Operations & maintenance 62%
Wind industry stakeholders consider data integration to be a significant barrier to digital advancement. ONYX InSight
digitalisation is only growing. “Wind turbines are no longer operating under a subsidy regime where you have fixed revenues linked to each megawatt hour that’s produced,” says Jonas Corné, CEO at Greenbyte, another leading predictive analytics company for the wind industry. The environment that the industry currently finds itself in contains a lot more volatility with regards to electricity pricing, which in turn creates more complexity around optimising the assets involved.
Hall likens the concept of maintenance strategies to that of a car. You operate it for a given period of time and then you bring in time-based preventative maintenance, which in the car’s case is regularly scheduled check-ups with a mechanic – rather than the alternative, which is to wait until your car breaks down. The only issue, for both cars and for wind turbines, is that the asset is out of operation during that preventative maintenance. For energy generation, it could also involve replacing parts that don’t need replacing, just to fit in with a certain timetable. That’s the advantage of digitalisation – using data that allows you to know exactly when to implement predictive maintenance, rather than relying on an estimation. For the wind industry, the benefits are clear for following the most advanced predictive maintenance principles. Wind turbines can be outfitted with a wide variety of sensors that can take data from various components within the turbine. Companies like ONYX InSight and Greenbyte then analyse that data and use their findings to empower customers to make smarter decisions when managing their assets. Hall lists two main advantages in this area – the first is that, by predicting a failure months ahead of time, you can plan your maintenance more effectively and reduced costs – for example, by pre-buying replacement parts at the best rate or by pre-booking cranes or vessels required for maintenance interventions. This enables operators to ensure that an asset does not go out of operation during a time when it can’t be easily replaced. This offers obvious benefits to offshore wind, which can be challenging to reach quickly in times of emergency.
The second advantage is that is enables operators to save money by minimising lost production. If an asset is taken out of production, it can’t generate electricity. Naturally, it would be preferable to avoid any breakdowns during a region’s windy season and to catch any failures before they happen during the low-wind season, when most maintenance work is done, such as gearbox replacement or assessing blade condition and pitching. Similarly, avoiding unnecessary site visits brings with it financial savings of its own, reducing labour hours, vessel hiring costs and further reducing the time assets spend out of production.
12 Get a sense of things
What kind of data is used to make these decisions, then? Well, modern turbines are built with a wide variety of sensors installed, and one of the key types involved tracks vibration data. Each turbine will have a range of sensors measuring the level of vibration of the major components within it, which is then used to judge their respective health and what actions should be taken to address any underperforming parts. For example, if sensors show high vibration levels in the turbine shaft, it could indicate that the shaft has run too far out of place and needs to be realigned. “If you notice that you have a gearbox that’s not working very well, perhaps it makes sense to actually derate the turbine to run it at a lower capacity,” notes Corné. Operators can then send a maintenance team to replace the low-functioning part in question before it breaks down and potentially compromises other parts of the turbine. “When something breaks down, it can also cause a bunch of secondary failures – other components that are nearby. You really want to avoid that.”
Even something as simple as weather forecasting can provide invaluable data to operators. “In wind, it’s very important to have data on what the future is going to look like for the next couple of days,” says Corné. “When you do maintenance on a wind farm, you want to make sure that you do it on days when it’s not windy and you don’t have a bunch of waves, so you can actually get the vessels out to the wind farm.” After all, hiring vessels to transport maintenance crew to offshore wind sites can easily cost tens of thousands of dollars per year, not to mention the time that is put into organising such work.
Barriers to overcome
While digitalisation offers many advantages, it also faces challenges of its own. It’s one thing to collect the data at a turbine, but in order to optimise its performance, operators need to be willing to gather the different data streams in one central location so that conclusions can be drawn from the complete data set. “That is not something that I have seen companies doing very well,” Corné acknowledges. “It’s often the case that data is siloed, it’s not accessible, and therefore you cannot draw conclusions.” Siloed data is the biggest obstacle to operational efficiency in the wind industry, according to an ONYX Insight industry survey from September 2021 – with 62% of wind industry stakeholders considering data integration to be a significant barrier to digital advancement. Data silos mean lost value – removing them, Corné believes, would be “a game changer” for the industry.
“If that does not happen, the rest of the digitalisation work will be impossible,” he warns. “Because the data is the underlying factor upon which all of the other digitalisation elements will have to build upon.”
World Wind Technology /
www.worldwind-technology.com
Ian Dyball/
Shutterstock.com
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