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Data-Driven Assessment of Wind Turbine Performance Decline with Age and Interpretation Based on Comparative Test Case
Davide Astolfi1, Ravi Pandit2, Ludovica Celesti1
1Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, Italy.
Sensors (Basel, Switzerland)
|May 20, 2022
Summary
Wind turbine performance decline with age was studied using SCADA data from Senvion MM92 and Vestas V52 models. Vestas turbines showed significant performance drops potentially due to hydraulic blade pitch issues, unlike Senvion turbines.
Area of Science:
- Renewable Energy Engineering
- Wind Turbine Technology
- Performance Monitoring
Background:
- Wind turbines are aging, necessitating analysis of long-term performance trends.
- Operational data from aging wind farms is crucial for understanding degradation.
- Two Italian wind farms with Senvion MM92 and Vestas V52 turbines were selected for analysis.
Purpose of the Study:
- To evaluate and interpret wind turbine performance decline with age.
- To compare aging trends between different wind turbine models.
- To identify potential causes of performance degradation in aging wind turbines.
Main Methods:
- Analysis of Supervisory Control and Data Acquisition (SCADA) data spanning 7-10 years.
- Development of data-driven models to construct wind turbine operation curves.
- Comparative analysis of performance trends across different turbine models and individual units.
Main Results:
- Senvion MM92 turbines showed negligible performance aging, with year-to-year variations below practical significance.
- Vestas V52 turbines exhibited significant performance variability, with two units showing notable drops and subsequent underperformance.
- Hydraulic blade pitch behavior is hypothesized as the cause for the Vestas V52 performance decline, while gearbox aging was found to be negligible.
Conclusions:
- Wind turbine aging impacts vary significantly by model and component.
- Hydraulic blade pitch systems may be a critical factor in Vestas V52 performance degradation.
- Long-term SCADA data analysis is effective for diagnosing wind turbine health and performance issues.
Keywords:
SCADAdata analysisperformance analysisrenewable energytechnical systems agingwind energywind turbinesMore Related Videos
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