Smarter management of turbine assets: How to get the most from your condition monitoring system

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1 Smarter management of turbine assets: How to get the most from your condition monitoring system Pressure is ratcheting up to asset managers to find to lower wind farm costs and increase efficiencies. Right now, the lowest hanging fruit in controlling costs is tackling operations and maintenance budgets. Even though acquisition, installation and commissioning of wind farms are the greatest contributors to the levelized cost of wind energy, the contribution from operations and maintenance (O&M) makes up between 15%-25% [1,2]. This is the only portion of the total cost that can be controlled once the wind farm is in operation. With a potential dearth of new installed capacity, this is the industry s sweet spot. This focus on O&M is a positive sign of a maturing industry. It has shined a spotlight on condition monitoring, the process of detecting faults in equipment before it fails. As with any new or cross-over technology, the connection between using that technology and ultimate cost savings is not always clear. Simply installing a condition monitoring system on a wind turbine will not save any money. It is a necessary technology, but not sufficient on its own. The only way to reduce costs is to use the condition monitoring information to make more efficient and effective maintenance decisions. What drives the O&M costs of a wind farm? The total maintenance costs (unscheduled and scheduled) for a typical wind farm are between 30% and 40% of the total operating expense. Successfully controlling these costs can make the difference between a profitable year and an unprofitable one. O&M activities matter because they affect not just costs, but also revenue. When a wind turbine is off-line for repair, it is not generating power. While the direct cost of an unscheduled maintenance call may be proportionally low, the maintenance event may have a significant impact on revenue if the turbine remains inoperable for two weeks or more. info@renewablenrgsystems.com 1

2 Operating cost data from a major US asset owner. Many wind farms are geographically isolated and present difficult working conditions for technicians. When one must ascend a tall tower with tools and work in a space-constrained nacelle, performing even basic maintenance isn t trivial. For example, a routine oil change is much more difficult when consumables and waste must be moved up- and down-tower. The unique characteristics of wind farm O&M makes the optimization of these activities critical to profitability. How can wind turbine O&M costs be reduced? The conversion of mechanical energy into electrical energy requires rotating machinery comprised of shafts, bearings, and gears the latter two requiring constant lubrication to avoid damage. The three basic maintenance strategies reactive, preventive, and predictive are best understood when compared to an everyday maintenance event familiar to most readers: changing the oil in their cars. In a reactive maintenance paradigm, equipment is run until it fails. This is similar to driving a vehicle off the sales lot and never changing the oil. Eventually, the car s engine will seize and render the vehicle useless. The downside of this maintenance strategy is obvious, but it doesn t mean many turbines have been, and continue to be, operated in just this manner. In a preventive maintenance (PM) paradigm, components are changed out on a time-based schedule, just as most drivers change the oil in their cars every 3000 miles. While this may seem like a good way to perform maintenance, it is inherently inefficient. PM reduces the amount of unplanned maintenance, but does this by increasing the amount of planned maintenance. PM can also waste a info@renewablenrgsystems.com 2

3 component that still has significant remaining useful life. Additionally, it can t detect early-life failures that are inevitable with some small fraction of components. The alternative to these two maintenance paradigms is predictive maintenance (PdM). The concept behind PdM is that maintenance should only be performed when a component is degrading, but before failure. Returning to the car example, there are many vehicles today that monitor the remaining useful life of the oil and tell the owner when to change it based on the measured condition of the oil. The PdM strategy maximizes the service life of each component, reducing the cost of premature replacement, while at the same time eliminating the collateral damage that can occur if a component is allowed to run until it fails. It reduces the amount of scheduled maintenance needed to ensure safe operation while also mitigating the risk of component failure. The PdM strategy has all the strengths of the reactive and preventive paradigms while eliminating many of their weaknesses. Where should I focus my condition monitoring efforts? Many in the O&M world are also familiar with Reliability- Centered Maintenance (RCM). RCM is not a maintenance methodology itself, but a framework for choosing which of the maintenance strategies (reactive, preventive and predictive) to apply to each component in the system. RCM seeks to balance the cost and effort needed to maintain each component with the environmental, health and safety (EH&S) concerns, and economic consequences of that component s failure. The use of predictive maintenance should focus on the subsystems that create significant downtime and add significant cost when they fail. The downtime caused by a subsystem failure on a wind turbine is not simply dictated by the amount of time it takes to perform the needed repair; it can be affected by parts availability and lead time, or the need for special equipment. For Aggregated downtime caused by per turbine subsystem failures from National Renewable Energy Laboratory [3]. info@renewablenrgsystems.com 3

