WindTwin – a collaborative project to develop a high fidelity, digital software platform combining operational sensor data with virtual system model data for the predictive maintenance of wind turbines – has won R&D Programme of the Year at the Business Green Technology Awards 2017. The consortium behind the winning project comprises engineering technology experts Agility3, Brunel University London, Dashboard, ESI and TWI Ltd.
Digital twin technology for wind turbine industry wins national environmental business award
Earlier this year, the consortium successfully secured funding from Innovate UK, the Government agency behind finding and driving the innovations that will grow the UK economy, to develop the digital twin technology which is specifically for the wind turbine industry. The aim of WindTwin is to provide a solution that will help mitigate the rapidly growing maintenance and operational costs of running wind turbines, as well as support the optimisation of wind energy generation by enabling more reliable, in-service wind turbines.
Busness Green explained why WindTwin had been selected as the winner in the R&D category, saying ‘The judges were won over by the project's consortium-led research approach and the tangible progress it has made tackling the major maintenance challenges faced by the wind and other renewables industries.’
WindTwin will see the consortium members develop and integrate a number of enabling technologies including high performance cloud computing, system fault and degradation modelling, data analytics and visualisation. A sensor network system, utilising optimised signal processing and condition monitoring algorithms, will be applied to the live wind turbine to collect operational data which will then interface with a replica, virtual 3D model, or digital twin, of the wind turbine. The output data will describe the wind turbine’s multi-dimensional, dynamic behavour and physical state during real time operations.
Ángela Angulo, Senior Project Leader, Condition and Structural Health Monitoring at TWI, (pictured collecting the award on behalf of the consortium), said: ‘We are delighted to have been recognised with this award. Digital twin models will give wind turbine operators up-to-the-minute data on how their assets are performing; thereby removing the need to schedule in regular shutdown for inspection and investigation; and enabling better diagnosis of performance variations of the entire wind turbine asset down to its individual components.’ She added ‘We are excited by the opportunities digital twin technology will bring to the wind energy industry and look forward to the next phase of the project.’
TWI is a world leading research and technology organisation with a focus on materials, engineering and manufacturing.