Turbine Prognosis

Multi-turbine comparison enables performance engineers and wind analysts to compare up to four turbines simultaneously, helping identify performance deviations, best versus worst performers, and operational patterns.

Overview

The enhanced Turbine Prognosis page supports comparative diagnostics across multiple turbines. You can analyze performance patterns, detect relative anomalies, and investigate behavior within specific wind speed ranges that are not visible when viewing a single turbine.

Key capabilities

Multi-turbine comparison provides the following capabilities:

  • Multi-turbine selection: Select up to four turbines simultaneously with distinct color coding for each turbine across all charts.
  • Wind speed filtering: Apply a global wind speed range filter that restricts all charts to a chosen wind speed band, enabling investigation of performance anomalies tied to partial-load or rated-load conditions.
  • Bin-wise average trendlines: View average lines overlaid on scatter plots for each selected turbine, reducing noise and making it easier to detect deviations from expected operational profiles.
  • Data quality layer: Automatic removal of absurd values and extreme outliers that use parameter bounds and IQR (Interquartile Range) method, help ensure cleaner and more reliable analysis.
  • Enhanced visualizations: Access new charts for rotor behavior (Rotor Speed vs Pitch Angle, Rotor Speed vs Wind Speed) and component temperatures (generator, gearbox, transformer, converter).

Benefits

Multi-turbine comparison delivers the following benefits:

  • Faster identification of best-performing versus worst-performing turbines
  • Reduced manual effort in exporting and comparing data across turbines
  • Improved diagnostic accuracy through pattern deviation detection
  • Clearer insights with noise-free trendlines and cleaned datasets
  • Deeper visibility into pitch regulation, rotor aerodynamics, and thermal behavior

Use cases

Performance engineers and wind analysts use multi-turbine comparison for the following scenarios:

  • Comparing power curve behavior between turbines to identify underperformers
  • Analyzing rotor rpm and pitch angle patterns within specific wind speed ranges
  • Detecting yaw deviation anomalies across multiple turbines
  • Validating pitch regulation and rotor aerodynamics under controlled wind conditions
  • Monitoring component temperatures to spot thermal stresses and derating behavior
  • Investigating turbulence impact on turbine performance