Published

2 years ago

May 29, 2024

Alice Rush

Weather Guard Lightning Tech

IntelStor Insights into Wind Turbine Blade O&M Costs

Phil Totaro, CEO of IntelStor, dives deep into the latest trends and data surrounding onshore wind turbine blade operations and maintenance costs. He discusses the strategies and innovations being employed to optimize blade performance, reduce downtime, and drive down costs.

Sign up now for Uptime Tech News, our weekly email update on all things wind technology. This episode is sponsored by Weather Guard Lightning Tech. Learn more about Weather Guard’s StrikeTape Wind Turbine LPS retrofit. Follow the show on Facebook, YouTube, Twitter, Linkedin and visit Weather Guard on the web. And subscribe to Rosemary Barnes’ YouTube channel here. Have a question we can answer on the show? Email us!

Pardalote Consulting – https://www.pardaloteconsulting.com
Weather Guard Lightning Tech – www.weatherguardwind.com
Intelstor – https://www.intelstor.com

Allen Hall: Welcome to the Uptime Wind Energy Podcast. I’m your host, Allen Hall. As the wind energy industry continues to grow and mature, the focus on reducing costs and improving efficiency has never Been more important. Operations and maintenance costs can account for a significant portion of the total cost of energy production, making it a critical area of concern for wind farm operators and energy users alike.

In this episode, Phil Totaro, CEO and founder of IntelStor, will share the latest data and trends related to Onshore Wind Turbine Blade Operations and maintenance costs, which everybody’s wondering about is going to provide some valuable insights into the current state of the blade industry and how we manage blades.

You also discussed some of the strategies, innovations being employed to optimize blade performance, reduce downtime, and ultimately. Drive down costs, so whether you’re a wind farm operator, an energy user, or just simply interested in the future of renewable energy, this is an episode you won’t want to miss.

Welcome again. Thanks, Allen. Thanks for having me. So the IntelStor report you just published, and there’s some news about it on LinkedIn, is really fascinating because Joel and I have been wandering around Oklahoma and Texas and other parts of the country looking at blades. And there is a lot of concern.

About the costs associated with damaged blades and how to forecast that and how to appropriately budget for them, particularly in terms of all the new types of blades that are being introduced, the bigger generators, the three megawatts, the four megawatts, the six megawatt machines versus the one and a half and two megawatts that we’re kind of used to it becomes really a guessing game for a lot of operators because they don’t have a sense of How much is it going to cost me to operate this turbine, and how do I manage that, and how do I appropriately schedule my technicians?

Like, how many technicians do I need for a season? These are subjects that come up all the time, and, and if you’ve been around anywhere in Canada or the United States over the last year, there’s so much more talk about it now. And this is where your new tool comes in, your Onshore tool. Basically estimator or looking at turbine size versus the types of damage a blade may suffer.

Phil, will you, will you walk us through what this tool is at the top

Philip Totaro: level? Sure. Of course. So, What we have been repeatedly getting asked about is, for the ISPs we work with, they want to understand the, a detailed market forecast. And the only way to get to a detailed market forecast is, we obviously know based on the work that we already do, how much capacity we’re expecting to be installed.

And that’s not based on like estimates, that’s based on actual pipeline of turbines. And so we know in markets like the United States or Brazil, where, there’s reasonably good detailed publication of those turbine sizes, we, we’ve built out that, that pipeline. But what we then needed to do was determine, all right, how many of those units are going to be online within the next, 10 years or so?

What’s the, most importantly, what are the top kind of failure modes? And then what’s the probability and, and kind of the annual failure rate for each one of those type of failure modes on the turbine as a whole. And then we started looking at blades in particular because it, as it turns out, most people will recall either anecdotally or through some previously published information that gearboxes were probably the most expensive.

Item in terms of downtime that you could have on a smaller turbine. But as we go bigger the gearboxes and generators have actually become more slightly more reliable. You still have, your, your periodic faults and failures. But they’ve developed a lot of technology through either modularization or other up tower cranes and things like that that allow you to service gearboxes, generators, etc.

in situ. Blades, if you’ve got a major issue, you probably still need to take it down. And that can either involve a single blade swap kind of, crane mechanism or a big crane. And it’s basically all that said, what’s happening now with bigger turbines is the bigger the turbines go, the The more cost is involved because of the amount of repair time and the crane cost associated with undertaking that type of repair.

So as compared to gearboxes or generators or pitch systems and, and maybe main bearings that used to be like the, the biggest causes of, O& M expense and, and the biggest impact on downtime. Blades are now kind of, unfortunately, taking the, the lead. And I guess right up your alley, lightning is probably still, like, one of the number one causes of both minor repairs and major.

Repairs and replacements.

Allen Hall: Yeah, so we’re seeing the, the common faults that existed on the one and a half megawatt machines and two megawatt machines when they move up to three and four megawatt machines. They didn’t always require a crane. Pretty much when you get to three megawatts, four megawatts, you’re going to require a crane from most of the, the major items.

Any sort of trailing edge bond line on the back end to lightning damage to any, anything internal. Boy, it just seems like there’s a real risk reward to using a larger turbine at the minute. And, and that’s where I think this data is very interesting because we, we are moving away from the one megawatt machines.

We obviously we’re kind of the one and a half to two range at the moment. Right. And then we’re going to be in the threes. What does that mean in terms of operational costs? What do we need to be planning for here? Do we need to be ordering more cranes? Do we need to have other plans

Philip Totaro: to deal with this? So there’s a couple of things at play here.

One is Besides lightning damage, one of the number one expenditures that you’re going to have is actually been a fatigue failure in the route. That’s again, according to the data we’ve got, as far as the probability of occurrence and, and the annual failure rate, that’s one of the highest impact repairs that you’re going to have.

