The debate around the limitations of full-service agreements (FSAs) with turbine manufacturers, commonly referred to as OEMs (original equipment manufacturers), has been gaining momentum in the wind energy sector. FSAs provide the comfort of availability guarantees, but the structure of these guarantees often leads to unintended outcomes: minimal action so long as turbines remain operational, even when underlying issues may be silently eroding performance.
A recent case we encountered with a client illustrates this vulnerability. A wind asset owner was informed that several turbines had stopped due to high wind alarms—a protective measure by design, as operating under high wind speeds can place excessive stress on turbine components. The downtime, categorized as an “environmental factor,” was excluded from the availability guarantee, a standard industry practice under many FSAs. Everything seemed in order until Kavaken’s Outages module flagged an unusual pattern that had slipped through the cracks: these high wind alarms were malfunctioning, shutting down turbines at wind speeds between 12-16 m/s, well below the typical threshold of 22-25 m/s (see power curve below—purple dots represent the false high wind alarms that mostly appear within the 12-16 m/s wind speed range).
Without this insight, the asset owner would have unknowingly accepted these shutdowns as natural occurrences outside the OEM’s control. In reality, favorable wind conditions were being prematurely cut short by faulty alarms, likely due to an operational error, such as an incorrect parameter setting—an issue that would indeed fall under the manufacturer’s responsibility. This malfunction led to 0.2% of lost production and revenue—losses for which the OEM bore no liability under the terms of the agreement.
This case underscores a larger issue with the availability-only approach commonly found in FSAs. By focusing solely on availability guarantees, asset owners can be left exposed to risks that go undetected. After all, it is production—not mere availability—that drives revenue, an important distinction that availability guarantees alone fail to cover. Yet the data generated by turbines holds the answers, continually signaling operational anomalies and performance patterns that only come to light when properly analyzed.
With ongoing and attentive examination of this data, uncovering issues like these becomes straightforward. This approach empowers asset owners to go beyond meeting availability targets, ensuring that the turbines they invested in are producing at optimal levels.
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