Turbine Prognosis reference
Reference information for Turbine Prognosis charts, data quality parameters, and performance expectations.
Available charts
The following table lists all charts available in Turbine Prognosis with their parameters and use cases.
| Chart | Parameters | Use case |
|---|---|---|
| Power curve | Wind Speed vs Active Power | Validate turbine power output against wind speed |
| Nacelle Deviation vs Active Power | Nacelle Deviation vs Active Power | Analyze yaw behavior impact on power generation |
| Nacelle Deviation vs Rotor RPM | Nacelle Deviation vs Rotor RPM | Detect yaw misalignment effects on rotor speed |
| Nacelle Deviation vs Frequency | Nacelle Deviation vs Frequency | Identify yaw deviation patterns and frequency distribution |
| Nacelle Deviation vs Generator RPM | Nacelle Deviation vs Generator RPM | Analyze yaw impact on generator speed |
| Rotor RPM vs Active Power | Rotor RPM vs Active Power | Validate rotor speed relationship to power output |
| Rotor RPM vs Generator RPM | Rotor RPM vs Generator RPM | Verify gearbox ratio and mechanical coupling |
| Wind Speed vs Rotor RPM | Wind Speed vs Rotor RPM | Analyze rotor speed response to wind conditions |
| Generator RPM vs Active Power | Generator RPM vs Active Power | Validate generator speed and power relationship |
| Pitch Angle vs Wind Speed | Pitch Angle vs Wind Speed | Verify pitch control response to wind speed |
| Pitch Angle vs Active Power | Pitch Angle vs Active Power | Analyze pitch regulation impact on power output |
| Wind Speed vs Turbulence | Wind Speed vs Turbulence | Assess turbulence intensity across wind speeds |
| Temperature vs Active Power | Temperature vs Active Power | Monitor thermal behavior during power generation |
| Rotor Speed vs Pitch Angle | Rotor Speed vs Pitch Angle | Validate pitch regulation and rotor aerodynamics |
| Rotor Speed vs Wind Speed | Rotor Speed vs Wind Speed | Analyze rotor aerodynamic performance |
| Component temperatures | Generator, Gearbox, Transformer, Converter temperatures | Monitor component thermal stresses and derating behavior |
Data quality parameters
The data quality layer automatically removes absurd values and extreme outliers to ensure reliable analysis. The following table lists parameter bounds and outlier removal rules using the interquartile range (IQR) method.
| Parameter | Hard bounds (absurd values dropped) | Outlier rule |
|---|---|---|
| Wind Speed (m/s) | Greater than or equal to cut-in wind speed and less than or equal to cut-out wind speed (from power curve) | IQR: Drop values outside [Q1 - 1.5 × IQR, Q3 + 1.5 × IQR] within selected wind speed range |
| Active Power (kW) | Greater than 0 and up to 1.20 × Rated Power | IQR per wind bin or global |
| Rotor RPM | Greater than 0 and up to 1.20 × Rated Rotor RPM | IQR or z-score |
| Generator RPM | Greater than 0 and up to 1.20 × Rated Generator RPM | IQR or z-score |
| Pitch Angle (°) | -5 to 90 | IQR |
| Nacelle Deviation (°) | -180 to +180 | IQR |
| Turbulence (%) | 0 to 100 | IQR |
| Wind Speed Standard Deviation | Less than 2 | Not finalized |
| Turbine Status | = Performance | N/A |
The system applies data quality rules in the following order:
- Apply global wind speed filter to raw data (if specified)
- Drop absurd values using hard bounds
- Remove outliers using IQR method (per-chart on Y variable; optionally per X-bin). Use z-score only when bin counts are small (N less than 20)
- Perform binning (equal-width on X; default 20 bins; minimum 5 samples per bin)
- Calculate average line as mean(Y) per bin (fallback to median if skewness greater than 1)
Charts display dropped counts by rule (hard bound versus outlier) for each turbine in a tooltip.