Again, besides lightning damage and followed closely by transportation damage, which, unfortunately, transportation damage is just kind of part of the cost of doing business, so to speak. But it can, it can vary. You can get to site and notice that you’ve got a few little things, maybe in the chips in the top coat that you just need to fix, or you could actually have some some severe issues with leading or trailing edge cracking or other things, you might get to site and notice that you’ve got some, missing parts or, or things like that.

Maybe they’re the the root inserts weren’t weren’t aligned perfectly correctly or, or something like that, when you go and try to install. So. There’s all kinds of things that, that can, have an impact here, but those are, those are probably the, the top issues you’ve got.

And then, you’ve, you’ve still got, while it’s infrequent, a full separation of the blade is probably the, the number five thing that happens in terms of total cost impact. So we’re looking at just for the U. S. market, by the way this year, it’s about 2. 5 billion in blade repairs that we’re anticipating are going to be necessary.

By 2030, we’re talking about 3 billion. And by, we, we only did our projection out about 10 years, but by, within 10 years, it’s going to be around 3. 3 billion. And that’s assuming that you have turbines that have no service lift. For turbines with a service lift, thankfully and since most, three, four, five, six megawatt turbines are gonna be installed that way from, from now on We’re looking at, anywhere from about two and a quarter billion up to, maybe three billion within ten years.

So, whether you’ve got a service lift or not, we’re talking, close to three billion dollars in, in a blade repair market alone that is Going to need to be serviced and those costs are continuing to inch up. So the other aspect of this that, that you asked about was regarding the growth in turbine size and, and power rating.

And what we’re noticing is that it’s not necessarily reducing the. The frequency of occurrence and the annual failure rate for specific failure modes. You’re still seeing lightning damage. In fact, with longer rotors, you may we don’t have enough data, unfortunately, because there’s not enough turbines out there, but you may actually see an increase in lightning damage as a result of longer blades.

So the reality of this is these, we’re kind of considering these estimates to be a bit conservative at this point. And we’re, we’re looking at a scenario where as turbines are getting bigger, Yes, you get more power out of it but you also get a higher impact on your downtime because for a single turbine going down, you’re not only talking about the repair cost and time you’re also talking about the, the loss of production.

And with that much of a, of an impact on lost production, it’s actually just as financially impactful to the asset owner. Because keep in mind that when we calculate these repair costs and the numbers I’ve just quoted, that’s literally only the, the actual cost of repairs. That’s not even taking into account the downtime which we will be kind of factoring into this.

When we kind of expand on this analysis later, later this year we want to be able to get down to a point where we can see what that impact is going to be on, on owners depending on the, the frequency of occurrence and regional distribution and all that, that sort of thing.

Allen Hall: So what I have seen from the field is as operators have chosen larger turbines, it seems great, right?

There’s less wires in the ground, fewer pads. Concrete everything adds up on that side, right? So it’s just less stuff, but what I’m seeing on the blade side is blades are newer less service history Transportation tends to be more of a problem You see more blade damage from transporting and lifting because of the blades have just gotten bigger and they’re harder to manage On top of that the the unknowns are still there, right?

so instead of We don’t have a good understanding, in some cases, in the early in the design phase of some of the twisting moments and, and the weird things you see out in the field. So you just experience it once they get out there. So instead of having a one and a half megawatt machine in which you have a proven service history, you get it up with this new big massive blade out there.

And what I’m seeing is that the failure rates go up. Not down. So the, the history we have with smaller blades seems to stop with those smaller plates. That’s not, you’re not having a, like a 3 percent failure rate doesn’t seem to be steady across platforms. What seems to be happening as the platforms get larger, the failure rates go up.

So even though you’re putting in fewer turbines, you’re, you’re still working against the failure rate going up. So you’re still roughly losing, you’re losing more power out of the farm than you were previously by having larger turbines is what it So is there really a savings? And this is where I want to get to folks.

I think this is the interesting piece to the analysis is, is it actually less expensive to put more turbines in of a lesser

Philip Totaro: power rating? If the availability is better and the reliability of the components is better, then yes. And, but here’s the thing, here’s the catch on why everybody wants a bigger turbine is because it’s necessarily a bit lower upfront CapEx.

It can, it can lower the, like you said, it’s a fewer number of pads, fewer electrical connections, et cetera. So everybody thinks about it in terms of, Oh, I’ve got to finance this, this project. And we’ve got to reduce the upfront CapEx as much as possible. So how can we do that? Well, let’s get the biggest turbines we can get.

And that’s the mentality. That’s what’s being, so basically what’s happening is developers and. The asset owners that they’re, if they’re doing a build and transfer a business model the asset owners and the developers who originally built the projects, they aren’t necessarily taking into account this total cost of ownership.

They’re assuming that, certain fault and failure rates that are underestimating what we’re actually seeing. And what it’s resulting in is actually bigger losses because of all the things we just talked about, what you’re seeing in the field and what we’re seeing from data.

Allen Hall: So the end of store data becomes really critical here because if you’re making those decisions, you need to understand a craneless repair versus a crane repair.

And the fact that it multiplies it times a hundred, a lot of cases on the cost and then the business interruption and all the other things that come with it. There is a real trade off here. We are crossing this threshold, which you guys are identifying of size versus quantity, right? That’s what it is.

Bigger size or more quantity. You need to pick one. The data, we don’t have a lot of data yet, and this is where I think the end of store data becomes really critical to the decision process, right?

Philip Totaro: Well, we hope so. And, and look, we’re, we’ve built this based on a data set that’s been collected from various independent power producers ISPs, and some academic research papers.