4 example, it may take several days to replace a failed gearbox, but it may take a week to have one delivered and another week before a crane can be scheduled to install it. The figure shows aggregated downtime caused by turbine subsystem failures. The three subsystems that comprise the turbine drive train the gearbox, generator, and the main bearing account for more than half of the downtime experienced during the six year period. This makes them prime candidates for condition monitoring. In addition to the downtime, the cost of repairing these subsystems is substantial [4]. For a 1.5 MW turbine, the replacement/repair cost of the gearbox is approximately $152,000 and the generator is $53,000. For a 2.0 MW machine, those costs escalate to $216,000 for a gearbox and $77,000 for the generator. Additional labor and crane rental costs can add $50,000 to $250,000 to the total cost depending upon the site [5]. What types of condition monitoring technologies are available? It is important to note that no condition monitoring system (CMS) can avoid component failure once it has started. The rate at which a component fails is determined by the equipment installed, maintenance performed, and wind conditions to which the turbine is exposed. A condition monitoring system is valuable because it can be used to reduce the risk of collateral damage due to component failure and allow for optimization of O&M activities through early detection of faults. The value of early detection cannot be overstated. Many condition monitoring systems can detect faults before catastrophic failure, but the value of doing it several months before catastrophic failure is much greater than several days before failure. In line with the old adage an ounce of prevention beats a pound of cure, oil monitoring systems are used to measure whether the conditions are right for a fault to emerge. In a recent wind turbine service journal, the service provider estimated that over 70% of all turbine bearing faults are due to lubricant problems [6]. Unfortunately, oil monitoring systems are not a silver bullet it cannot detect other mechanical faults, such as gear, bearing, and shaft cracks. Hence, additional monitoring systems are needed to implement a predictive maintenance strategy. Vibration monitoring can be used to sense faults in gears, shafts and bearings once they have emerged. These monitoring systems are usually very sensitive to early stage faults and have been proven in other industries. The drawback of vibration monitoring systems is that modern wind turbines operate in widely varying conditions (e.g. speeds and torque) which makes the analysis of the vibration very difficult. Analysis requires a great deal of expertise and processing of the data to create actionable information for a site manager. info@renewablenrgsystems.com 4

5 Oil debris monitoring (not to be confused with oil monitoring) monitors debris particles in the lubrication system. This can be done either in-line, where the oil passes through the sensor on the way to the filter, or at the system sump, where debris particles tend to gather naturally. These systems typically use an inductive sensor to monitor ferrous (e.g. steel) particles in the oil. They are well-suited to tracking surface fatigue faults (e.g. bearing spalls) where significant material is lost during the failure, but they cannot isolate that failure to a single component. Nor can they sense faults that do not cause material loss, such as cracks. Oil debris monitoring systems are less expensive than a typical vibration monitoring system. No discuss of condition monitoring would be complete without mentioning the use of SCADA data to detect system faults. There are many cases where using SCADA is possible and even advisable for fault detection, such as with faults in the electrical system, or in a turbine control sensor, but SCADA does not work well for detecting and diagnosing gear, bearing or shaft faults because it allows just a few days time to react. The following figure depicts the importance of early fault detection and the relative value of each system previously discussed on a system where water has entered the oil supply. info@renewablenrgsystems.com 5

6 Conclusion: Evaluating the performance of a condition-monitoring system Unfortunately there is no yardstick to evaluate the performance of condition-monitoring systems. Germanischer Lloyd maintains a certification process for vibration-based and oil debris condition monitoring systems based on a specification, but does not address performance. In the end, success is measured by what you are trying to do with the system. The solution for someone trying to eliminate collateral damage will be very different than the solution for someone trying to optimize O&M costs over the long-term. For others, a combination of technologies provides the best solution. It all depends on what you aim to do with the information coming from your system. When evaluating a system, a buyer should consider three things: the timeliness, accuracy, and actionability of the information being produced: Timeliness: Understanding how early the system detects potential faults is key. Knowing about a failure months ahead of time allows you to plan your maintenance schedule in advance, while knowing just days in advance only allows you to react to an impending failure. Accuracy of the information is also essential. A false alarm or missed detection can erode user confidence and the overall value of the system. That is why it is imperative to understand how the CMS vendor manages uncertainty surrounding condition monitoring and how they set their alarm thresholds. Actionability: Are the services of a qualified engineer required to analyze the data and provide an interpretation to the user? Or does the system analyze the data itself and deliver indicators that the user can take action on with little or no training? CMS systems vary widely in terms of how they deliver data to the user. Condition monitoring systems can provide tremendous value for O&M providers by helping to reduce maintenance costs and optimize availability. To maximize the return on investment, it s important to focus resources on those components that pose the greatest risks to cost and profitability if and when they fail. References E-ON Climate and Renewables, March 2011; An overview of our business activities. Retrieved from: 3. Sheng, S. & Veers, P., Wind Turbine Drivetrain Condition Monitoring An Overview. NREL/CP Retrieved from: info@renewablenrgsystems.com 6

7 4. Poore, R. & Walford, C., Development of an Operations and Maintenance Cost Model to Identify Cost of Energy Savings for Low Wind Speed Turbines. NREL/SR Retrieved from: 5. Vachon, W. Crane Considerations Related to Maintaining Wind Turbines. Presented at 2006 Wind Turbine Reliability Workshop. Retrieved from: 6. ON Service Journal September 2011, Retrieved from: Infigen Energy provided valuable input in this paper. About the author: Brogan Morton is the Product Manager for TurbinePhD, a vibration-based predictive health monitoring system, at. Brogan started his career performing engineering research on the diagnostics and prognostics of mechanical components in aerospace systems. Morton holds a Master s degree in mechanical engineering from the University of New Hampshire and an MBA from Idaho State University. info@renewablenrgsystems.com 7