Skip to main content

Annual Photovoltaic Performance Analysis Dataset

Purpose of the Dataset

This dataset aims to detail the hourly annual energy production of five photovoltaic self-consumption plants. It acts as a structured information source to facilitate technical monitoring, the analysis of real versus theoretical performance, and the optimization of maintenance and operation strategies based on historical operational data.

Scope and Technical Considerations

The dataset provides a granular and technical view of the energy assets' behavior under the following criteria:

  • Temporal resolution: Hourly granularity (ISO 8601 format).
  • Scope: Five monitored self-consumption plants.
  • Update frequency: Monthly.
  • Data origin: Technical telemetry from photovoltaic inverters and monitoring devices (loggers).

Type of Dataset

  • Private dataset: Integrated into the EMPOWER-X sectoral data space (Gaia-X Lighthouse Project).
  • Accessibility: Available to authorized users via direct download through the Marketplace.

Content of the Dataset

The dataset includes generation and performance metrics associated with specific self-consumption assets.

Asset identification:

  • Technical identifiers: Alphanumeric codes are used for the managing entity (company) and the monitoring equipment (deviceName).
  • Privacy by design: Personal data, sensitive commercial information, and direct physical locations are not included, ensuring end-customer anonymity.

Format of the Dataset

Data is structured in an optimized and interoperable JSON format, following a public ontology defined using JSON-Schema.

Dataset Structure (Conceptual Example):

FieldDescriptionExample
companyTechnical identifier of the managing entity (anonymized)."E00001"
deviceNameUnique identifier of the monitoring equipment."Logger-10235593..."
startTimeStart timestamp of the reading (ISO 8601)."2025-01-02 15:00:00"
totalPvPerformanceKWhValue of total accumulated photovoltaic performance in kWh.2179.71
pvGenerationDataValue of hourly photovoltaic generation in kWh.11.99

Relationship with Algorithms

This data product is designed to power advanced digital services within the energy ecosystem, such as:

  • Optimization for Energy Communities: Load balancing and strategic decision-making based on real generation.
  • Predictive Maintenance and Benchmarking: Early detection of anomalies and validation of photovoltaic prediction models.
  • Demand Management (Smart Grids): Creation of algorithms for the optimization of distributed energy assets.

Data Security and Governance

  • Secure infrastructure: Deployed on a microservices architecture (Docker) with encrypted communications via SSL/HTTPS.
  • Access control: Implementation of policies based on Verifiable Credentials (VC) and Web3 wallets, aligned with the Gaia-X trust framework.
  • Regulatory Compliance: Aligned with GDPR and LOPDGDD, as well as the UNE 0087:2025 standard for data spaces.

Summary

This dataset constitutes a Data as a Service (DaaS) that positions Naturelek Consulting SLL as a trusted data provider within the European market. It offers standardized and highly reliable solar generation metrics, facilitating the energy transition through the secure sharing of operational data from renewable plants.


View Dataset