But we need more. And so this is a call to action, and frankly, an opportunity for asset owners and operators will pay you royalties for access to some of this information. You don’t have to give us like necessarily site specific data. We would certainly prefer to have turbine specific data so that we could identify which OEMs are really kind of, or which products are really the, the red headed stepchild, if you will, of the, the product family.

But we need to be able to quantify it. I think a lot of people know, kind of anecdotally, it gets talked about, texts from different sites talk to each other, Oh, this thing’s a big pain in the butt. That thing’s not, but You know that we need to quantify it and and in quantifying it at the end of the day, the reason that we do what we do with all this data is we’re trying to tell a story and we’re trying to attract investors to this industry.

Okay, we’ve got a good story to tell. Despite the fact that we’re going to have this, this O and M challenge, we’ve got a really good story to tell in terms of cost of energy in terms of, greening the electric system there, there’s a great story to tell here, but we need data to be able to convince people that we’ve got, a place where they can feel confident in parking their money.

The more data we can get our hands on in terms of fault and failure rates, in terms of, time it takes to do a particular type of repair, which, frankly speaking, It doesn’t necessarily have to be that sensitive, okay? It’s, we’re, we’re just trying to, come up with the best estimates that we can so that we can all work together to try and attract more investment to this industry.

That’s ultimately what we need to be able to do, and, and having the data at our disposal as an industry to be able to tell that story is absolutely essential.

Allen Hall: Does this help us better understand where the next plateau of wind turbine sizes will be? Like GE and Vestas have done offshore at 15 megawatts, is there going to be a data point crossing where you say, All right, 3 megawatts is as far as we should go onshore because it is the most efficient machine we’re going to be able to build and transport and install and maintain today.

Anything bigger than that is going to be trouble. For Doesn’t that data lead us to that kind of decision matrix and also in terms of PPAs? Because the PPA market is a sort of a fixed market out there And if you know what that sort of ballpark cap is for PPAs You’re really trying to keep your costs well underneath those PPAs ideally

Philip Totaro: that’s going to have a decision matrix too, right?

Well, and keep in mind something that we’ve been analyzing recently, which was If you’ve got a PPA that’s below what you’re getting for production tax credit revenue, so basically if your PPA is below, like, let’s say 26 a megawatt hour or, 26. 80 or whatever it’s indexed to these days, if you’ve got a PPA below what you’re getting for PTC revenue, you are absolutely dependent not only on the PTC revenue, but you are absolutely dependent on high availability.

If you do not have high availability, you’ve got a big problem, a revenue problem, and you’re not only going to have to repower, but you’re probably going to have to repower with refinancing a substantial portion of your project site. In that repowering cost any residual value that you haven’t already paid off from the original project, you got to carry that over if you’re debt refinancing your project or whatever you’re doing you’re, you’re going to have a certain amount of, of money left over that you’re going to have to include in, in that refinance.

The more you can pay that down, the faster it, which again, translates back to high availability. The, the faster you can generate revenue on your project, the faster you can reduce the residual value of your project down to a point where you’ve, you’ve broken even and you’re seeing a net positive return on capital that is essential in terms of financial health and, and portfolio viability.

The good news is we’re seeing merchant market prices trend back up there around, 35 to 40 this year. But, going back a few years, I mean, you were seeing power purchase contracts in the U. S. market get executed down like 10, 11, 12 for, for some projects. Now they might have only been like a three or five year duration on that On that PPA, but it’s still a problem, like you, if you’re not going to be able to then transition into a merchant market, if you’re going back to these, power off takers that are only going to pay you like 15 bucks a megawatt hour, you have to be on top of your availability.

Because availability equals PTC revenue equals financial viability of your project. And that’s

Allen Hall: where the IntelStor data comes in, right? Because IntelStor has done the analysis in all the wind farms in the United States to look at availability, which then goes to how the turbines are maintained, the type of turbine that is installed, all those little variables that do produce an availability number.

In a store has, you can go back and look and say, well, this turban did really well in this part of the country because they’re using this type of maintenance scheme. Maybe I want to repeat that because I know what my output will be at the end of the day. Well, my payback

Philip Totaro: time will be right. Absolutely.

And this goes back to what I just talked about. We’re trying to tell a story about. If there’s a particular asset owner or operator that’s doing a really good job and has a really financially healthy portfolio, that’s the kind of, place that investors want to be able to park their money.

That’s the type of, the people who originally developed that project. They’re going to get, an easier time of it, trying to go get financing. The people who are owning and operating those projects are going to have an easier time of it going and getting financing. And it’s largely down to the fact that they’ve taken things like this O& M challenge seriously.

They, they’ve recognized the fact that we’re seeing these issues and they’re getting on top of it by being proactive with their maintenance. Because of, again, all these things we just talked about, you need high availability, you need to reduce your OpEx cost, you need to reduce the frequency with which things fail, and you need to be able to detect that something’s going to fail earlier, so that before you need to call out a crane, you can, you can address it, and you won’t have that that escalation of cost that you necessarily see.

Thank you. So this was, I mean, look, I’ll go back to when we had our IntelStor event the O and M in San Diego, back in February, there was an independent power producer who was there that specifically asked for this. They, they wanted to know how much, we’ve got a finite amount of, of budget to spend, how much can we realistically.

Get out of, addressing all the things that were like a cat 4, cat 5 damage on, on the blade that we have to address to be able to get it back up and running. But going down into things that were maybe cat 2 or cat 3. Should we really put off doing the maintenance on those or are we going to get to a point where we’re going to incur a substantially increased cost later because we’re going to have more crane callouts than we would otherwise have?

