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.

GPM SCADA

GPM SCADA has standard criteria for data consolidation and storage at different levels of granularity. The system's unmatched capacities also allow it to configure consolidations with greater levels of detail (granularity) and longer time periods for storage, depending on the needs and capacity of specific projects.
Note: For detailed information, click on each list item to see the corresponding section.

  • Consolidation: the aggregation of incoming data at regular intervals, for the purpose of processing, storage and analysis..

  • Storage: levels of consolidation for specific periods of time.

  • Granularity: the level of detail at which you analyze data, in relation to the scope of the time period you want to analyze.

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:

Consolidation

Data consolidation is the aggregation of incoming data at regular intervals, for the purpose of processing, storage and analysis. Consolidation involves collecting, integrating and harmonizing multiple variables . This allows users to work with meaningful metrics adapted to the context of each project.

Note: For more information about project-specific configurations, contact your GPM representative.

The standard level of consolidation for solar PV assets is five-minute intervals. Depending on specifications of your project, it may be necessary to configure higher levels of consolidation. GPM SCADA can consolidate real-time data from up to one million variables at one-minute intervals.

The standard level of consolidation for wind plants is ten-minute intervals. Depending on specifications of your project, it may be necessary to configure higher levels of consolidation.

Consolidation methods in GPM SCADA

GPM SCADA collects large amounts of data every second and aggregates the average measurements for all the granularity levels, as each variables may have its own level of granularity.

It also possible to have different consolidation intervals for the same variable within the same project (for example: 1-minute intervals for weather stations and 5-minute intervals for inverters).
Note: The consolidation process uses different aggregation methods, depending on your specific needs and configuration. For more information regarding aggregation methods, contact your GPM representative.
In GPM SCADA, dataloggers also create a back-up of aggregated data in the database, with one-minute data intervals. When the SCADA receives and validates the back-up data, the datalogger deletes them in order to make room for the next incoming values.
Note: The GPM SCADA database storage process uses a sharding approach, which partitions data by month and dataloggers. Partitioned data are stored in the GPM Server.
Information in GPM SCADA can come from different sources:
  • Reading real-time information every second from Dataloggers. Each datalogger has its own aggregation period.
  • Receiving binary frames from external processes.

Granularity

Granularity is the level of detail at which you analyze data, in relation to the scope of the time period you want to analyze.

The level of granularity depends on the types of data that you select for an analysis, the period of time that you want to cover, and the level of detail of the time intervals for the measurements. If you combine metrics that have different levels of granularity (for example, real-time actual power and five-minute energy output), the system aggregates the average values for each level).

There are two key factors to keep in mind when defining granularity settings to analyze data:

  • Performance: depending on the size, hardware, infrastructure and configuration of your project, processing large datasets with high levels of detail (graunarity) may affect speed and overall user experience.

  • Relevance: optimal granularity settings depend on the type of analysis you want to perform. For example, five-minute data may be relevant to assess the hourly performance ratio of a group of inverters in the same location, but it may not provide meaningful information regarding the yearly performance of an entire plant.

Storage

Renewable energy plants must store data at different levels of consolidation for specific periods of time. The specific configurations for storage depend on several factors affecting each project, including the quality and availability of servers, and contractual and regulatory obligations.

The minimum thresholds are defined by contractual and regulatory obligations for the purpose of accountability. These are usually standards defined by the industry and grid regulators.

Maximum thresholds depend on the capacities of each plant's hardware and communications infrastructure, relative to the size and scope of the project.

Standard: 1-second data stored for 3 days. 5-minute data stored for 3 years. (Dpending on servers)