identify situations when sun-tracking instruments are not working properly. After the detection, the user can visualize and highlight periods affected by this issue.

After the data quality check, it is usual to have some valid flags left in the dataset. These individual flags often don't provide much value and they can be easily removed with the automatic post-filtering feature included in Analyst.

After a quality assessment is performed, the users of Solargis Analyst can generate a PDF report and XLSX tables with the results of the quality assessment. The report provides a summary of quality assessment results, and comparison statistics including the most representative graphs and tables, together with information about the measuring station, installed instruments, and measured parameters.

In Analyst, you can import datasets from delimited text files (e.g. CSV). Import instructions can be saved as a template for later use on similar files. To enrich information about measured data, logs about the maintenance of sensors can be imported into Analyst too.

Analyst provides a specific feature to make sure that time stamps will be correctly imported. In addition, shifting data capabilities are available to have datasets under control when working with several time zones.

Solargis Analyst has specific features for data editing and calculation. The dataset calculator includes tools for column creation, column deletion, and application of common functions to the data. It also includes a unit conversion feature, which can convert between different data parameter units.

Users of Analyst can aggregate multiple data records into one single record. Typical use cases of this feature can be the summarization of sub-hourly datasets into hourly, or the harmonization time steps across different datasets before comparing them.

Customizable aggregation rules and functions can be applied to each data parameter. These rules include basic summarization functions and more specific methods like weighted mean or angular aggregation.

Joining is used to add columns of values from one dataset to another dataset. It does the job for all matching records based on timestamps. On the other hand, combining is used for adding new records to an existing dataset. This for instance useful when new sensor readings are available and need to be added to the dataset. Overlapping records can be managed from the Analyst user interface.

Analyst offers the possibility to export the full set of datasets under a working project or a selection of parameters. The user can choose between several exporting formats. Besides the original Analyst Exchange File format, which provides the fastest way to transfer a single dataset between different Analyst users, other commonly used formats like CSV or PVSYST compatible files are available among the exporting options.

Under this group of features, users can find additional tools for linking, creating, deleting databases, physical removal of datasets from databases,  cloning datasets, and adding/removing datasets to a project.