And anytime you can reduce crane time, everybody already knows inherently that’s, that’s critical. And I

Allen Hall: think this data from what I’ve reviewed of it drives you to some questions about continuous monitoring systems. very much. And other types of systems just to, to keep your turbine from, and that could be technicians having more touch time with the lifts inside the turbines where you can get up and down and take a quick look like, like blade bolts seems to be a big issue, pitch bearings, big issue, right?

That seems to be industry wide. You, you have to stay on top of these things where before, I think, five years ago, ten years ago, you weren’t as on top of them, you didn’t need to monitor them, your farms were smaller even, and now that we kind of crossed this threshold, we’re like, Sunzea, which is, I don’t know how many turbines, 650 turbines or something like that.

Those numbers are massive. There’s no way you’re gonna be able to monitor all those turbines. Doesn’t that, with the, especially with the data you have, and the failure rates, and the projections forward, doesn’t that really force your hand into some sort of continuous monitoring systems so that you can then keep track of what your failure rates are and get ahead of some of these maintenance items.

Philip Totaro: The good news is that the reason that condition monitoring had such a hard time getting adopted with smaller turbines was because of As a percentage of cost of the overall turbine capex, a condition monitoring system was just too expensive. But the technology’s improved, the cost per kind of installed megawatt, shall we say, has come down a little bit.

Over the years based on just economies of scale with deploying more CMS systems. But as turbines get bigger, you can more sort of easily afford I’ll, I’ll say a full kind of condition monitoring system. If you’re getting up to the point where you have a four, five, six megawatt turbine, you’re almost going to want this because you also frankly, whether you’ve got a service lift or not, if you can avoid sending a tech up tower, That right there is, or multiple techs up tower, that right there is saving you, potentially thousands if not millions of dollars across your entire fleet during the course of a year.

If, if we go back to the data we just calculated, Cost Delta between for just for blade repairs for if you assume nobody’s got a service lift versus there’s 100 percent service lift adoption, it’s a diff it’s a difference of 300 million just in the time that techs are taking to climb towers. And that’s, again, that’s just for blade repairs.

We haven’t even done the math on, pitch systems, main shafts. Gearboxes, generators, converters, et cetera. Everything else that might necessitate having a tech go up tower. So, not, we’re, we’re not necessarily doing a, an advertisement for, the service lift companies, but, if I’m, if I’m the sales guy at a service lift company, I should expect my phone to be off the hook at this point.

Allen Hall: Yeah, I would imagine. So the, the IntelStor data is pointing everybody in the right direction. And I think the industry is starting to wake up to what, what data IntelStor has and the power it has and the advantage it gives you going forward, particularly as we build out more turbines across the United States and all over the world.

This data becomes important in the decision making process. So, Phil, how do people get ahold of you and check out IntelStor’s data?

Philip Totaro: They can visit our website, www. intelstor. com, intelstor.com/contact. You can reach out to me on LinkedIn, any way you can get in touch. We’re always happy to have a conversation, and we’d love to be able to help you.

https://weatherguardwind.com/intelstor-wind-turbine-blade-om-cost/

Renewable Energy

Wind Industry Operations: In Wind’s Next Chapter, Operations take center stage

Published

6 hours ago

February 26, 2026

Alice Rush

Weather Guard Lightning Tech

Wind Industry Operations: In Wind’s Next Chapter, Operations take center stage

This exclusive article originally appeared in PES Wind 4 – 2025 with the title, Operations take center stage in wind’s next chapter. It was written by Allen Hall and other members of the WeatherGuard Lightning Tech team.

As aging fleets, shrinking margins, and new policies reshape the wind sector, wind energy operations are in the spotlight. The industry’s next chapter will be defined not by capacity growth, but by operational excellence, where integrated, predictive maintenance turns data into decisions and reliability into profit.

Wind farm operations are undergoing a fundamental transformation. After hosting hundreds of conversations on the Uptime Wind Energy Podcast, I’ve witnessed a clear pattern: the most successful operators are abandoning reactive maintenance in favor of integrated, predictive strategies. This shift isn’t just about adopting new technologies; it’s about fundamentally rethinking how we manage aging assets in an era of tightening margins and expanding responsibilities.

The evidence was overwhelming at this year’s SkySpecs Customer Forum, where representatives from over 75% of US installed wind capacity gathered to share experiences and strategies. The consensus was clear: those who integrate monitoring, inspection, and repair into a cohesive operational strategy are achieving dramatic improvements in reliability and profitability.

Takeaway: These options have been available to wind energy operations for years; now, adoption is critical.

Why traditional approaches to wind farm operations are failing

Today’s wind operators face an unprecedented convergence of challenges. Fleets installed during the 2010-2015 boom are aging in unexpected ways, revealing design vulnerabilities no one anticipated. Meanwhile, the support infrastructure is crumbling; spare parts have become scarce, OEM support is limited, and insurance companies are tightening coverage just when operators need them most.

The situation is particularly acute following recent policy changes. The One Big Beautiful Bill in the United States has fundamentally altered the economic landscape. PTC farming is no longer viable; turbines must run longer and more reliably than ever before. Engineering teams, already stretched thin, are being asked to manage not just wind assets but solar and battery storage as well. The old playbook simply doesn’t work anymore.

