Plant Diagnostic Services

Plant Diagnostic Services

Wind and solar plants generate massive amounts of data, which if utilized properly can provide significant insight for potential improvement of operational performance. Plant operators benefit from advanced metric and performance monitoring to identify unexpected developments and behaviors in the wind farm. UL provides this periodic performance reporting from an independent perspective.

Plant Diagnostic and Optimization Report (PDOR)

The main drivers for underperformance issues occurring at a wind or solar project can be detected with the analysis of the SCADA data. The PDOR includes an in-depth analysis and comprehensive visualization of key sensor measurements and operating parameters reported in the SCADA data. To identify issues in asset performance or reliability, comparative analysis of individual asset operation and performance within a plant or against expectations are evaluated using anomaly detection, outlier detection and trend analysis. By identifying such developments in early stages, it is possible to apply low cost corrective actions that significantly reduce maintenance costs and turbine downtime. The PDOR also includes a comprehensive overview, summarizing the findings and specific recommendations for each of the problems detected in order to address them. Typical SCADA signals which are evaluated can include:

  • Electrical (voltages, currents, active and reactive power)
  • Mechanical (nacelle position, yaw error, blade pitch
    angle, generator and rotor speed)
  • Thermal (gearbox, bearings, oil, generator or ambient)
  • Performance (Tip-speed-ratio, Coefficient of power,

Monthly Performance Reports (MPRs)

MPRs target the delivery of independent information about the performance of the wind farm and the development of key performance indicators (KPIs) throughout the life of the wind farm or solar plant. The reports deliver insights on production and availability of the wind farm and reasons for loss of power generation, and identify wind turbines with abnormal behavior. MPRs are independent from analyses provided by turbine manufacturers and operators, thereby giving owners and investors reliable third-party advice for the assessment of the investment and a solid basis for decision making. The report contains as a standard:

  • Power generation & comparison to expected
  • Availability assessment (energy- and time-based)
  • Detailed assessment of downtime and lost energy
  • Wind resource based on the nacelle anemometer
  • Identification of outliers in behavior of performance as
  • Performance KPIs by turbine
  • Correlation between wind turbine production and its development along the operation of the wind farm.

MPR’s are based on the 10-minute (or higher resolution) SCADA data and alarm logs of all turbines. The report can be extended and customized by inclusion of further data sources such as met masts, revenue meters, service records, work orders, and balance of plant (BOP) registers according to the specific needs of each customer.


Plant-Level Monthly Wind Speed and Anomaly Time Series

Knowing the performance of the wind can help you understand the performance of your wind farm. To understand the wind at specific sites we offer plant-level, historical, monthly-average wind resource information derived from maps and global reanalysis data, on a onetime or subscription basis, updated within 7 days of the end of each month. These custom datasets are based on a combination of three reanalysis data sources: ERA Interim, MERRA, and CFSR, which allows for rapid, reliable updates of wind conditions around the globe. Anomalies are defined as the percent deviation in speed relative to the historical average speed for the given calendar month, quarter, or year.

Wind Anomaly Map of Project Sites

This product can be used in a number of applications, including:

  • A reference for Measure-Correlate-Predict for
    operating wind plants, to extrapolate short-term
    performance to long-term conditions.
  • Tracking performance of wind plants against
    expectations and identifying deviations against preconstruction
  • Assessing portfolio diversity benefits for multiple
    wind projects in different regions.
  • Studies of wind climate trends and variability