How to model O&M costs and evaluate the cost impact of serial failures

Wind farm O&M cost is primarily made up of scheduled (planned) and unscheduled (unplanned) maintenance. The main source of uncertainty is unscheduled maintenance, and the biggest driver behind this is what we call technology risk. This can stem from a new turbine type that is relatively unproven, an existing turbine type running a new gearbox variant, blades from a new supplier or a new control algorithm that has been rolled out by the OEM.

The accuracy of an O&M cost forecast is critical to meeting the long term financial goals for a project. Romax InSight’s approach is to combine site-specific information from the wind farm, plus turbine-specific and technology-specific information from a vast historical database of past information.

Romax InSight’s approach to data for O&M cost forecasting

A serial defect, out of warranty, can be the worst nightmare for a wind farm owner – leading to lower than expected availability and significantly higher O&M costs. The cost of major component replacements can greatly reduce the project net revenues to a point where the debt may not be fully covered.   

Take for example pitch bearing failures, currently a widespread issue for the industry. A wind turbine has three pitch bearings supporting the blades. The image below shows a pitch bearing that failed prematurely due to excessive flexibility of the raceway, resulting in edge-loading on the bearing and a phenomenon known as ellipse truncation. This was confirmed using a RomaxWIND simulation including the deformation of the hub and pitch bearing, also shown below. The cost impact of a pitch bearing failure is huge – the repair requires a large crane operation, extensive downtime and three expensive replacement bearings.

An example pitch bearing failure – a failure mode with extremely high cost implications.

Download the Technical White Paper on forecasting O&M costs...

The Romax InSight team will be hosting a webinar on this topic. If you want to learn more about the methods we use for O&M cost prediction, along with some fascinating real-world examples then click below to sign up.

 


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