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Reducing yaw system downtime
Reducing yaw system downtime
by RES | Feb 05, 2023 | Lesezeit: 2 min
As part of the asset management service we deliver to a wind farm in Scotland for one of our clients, our analysis and optimisation team collect SCADA data produced by the turbines and substation.
Using our custom-built technology agnostic software we carry out performance analysis on this data to provide meaningful insights into asset performance. For instance, we can identify the cause of lost production and expected yield.
The work
Our analysis highlighted that there was an unusually high yaw system downtime on this site. We quickly investigated and found that following a software update by the OEM an alarm wasn’t automatically restarting the turbines as it should following a period of low wind. This meant that the turbines had been down for longer than necessary, losing valuable revenue for our client. As we manage a large portfolio for various clients, we checked the other sites that we manage and identified that this site wasn’t unusual and that other wind farms were suffering from the same issue.
Following our investigation into the cause of the downtime, RES asked the OEM to provide a patch to the existing software to fix the incorrect parameter setting. Once the software update was completed by the OEM, RES performed checks to ensure that the downtime was as expected, and the issue had been resolved.
We also rolled out the fix to our entire portfolio of wind assets that we manage, ensuring that our other clients benefit from our experiences. Once the issue had been correctly resolved, we updated our analysis tools to ensure that any similar behaviour was automatically identified to us in order to minimise the time to resolve the issue and prevent significant lost production on any asset that we manage.
Results
Our analysis and optimisation service provides useful insights into performance, that may otherwise go unnoticed. This helps our clients to increase revenue and maximise asset performance. On this occasion we saved our client over £160K.