Consider the scope of just one challenge: polyester blade failures. During our podcast conversation with Edo Kuipers of We4Ce, we learned that an estimated 30,000 to 40,000 blades worldwide are experiencing root bushing issues. ‘After a while, blades are simply flying off,’ Kuipers explained. The financial impact of a single blade failure can exceed €300,000 when you factor in replacement costs, lost production, and crane mobilization. Yet innovative repair solutions, like the one developed by We4Ce and CNC Onsite, can address the same problem for €40,000 if caught early. This pattern repeats across every major component. Gearbox failures that once required complete replacement can now be predicted months in advance. Lightning damage that previously caused catastrophic failures can be prevented with inexpensive upgrades and real-time monitoring. All these solutions are based on the principle that predicted maintenance is better than an expensive surprise.

Seeing problems before they happeny, and potential risks

The transformation begins with visibility. Modern monitoring systems reveal problems that traditional methods miss entirely. Eric van Genuchten of Sensing360 shared an eye-opening statistic on our podcast: ‘In planetary gearbox failures, they get 90%, so there’s still 10% of failures they cannot detect.’ That missing 10% represents the catastrophic failures that destroy budgets and production targets. Advanced monitoring technologies are filling these gaps. Sensing360’s fiber optic sensors, for example, detect minute deformations in steel components, revealing load imbalances and fatigue progression invisible to traditional monitoring. ‘We integrate our sensors in steel and make rotating equipment smarter,’ van Genuchten explained.

Other companies are deploying acoustic systems to identify blade delamination, oil analysis for gearbox health, and electrical signature analysis for generator issues. Each technology adds a piece to the puzzle, but the real value comes from integration. The impact of load monitoring alone can be transformative.

As van Genuchten explained, ‘Twenty percent more loading on a gearbox or on a bearing is half of your life. The other way around, twenty percent less loading is double your life.’ With proper monitoring, operators can optimize load distribution across their fleet, extending component life while maximizing production.

But monitoring without action is just expensive data collection. The most successful operators are those who’ve learned to translate sensor data into operational decisions. This requires not just technology but organizational change, breaking down silos between monitoring, maintenance, and management teams.

In Wind Energy Operations, Early intervention makes the million-dollar difference

The economics of early intervention are compelling across every component type. The blade root bushing example from We4Ce illustrates this perfectly. With their solution, early detection means replacing just 24-30 bushings in about 24 hours of drilling work. Wait, and you’re looking at 60+ bushings and 60 hours of work. Early detection doesn’t just prevent catastrophic failure; it makes repairs faster, cheaper, and more reliable.

This principle extends throughout the turbine. Early-stage bearing damage can be addressed through targeted lubrication or minor adjustments. Incipient electrical issues can be resolved with cleaning or connection tightening. Small blade surface cracks can be repaired in a few hours before they propagate into structural damage requiring weeks of work.

Leading operators are implementing tiered response protocols based on monitoring data. Critical issues trigger immediate intervention. Developing problems are scheduled for the next maintenance window. Minor issues are monitored and addressed during routine service. This systematic approach reduces both emergency repairs and unnecessary maintenance, optimizing resource allocation across the fleet.

Turning information into action

While monitoring generates data, platforms like SkySpecs’ Horizon transform that data into operational intelligence. Josh Goryl, SkySpecs’ Chief Revenue Officer, explained their evolution at the recent Customer Forum: ‘I think where we can help our customers is getting all that data into one place.

The game-changer is integration across data types. The company is working to combine performance data with CMS data to provide valuable insights into turbine health. This approach has been informed by operators across the world, who’ve discovered that integrated platforms deliver insights that siloed data can’t.

The platform approach also addresses the reality of shrinking engineering teams managing expanding portfolios. As Goryl noted, many wind engineers are now responsible for solar and battery storage assets as well. One platform managing multiple technologies through a unified interface becomes essential for operational efficiency.

The Integration Imperative for Wind Farm Operations

The most successful operators aren’t just adopting individual technologies; they’re integrating monitoring, inspection, and repair into a seamless operational system. This integration operates at multiple levels.

At the technical level, data from various monitoring systems feeds into unified platforms that provide comprehensive asset visibility. These platforms don’t just display data; they analyze patterns, predict failures, and generate work orders.

At the organizational level, integration means breaking down barriers between departments. This cross-functional collaboration transforms O&M from a cost center into a value driver. Building your improvement roadmap For operators ready to enhance their O&M approach, the path forward involves several key steps:

Assessing the Current State of your Wind Energy Operations

Document your maintenance costs, failure rates, and downtime patterns. Identify which problems consume the most resources and which assets are most critical to your wind farm operations.

Start with targeted pilots Rather than attempting wholesale transformation, begin with focused initiatives targeting your biggest pain points. Whether it’s blade monitoring, gearbox sensors, or repair innovations, starting with your largest issue will help you see the biggest benefit.

• Invest in integration, not just technology: the most sophisticated monitoring system is worthless if its data isn’t acted upon. Ensure your organization has the processes and culture to transform data into decisions – this is the first step to profitability in your wind farm operations.

Build partnerships, not just contracts: look for technology providers and service companies willing to share knowledge, not just deliver services. The goal is building capability, not dependency.

• Measure and iterate: track the impact of each initiative on your key performance indicators. Use lessons learned to refine your approach and guide future investments.

The competitive advantage

The wind industry has reached an inflection point. With increasingly large and complex turbines, monitoring needs to adapt with it. The era of flying blind is over.

In an industry where margins continue to compress and competition intensifies, operational excellence has become a key differentiator. Those who master the integration of monitoring, inspection, and repair will thrive. Those who cling to reactive maintenance face escalating costs and declining competitiveness.

The technology exists. The business case is proven. The early adopters are already reaping the benefits. The question isn’t whether to transform your O&M approach, but how quickly you can adapt to this new reality. In the race to operational excellence, the winners will be those who act decisively to embrace the efficiency revolution reshaping wind operations.

Unless otherwise noted, images here are from We4C Rotorblade Specialist.

Wind Industry Operations: In Wind's Next Chapter, Operations take center stage

Contact us for help understanding your lightning damage, future risks, and how to get more uptime from your equipment.

Download the full article from PES Wind here

Find a practical guide to solving lightning problems and filing better insurance claims here

Wind Industry Operations: In Wind’s Next Chapter, Operations take center stage

Renewable Energy

BladeBUG Tackles Serial Blade Defects with Robotics

Published

9 hours ago

February 26, 2026

Alice Rush

Weather Guard Lightning Tech

BladeBUG Tackles Serial Blade Defects with Robotics

Chris Cieslak, CEO of BladeBug, joins the show to discuss how their walking robot is making ultrasonic blade inspections faster and more accessible. They cover new horizontal scanning capabilities for lay down yards, blade root inspections for bushing defects, and plans to expand into North America in 2026.

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Welcome to Uptime Spotlight, shining Light on Wind. Energy’s brightest innovators. This is the Progress Powering Tomorrow.

Allen Hall: Chris, welcome back to the show.

Chris Cieslak: It’s great to be back. Thank you very much for having me on again.

Allen Hall: It’s great to see you in person, and a lot has been happening at Blade Bugs since the last time I saw Blade Bug in person. Yeah, the robot. It looks a lot different and it has really new capabilities.

Chris Cieslak: So we’ve continued to develop our ultrasonic, non-destructive testing capabilities of the blade bug robot.

Um, but what we’ve now added to its capabilities is to do horizontal blade scans as well. So we’re able to do blades that are in lay down yards or blades that have come down for inspections as well as up tower. So we can do up tower, down tower inspections. We’re trying to capture. I guess the opportunity to inspect blades after transportation when they get delivered to site, to look [00:01:00] for any transport damage or anything that might have been missed in the factory inspections.

And then we can do subsequent installation inspections as well to make sure there’s no mishandling damage on those blades. So yeah, we’ve been just refining what we can do with the NDT side of things and improving its capabilities

Joel Saxum: was that need driven from like market response and people say, Hey, we need, we need.

We like the blade blood product. We like what you’re doing, but we need it here. Or do you guys just say like, Hey, this is the next, this is the next thing we can do. Why not?

Chris Cieslak: It was very much market response. We had a lot of inquiries this year from, um, OEMs, blade manufacturers across the board with issues within their blades that need to be inspected on the ground, up the tap, any which way they can.

There there was no, um, rhyme or reason, which was better, but the fact that he wanted to improve the ability of it horizontally has led the. Sort of modifications that you’ve seen and now we’re doing like down tower, right? Blade scans. Yeah. A really fast breed. So

Joel Saxum: I think the, the important thing there is too is that because of the way the robot is built [00:02:00] now, when you see NDT in a factory, it’s this robot rolls along this perfectly flat concrete floor and it does this and it does that.

But the way the robot is built, if a blade is sitting in a chair trailing edge up, or if it’s flap wise, any which way the robot can adapt to, right? And the idea is. We, we looked at it today and kind of the new cage and the new things you have around it with all the different encoders and for the heads and everything is you can collect data however is needed.

If it’s rasterized, if there’s a vector, if there’s a line, if we go down a bond line, if we need to scan a two foot wide path down the middle of the top of the spa cap, we can do all those different things and all kinds of orientations. That’s a fantastic capability.

Chris Cieslak: Yeah, absolutely. And it, that’s again for the market needs.

So we are able to scan maybe a meter wide in one sort of cord wise. Pass of that probe whilst walking in the span-wise direction. So we’re able to do that raster scan at various spacing. So if you’ve got a defect that you wanna find that maximum 20 mil, we’ll just have a 20 mil step [00:03:00] size between each scan.

If you’ve got a bigger tolerance, we can have 50 mil, a hundred mil it, it’s so tuneable and it removes any of the variability that you get from a human to human operator doing that scanning. And this is all about. Repeatable, consistent high quality data that you can then use to make real informed decisions about the state of those blades and act upon it.

So this is not about, um, an alternative to humans. It’s just a better, it’s just an evolution of how humans do it. We can just do it really quick and it’s probably, we, we say it’s like six times faster than a human, but actually we’re 10 times faster. We don’t need to do any of the mapping out of the blade, but it’s all encoded all that data.

We know where the robot is as we walk. That’s all captured. And then you end up with really. Consistent data. It doesn’t matter who’s operating a robot, the robot will have those settings preset and you just walk down the blade, get that data, and then our subject matter experts, they’re offline, you know, they are in their offices, warm, cozy offices, reviewing data from multiple sources of robots.

And it’s about, you know, improving that [00:04:00] efficiency of getting that report out to the customer and letting ’em know what’s wrong with their blades, actually,

Allen Hall: because that’s always been the drawback of, with NDT. Is that I think the engineers have always wanted to go do it. There’s been crush core transportation damage, which is sometimes hard to see.

You can maybe see a little bit of a wobble on the blade service, but you’re not sure what’s underneath. Bond line’s always an issue for engineering, but the cost to take a person, fly them out to look at a spot on a blade is really expensive, especially someone who is qualified. Yeah, so the, the difference now with play bug is you can have the technology to do the scan.

Much faster and do a lot of blades, which is what the de market demand is right now to do a lot of blades simultaneously and get the same level of data by the review, by the same expert just sitting somewhere else.

Chris Cieslak: Absolutely.

Joel Saxum: I think that the quality of data is a, it’s something to touch on here because when you send someone out to the field, it’s like if, if, if I go, if I go to the wall here and you go to the wall here and we both take a paintbrush, we paint a little bit [00:05:00] different, you’re probably gonna be better.

You’re gonna be able to reach higher spots than I can.

Allen Hall: This is true.

Joel Saxum: That’s true. It’s the same thing with like an NDT process. Now you’re taking the variability of the technician out of it as well. So the data quality collection at the source, that’s what played bug ducts.

Allen Hall: Yeah,

Joel Saxum: that’s the robotic processes.

That is making sure that if I scan this, whatever it may be, LM 48.7 and I do another one and another one and another one, I’m gonna get a consistent set of quality data and then it’s goes to analysis. We can make real decisions off.

Allen Hall: Well, I, I think in today’s world now, especially with transportation damage and warranties, that they’re trying to pick up a lot of things at two years in that they could have picked up free installation.

Yeah. Or lifting of the blades. That world is changing very rapidly. I think a lot of operators are getting smarter about this, but they haven’t thought about where do we go find the tool.

Speaker: Yeah.

Allen Hall: And, and I know Joel knows that, Hey, it, it’s Chris at Blade Bug. You need to call him and get to the technology.

But I think for a lot of [00:06:00] operators around the world, they haven’t thought about the cost They’re paying the warranty costs, they’re paying the insurance costs they’re paying because they don’t have the set of data. And it’s not tremendously expensive to go do. But now the capability is here. What is the market saying?

Is it, is it coming back to you now and saying, okay, let’s go. We gotta, we gotta mobilize. We need 10 of these blade bugs out here to go, go take a scan. Where, where, where are we at today?

Chris Cieslak: We’ve hads. Validation this year that this is needed. And it’s a case of we just need to be around for when they come back round for that because the, the issues that we’re looking for, you know, it solves the problem of these new big 80 a hundred meter plus blades that have issues, which shouldn’t.

Frankly exist like process manufacturer issues, but they are there. They need to be investigated. If you’re an asset only, you wanna know that. Do I have a blade that’s likely to fail compared to one which is, which is okay? And sort of focus on that and not essentially remove any uncertainty or worry that you have about your assets.

’cause you can see other [00:07:00] turbine blades falling. Um, so we are trying to solve that problem. But at the same time, end of warranty claims, if you’re gonna be taken over these blades and doing the maintenance yourself, you wanna know that what you are being given. It hasn’t gotten any nasties lurking inside that’s gonna bite you.

Joel Saxum: Yeah.

Chris Cieslak: Very expensively in a few years down the line. And so you wanna be able to, you know, tick a box, go, actually these are fine. Well actually these are problems. I, you need to give me some money so I can perform remedial work on these blades. And then you end of life, you know, how hard have they lived?

Can you do an assessment to go, actually you can sweat these assets for longer. So we, we kind of see ourselves being, you know, useful right now for the new blades, but actually throughout the value chain of a life of a blade. People need to start seeing that NDT ultrasonic being one of them. We are working on other forms of NDT as well, but there are ways of using it to just really remove a lot of uncertainty and potential risk for that.

You’re gonna end up paying through the, you know, through the, the roof wall because you’ve underestimated something or you’ve missed something, which you could have captured with a, with a quick inspection.

Joel Saxum: To [00:08:00] me, NDT has been floating around there, but it just hasn’t been as accessible or easy. The knowledge hasn’t been there about it, but the what it can do for an operator.

In de-risking their fleet is amazing. They just need to understand it and know it. But you guys with the robotic technology to me, are bringing NDT to the masses

Chris Cieslak: Yeah.

Joel Saxum: In a way that hasn’t been able to be done, done before

Chris Cieslak: that. And that that’s, we, we are trying to really just be able to roll it out at a way that you’re not limited to those limited experts in the composite NDT world.

So we wanna work with them, with the C-N-C-C-I-C NDTs of this world because they are the expertise in composite. So being able to interpret those, those scams. Is not a quick thing to become proficient at. So we are like, okay, let’s work with these people, but let’s give them the best quality data, consistent data that we possibly can and let’s remove those barriers of those limited people so we can roll it out to the masses.

Yeah, and we are that sort of next level of information where it isn’t just seen as like a nice to have, it’s like an essential to have, but just how [00:09:00] we see it now. It’s not NDT is no longer like, it’s the last thing that we would look at. It should be just part of the drones. It should inspection, be part of the internal crawlers regimes.

Yeah, it’s just part of it. ’cause there isn’t one type of inspection that ticks all the boxes. There isn’t silver bullet of NDT. And so it’s just making sure that you use the right system for the right inspection type. And so it’s complementary to drones, it’s complimentary to the internal drones, uh, crawlers.

It’s just the next level to give you certainty. Remove any, you know, if you see something indicated on a a on a photograph. That doesn’t tell you the true picture of what’s going on with the structure. So this is really about, okay, I’ve got an indication of something there. Let’s find out what that really is.

And then with that information you can go, right, I know a repair schedule is gonna take this long. The downtime of that turbine’s gonna be this long and you can plan it in. ’cause everyone’s already got limited budgets, which I think why NDT hasn’t taken off as it should have done because nobody’s got money for more inspections.

Right. Even though there is a money saving to be had long term, everyone is fighting [00:10:00] fires and you know, they’ve really got a limited inspection budget. Drone prices or drone inspections have come down. It’s sort, sort of rise to the bottom. But with that next value add to really add certainty to what you’re trying to inspect without, you know, you go to do a day repair and it ends up being three months or something like, well

Allen Hall: that’s the lightning,

Joel Saxum: right?

Allen Hall: Yeah. Lightning is the, the one case where every time you start to scarf. The exterior of the blade, you’re not sure how deep that’s going and how expensive it is. Yeah, and it always amazes me when we talk to a customer and they’re started like, well, you know, it’s gonna be a foot wide scarf, and now we’re into 10 meters and now we’re on the inside.

Yeah. And the outside. Why did you not do an NDT? It seems like money well spent Yeah. To do, especially if you have a, a quantity of them. And I think the quantity is a key now because in the US there’s 75,000 turbines worldwide, several hundred thousand turbines. The number of turbines is there. The number of problems is there.

It makes more financial sense today than ever because drone [00:11:00]information has come down on cost. And the internal rovers though expensive has also come down on cost. NDT has also come down where it’s now available to the masses. Yeah. But it has been such a mental barrier. That barrier has to go away. If we’re going going to keep blades in operation for 25, 30 years, I

Joel Saxum: mean, we’re seeing no

Allen Hall: way you can do it

Joel Saxum: otherwise.

We’re seeing serial defects. But the only way that you can inspect and or control them is with NDT now.

Allen Hall: Sure.

Joel Saxum: And if we would’ve been on this years ago, we wouldn’t have so many, what is our term? Blade liberations liberating

Chris Cieslak: blades.

Joel Saxum: Right, right.

Allen Hall: What about blade route? Can the robot get around the blade route and see for the bushings and the insert issues?

Chris Cieslak: Yeah, so the robot can, we can walk circumferentially around that blade route and we can look for issues which are affecting thousands of blades. Especially in North America. Yeah.

Allen Hall: Oh yeah.

Chris Cieslak: So that is an area that is. You know, we are lucky that we’ve got, um, a warehouse full of blade samples or route down to tip, and we were able to sort of calibrate, verify, prove everything in our facility to [00:12:00] then take out to the field because that is just, you know, NDT of bushings is great, whether it’s ultrasonic or whether we’re using like CMS, uh, type systems as well.

But we can really just say, okay, this is the area where the problem is. This needs to be resolved. And then, you know, we go to some of the companies that can resolve those issues with it. And this is really about played by being part of a group of technologies working together to give overall solutions

Allen Hall: because the robot’s not that big.

It could be taken up tower relatively easily, put on the root of the blade, told to walk around it. You gotta scan now, you know. It’s a lot easier than trying to put a technician on ropes out there for sure.

Chris Cieslak: Yeah.

Allen Hall: And the speed up it.

Joel Saxum: So let’s talk about execution then for a second. When that goes to the field from you, someone says, Chris needs some help, what does it look like?

How does it work?

Chris Cieslak: Once we get a call out, um, we’ll do a site assessment. We’ve got all our rams, everything in place. You know, we’ve been on turbines. We know the process of getting out there. We’re all GWO qualified and go to site and do their work. Um, for us, we can [00:13:00] turn up on site, unload the van, the robot is on a blade in less than an hour.

Ready to inspect? Yep. Typically half an hour. You know, if we’ve been on that same turbine a number of times, it’s somewhere just like clockwork. You know, muscle memory comes in, you’ve got all those processes down, um, and then it’s just scanning. Our robot operator just presses a button and we just watch it perform scans.

And as I said, you know, we are not necessarily the NDT experts. We obviously are very mindful of NDT and know what scans look like. But if there’s any issues, we have a styling, we dial in remote to our supplement expert, they can actually remotely take control, change the settings, parameters.

Allen Hall: Wow.

Chris Cieslak: And so they’re virtually present and that’s one of the beauties, you know, you don’t need to have people on site.

You can have our general, um, robot techs to do the work, but you still have that comfort of knowing that the data is being overlooked if need be by those experts.

Joel Saxum: The next level, um, commercial evolution would be being able to lease the kit to someone and or have ISPs do it for [00:14:00] you guys kinda globally, or what is the thought

Chris Cieslak: there?

Absolutely. So. Yeah, so we to, to really roll this out, we just wanna have people operate in the robots as if it’s like a drone. So drone inspection companies are a classic company that we see perfectly aligned with. You’ve got the sky specs of this world, you know, you’ve got drone operator, they do a scan, they can find something, put the robot up there and get that next level of information always straight away and feed that into their systems to give that insight into that customer.

Um, you know, be it an OEM who’s got a small service team, they can all be trained up. You’ve got general turbine technicians. They’ve all got G We working at height. That’s all you need to operate the bay by road, but you don’t need to have the RAA level qualified people, which are in short supply anyway.

Let them do the jobs that we are not gonna solve. They can do the big repairs we are taking away, you know, another problem for them, but giving them insights that make their job easier and more successful by removing any of those surprises when they’re gonna do that work.

Allen Hall: So what’s the plans for 2026 then?

Chris Cieslak: 2026 for us is to pick up where 2025 should have ended. [00:15:00] So we were, we were meant to be in the States. Yeah. On some projects that got postponed until 26. So it’s really, for us North America is, um, what we’re really, as you said, there’s seven, 5,000 turbines there, but there’s also a lot of, um, turbines with known issues that we can help determine which blades are affected.

And that involves blades on the ground, that involves blades, uh, that are flying. So. For us, we wanna get out to the states as soon as possible, so we’re working with some of the OEMs and, and essentially some of the asset owners.

Allen Hall: Chris, it’s so great to meet you in person and talk about the latest that’s happening.

Thank you. With Blade Bug, if people need to get ahold of you or Blade Bug, how do they do that?

Chris Cieslak: I, I would say LinkedIn is probably the best place to find myself and also Blade Bug and contact us, um, through that.

Allen Hall: Alright, great. Thanks Chris for joining us and we will see you at the next. So hopefully in America, come to America sometime.

We’d love to see you there.

Chris Cieslak: Thank you very [00:16:00] much.