WindTwin digital platform increases efficiency on wind farms and tests maintenance upgrades

Engineers at Brunel Innovation Centre are developing a digital platform that increases efficiency for a fraction of the cost. The virtual mission platform, WindTwin, operates as a control panel, giving live condition checks on wind farms. Data fed from sound sensors will predict upcoming repair needs, allowing maintenance to be conducted before damage is done.

Dr. Miltiadis Kourmpetis of Brunel stated that the goal was “to develop digital models or clones of a wind turbine which combine mathematical models describing the physics of the turbine’s operation, with sensor data from actual parts during day-to-day running.

 

The project utilizes digital twin technology to combine operational sensor data with virtual system model data. A sensor network system uses signal processing and condition monitoring algorithms, which are applied to the live wind turbine, to collect operational data and create a virtual replica of the turbine.

The output is processed, allowing for a multi-dimensional reading of the turbine’s behaviour and physical state during real time operations. Implementation of this technology will allow for real time data on performance and condition, thus allowing maintenance and repairs tobe made as needed, rather than being faced with extensive repairs and downtime due to issues that often go unnoticed for extended periods of time.

 

Senior Project Leader Ángela Angulo explained further. “The data to be provided by the WindTwin digital software platform has the potential to provide the wind-turbine industry with many benefits. It will enable wind-farm operators to better diagnose performance variations of the entire wind turbine asset down to its constituent individual components level; anticipate degradation and failures, and deploy condition-based maintenance instead of schedule-based strategies.”

The platform uses advanced data analytics, cloud computing, system fault and degradation modeling, and visualizations to expose the condition of the turbines with approximately 99.5 per cent reliability, ensuring proper maintenance and reducing costs by an estimated 30 per cent. Workers can monitor the condition of these turbines remotely and securely, eliminating the potential for irreparable damage. Downtime and subsequent losses will also be reduced by 70 per cent.

Angulo also stated that the WindTwin’s operators “will be able to virtually test maintenance upgrades before deployment and better control wind turbine setting, resulting in optimized wind-turbine performance and energy output.” The project’s ultimate goal is to go forward with the business plan, commercialize the platform globally, and expand into other areas that could benefit from the technology.

 

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