“You might think pair programming would take twice as long but I think we save time by creating better solutions with fewer bugs. It’s also easier for both of us to continue working on the code when we know it as well as we do."
Thomas H. Thoresen
His pair programming pal Thibaut works in NES and tells us it’s like a dream come true to sit down with developers and work on new technology.
“We’re only 4 people in the team, but it’s really good to work together with them – and struggle with them. There’s been some challenges, but it’s in the tough times you can see if your team is good or not,” Thibaut laughs.
Wondering what it looks like when Thibaut and Thomas do a little bit of pair programming? Then watch this! (Video: Torstein Lund Eik)
Visualization is the way to go
Like most software development it’s not all sunshine and rainbows. Now, the team is in the middle of the agile sprint creating a newer version of the dashboard using Microsoft Power BI. While the team understands how the alarm predictions all work, it can be a challenge to communicate it to the operators, Thomas explains.
“To imagine that it can “predict the future” can be a little difficult if the traditional understanding is that these failures simply just happen. Then it’s our job to show how it all works and show them that it can be trusted,” he says.
He hopes to achieve this by explaining how the machine learning network works and that they’ve trained it using years of data. This will help the end user to get an intuitive relationship with it all.
“I think the way to do it is through good visualizations and by not removing information from the dashboard. We’re also working on a way to explain how the network is trained easily, so we can build trust and understanding of the tool,” Thomas explains.
After showing a minimum viable product (MVP), featuring basic usability and function, they’ve received solid feedback from their users at Dudgeon. Their suggestion was to focus on the big components of the wind turbines such as gear boxes or generators, product owner Nenad Keseric tells us.
“These gearboxes cost between 12 and 20 million NOK each and we have 88 turbines at Sheringham alone. Being able to predict failure on even a single one of them is an incredible potential,” he says.
He says that the machine learning algorithm works great as it is now and the next thing is to apply a larger data set and adapt it to bigger components.
Did you know...
That our wind farms and turbines have more than 80 000 sensors?
Getting in a predictive mode where we know what’s going to happen before it happens is alpha and omega – especially within renewable energy, Nenad explains
“The future is predicting these failures through an algorithm and thus getting a data driven operation. Then we won't need our operators checking these things manually."
It’ll be interesting to see what the winds bring us, but we’ll be sure to keep you updated! Make sure you’re subscribed to the newsletter below and you’ll get a notification as soon as there’s new stories to be read.