Your Wind Turbine Is Running. But Is It Performing?

For wind plant owners and operators, availability is one of the most closely watched performance indicators. It answers an essential question: Was the turbine capable of operating when it was expected to operate?

But availability does not answer an equally important question:

When the turbine was operating, was it producing as much energy as it should have?

A turbine can be online, free of major alarms, and technically "available" while quietly losing its potential yield every single day. These hidden performance losses could persist for months or years without triggering an urgent SCADA alarm.

To protect asset value and maximize ROI, wind performance must be evaluated through two distinct lenses: availability and energy performance.

Availability Is Essential—but It Is Not the Complete Picture

Availability measures time and capacity readiness. Depending on your operations agreement, it accounts for downtime due to maintenance, faults, grid curtailment, and other excluded conditions. This makes availability valuable for managing maintenance performance, warranty obligations and operational uptime.

However, relying solely on availability to judge asset health is like evaluating a factory based on whether the lights are on. It doesn't tell you how fast the assembly line is moving.

The turbine is running—but it is not necessarily performing.

Small Losses Become Significant Over Time

A brief period of underperformance may not appear financially significant. The commercial impact emerges when the behavior is repeated across thousands of operating hours or multiple turbines.

Consider a turbine that consistently operates below its expected potential under a particular combination of wind speed, direction and operating mode. If the behavior affects only certain conditions, it may be diluted when performance is summarized using monthly production figures.

If the same condition affects several turbines, however, the accumulated loss can become material at the plant level.

The result is often a persistent gap between actual production and achievable production—without a corresponding reduction in reported turbine availability.

Performance Problems Do Not Always Trigger Alarms

Modern wind turbines generate large quantities of SCADA and event data. These systems are effective at identifying many faults and conditions that require operator attention. But alarms are primarily designed to protect equipment and report defined operating conditions. They do not identify every instance of lost energy.

A turbine controller may be operating exactly as configured, even when a parameter, sensor offset or control response is causing avoidable underperformance. In other situations, an event log may show that a change occurred but may not contain enough information to determine whether the turbine responded correctly.

This creates a critical distinction:

The absence of an alarm does not prove the absence of a performance problem.

Identifying these problems requires examining how power, pitch, rotor speed, yaw position, operating mode and other signals behave together under changing conditions.

Look Beyond the Average Power Curve

Power curves are an important part of wind plant performance analysis. They can show whether a turbine’s production differs from a reference curve or from comparable turbines. But a conventional power curve is still a summary. It can indicate that a difference exists without explaining why it exists.

For example, two turbines may show similar average power-curve deviations while experiencing entirely different underlying problems. One may have a yaw-alignment issue. Another may be responding incorrectly during a power-mode transition. A third may be affected by wake conditions or a sensor offset.

The operational response will be different in each case.

To move from detecting underperformance to correcting it, owners need to connect the observed energy loss to the turbine behavior causing it.

Compare Turbines Under Comparable Conditions

One of the most useful advantages of plant-level analysis is the ability to compare similar turbines operating under similar environmental conditions.

These comparisons can help identify:

• A turbine that consistently produces less than its peers

• Differences in pitch or rotor-speed response

• Direction-dependent performance losses

• Changes following maintenance or controller updates

• Recurring issues that affect an entire turbine model

• Plant-level behavior that cannot be explained by a single turbine

Comparisons must be made carefully. Turbines experience different terrain, wakes, availability conditions and environmental inputs. A meaningful analysis accounts for those differences rather than assuming every turbine should behave identically.

The objective is not simply to rank turbines. It is to identify repeatable evidence that points toward a correctable cause.

Close the Loop From Detection to Verification

Finding underperformance is only the beginning. A useful performance-improvement program should follow a closed-loop process:

1. Detect: Identify abnormal behavior using SCADA analytics, turbine-to-turbine comparisons and operating-state analysis.

2. Diagnose: Determine whether the deviation is associated with yaw, pitch, power control, sensors, derating, wake effects or another operating condition.

3. Prioritize: Estimate the frequency, energy impact, corrective effort and operational risk associated with the issue.

4. Correct: Work with the owner, operator or OEM to implement the appropriate controller, sensor, maintenance or operating change.

5. Verify: Measure performance after the correction using a defined methodology, suitable reference turbines and comparable operating conditions.

This final step is critical. A closed work order does not necessarily mean that the expected performance improvement was achieved.

From Operational Availability to Asset Value

Availability remains a fundamental wind industry metric. But managing availability alone can create an incomplete view of asset performance.

Owners need visibility into both sides of the equation:

• Is the equipment able to operate?

• Is it converting the available wind into energy effectively?

PulseSense Dynamics helps wind plant owners analyze high-resolution operational data, identify the causes of underperformance and verify the results of corrective actions.

Because a turbine that is running is not necessarily a turbine that is performing—and closing that gap can improve both annual energy production and long-term asset value.

Ready to see what your 10-minute SCADA data is missing? Explore Wind PulseSense or reach out to our team to start uncovering hidden yield on your site today.