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Real-Time Performance Analytics Console for European Solar Assets 

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Project Summary

A European developer and owner of solar projects required a robust performance analytics platform to monitor, validate, and compare real-time plant generation data against forecasted and satellite-derived benchmarks. The goal was to streamline operational reporting, verify generation anomalies, and support data-driven asset management. 

Challenge

Solar plants often underperform due to weather variability, equipment malfunction, or data inconsistencies. The client needed a lightweight but technically robust tool that: 

  • Cross-validates generation data using satellite and ground-station irradiance 
  • Detects anomalies against expected energy yields 
  • Produces actionable daily and monthly performance summaries 
  • Consolidates data integrity, assumptions, and forecast comparisons in a single console 

Solution

We developed a custom Performance Analytics Console, leveraging dynamic and structured dashboards to provide: 

Automated Data Validation:
  • Hourly data checks from SCADA, satellite (East and West), and ground stations 
  • Highlighting of data gaps or inconsistencies 
Performance Indexing:
  • Generation deviation calculations vs. forecasted and modeled expectations 
  • Daily and monthly summaries of over- and under-performance 
Dynamic Reporting:
  • Generation data visualized against irradiance (GHI and GTI) 
  • Console interface with input fields for a wide range of inputs 
Forecast Benchmarking:
  • Integration of PVsyst simulation outputs for baseline energy expectation 
  • Adjustable assumptions for near-term diagnostics 

Key Results

Fully automated with time-step reporting

Satellite vs. on-site data triangulation

Custom input for degradation, tilt effects, and plant-specific variables

Modular tabs for expected generation, integrity review, and raw data logs

Impact

The client now benefits from: 

  • Enhanced visibility into daily and monthly performance 
  • Proactive detection of deviations from expected generation 
  • Evidence-backed diagnostics to support maintenance and O&M decisions 
  • Reduced downtime and improved forecasting reliability 

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