Predicting the future to save energy
Madrid / 19 November 2020
It sounds like science fiction, but it’s not. Our team can predict the behaviour of wind turbines and prevent failures before they occur. How do they manage to do it? Thanks to mathematical models that over the last nine years have been able to detect 50,000 anomalies in wind turbines. And the result? Well, pretty incredible, with savings of over a million hours of energy.
“Whenever the data streaming from any of the 400 sensors installed in each of more than 17,000 wind turbines monitored by the system in 44 different countries – this amounts to almost 1.500 billion measurements each day – no longer fits to the model, this may indicate a problem. If this is the case, a ticket is created, asking the service technicians to investigate and address the issue,” explains Henrik Pedersen, who is in charge of model-based diagnostics at Siemens Gamesa.
The advantages of this system are immense. Firstly, problems are detected at a very early stage, making repairs easier, faster, safer and cheaper, and avoiding major complications. The time when the machine is stopped and not operating is reduced and stops can be programmed for periods with less wind, which is especially beneficial for offshore projects. By keeping turbines fit in all areas, the company can avoid wear and tear on components like electronics, valves or motors. The maintenance team's work is made easier because when the warning is generated it is already accompanied by a detailed guide with the procedure for action and the spare parts needed for the repair.
As Henrik highlights, each early detected defect represents an opportunity. By predicting the future, the 50,000 tickets generated over the last decade have saved over a million hours of energy that would otherwise have been lost.
Whenever the data streaming from any of the 400 sensors installed in each of more than 17,000 wind turbines monitored by the system– this amounts to almost 1.500 billion measurements each day – no longer fits to the model, this may indicate a problem
“As a consequence, this becomes a scheduled service on that turbine, it takes about 10 minutes to replace that, and the turbines are good to go again,” highlights Henrik. “We have become so smart that we can identify issues nobody knew about. And get them
The next objectives for Henrik’s team have already been set: having more and new sensor types installed in new turbines and use the diagnostic model to perform inspection and tests that today are performed manually by service technicians. "The opportunities provided by digitalization are massive and we at Siemens Gamesa are making the most of their potential to increase value to the customer," concludes Henrik.