Data

Renewable energy projects must capture, communicate and store very large amounts of data from different sources, which also undergoes several complex processes to produce useful metrics for asset managers and operators.

Renewable energy plants rely on Statuatory Control and Data Acquisition (SCADA) systems to capture and process the data for the purposes of asset management, operations and maintenance. The key indicators of the SCADA system's capacity to process and manage data are consolidation, storage and granularity. Each of these elements, and the relations between them, affect the overall usability of data for monitoring systems, production analysis, accountability, and compliance with contractual and regulatory obligations.

Monitoring systems provide an additional layer of complexity, to convey meaningful metrics and relevant KPIs to inform real-time monitoring, decision-making and analysis.
Note: For more information about GPM products process and calculate data to produce each metric, see the KPIs section.

SCADA systems

The infrastructure and protocols of the SCADA system must guarantee the availability, integrity, accuracy, and reliability of every variable, and the processed metrics and KPIs that monitoring systems produce.

GreenPowerMonitor's GPM SCADA is the leading digital solution for solar asset management. A testimony to the system's outstanding reliability, speed and overall user experience (UX) is the record-setting capacity to handle over one million variables in real-time.

Data processing: parameters and variables

In the context of GreenPowerMonitor products and projects, the two main types of data:

  • Parameters: fixed values for specific projects, plants and devices.

    For example:

    • Geolocation

    • Altitude

    • Theoretical AC power.

    • Minimum and maximum production thresholds.

  • Variables: measurements of actual production and of the external conditions and factors that affect it.

    • Raw data: measured by plant devices and communicated to the system for further processing:

      For example:

    • Processed data: values calculated by the system to produce relevant metrics and KPIs based on specific project configurations.

      For example: