Asset managers need heads in the cloud

Cloud storage is the bedrock of digital change in the global wind industry.


October 21, 2021

Cloud storage is the bedrock of digital change in the global wind industry.

If operators are to successfully deploy artificial intelligence and machine learning at their assets, they need to be able to quickly analyse huge amounts of data. That is more easily done when operators store data in powerful remote servers – i.e. ‘in the cloud’ – rather than in on-site servers. This can help to boost profits at wind farms.

But there are also challenges with skills and logistics that could undermine even the best asset management plans. That was a key focal point of the Asset Management Summit that A Word About Wind and our parent company Tamarindo Group held on 7th October, in conjunction with wind optimisation specialist Sereema.

We were joined at this one-hour online discussion by Yufan Cai, head of commercial and finance at the UK offshore wind farm London Array; Meghan Semiao, director of asset management at US wind and solar business Longroad Energy; and Jerome Imbert, founder and chief executive of Sereema.

In this article, we share some of the speakers’ views of the impacts of digital systems on asset management, as well as insights into skills gaps and supply chain issues. You can watch the recording here.

Emerging digital trends

Semiao said adopting digital asset management systems early in project life cycles could help operators to maximise their benefit.

“Being proactive in the first five years will have a greater impact on the megawatts of activity for the remaining life of the projects. It is extremely important to ensure that you’re capturing these megawatts, hitting your capacity numbers, and achieving maximum profitability,” she said.

One obstacle for operators to introduce new technologies to their projects in these early days is that making physical changes to turbines could put them in breach of their warranty periods with manufacturers. Semiao agreed this is important but said that most digital systems would not interfere with these warranties at all.

“There are a lot of asset management platforms that integrate all this big data and compress it to give the analytics you need to predict failures,” she said.

As well as helping operators to make physical improvements to assets, this information can help them in their commercial negotiations with turbine manufacturers.

But we also heard that operators could only take full advantage of ‘big data’ if they are using cloud computing systems to store information remotely away from their own servers. This can give operators more processing power and Imbert said it is fundamental for companies moving to digital asset management systems.

“With the cloud you’re able to gather big amounts of data, to store them and, when you need it, to process it in no time. That is a really dramatic change,” he said.

This power will support the emergence of artificial intelligence and machine learning systems in wind. These technologies monitor the performance and behaviour of the individual machines at projects, and compare current output to their historical output. This can help operators to identify potential problems before failures happen.

Practical challenges

Yufan said it was “very exciting” for operators to understand their assets in deeper ways, and that this should help asset managers to formulate their strategies. But she added operators could struggle to implement their strategies due to logistics issues.

She explained: “Sometimes you may find you know the strategy but, when it comes to implementation, then due to supply chain logistics or bottlenecks you are not in a position to implement the desired result. That is a situation where we can have the data and information, but we need to apply it to resolve the issue.”

One way London Array is looking to deploy technicians most effectively is by using drones for blade inspections, rather than sending individual workers. This shows technology can help operators save worker time and boost efficiency.

Semiao agreed complex machine learning is an area that operators are “starting to wrap our heads around” and that is was “extremely important” for technicians on site to have a really good idea of what is happening in the wind turbines. But she added that a shortage of skilled technicians was a significant challenge for US operators.

She also said that spare parts procurement was getting “very complicated” as the industry is seeing shortages around the world. Cloud-based systems can help show operators what they need to do, but they still need access to the right parts and skills if their plans are to survive in the real world.

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