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Development of Low Cost Cloud Monitoring for the Diagnosis and Prognostic of the Wind Turbines

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Predictive cloud-based solution reduces wind farm maintenance costs

Being able to predict wind turbine breakdowns ensures damage limitation, better maintenance planning and reduced energy losses. The CLOUD DIAGNOSIS project has developed a modular diagnosis and prognosis cloud-based system to achieve just that.

Energy

Every year, around 3 % of wind turbines are put out of service globally due to structural failures, and this figure jumps dramatically for older wind farms to between 15 %, and even, 30 %. The main causes of failure are gearbox and generator problems, usually located in the bearings. If the industry is to remain cost-effective and profitable, there a clear incentive to improve maintenance and operational processes The EU-supported CLOUD DIAGNOSIS project was established to provide solutions for the improvement of wind farm productivity, based on fusion data coming from a range of sources, (such as SCADA, alongside various sensors). To achieve this aim, the project developed cloud-based software diagnosis and prognosis tools, to detect operational anomalies and implement preventive and corrective measures. The one of a kind modular solution The EU funding for SME projects enabled Smartive to develop its cloud based software application SmartGear. This specific solution was designed to augment the company’s wider suite for improved wind farm management: SmartCast, SmartScada and SmartBoard. The core of package is SmartCast which is designed for predictive maintenance. As it can process real time data from the turbine’s Supervisory Control and Data Acquisition (SCADA) system, it does not require the installation of additional sensors and so offers a low cost solution. The system works by monitoring potential anomalies, giving users a diagnostic identifying the problem along with a prognostic to analyse why it is happening. As project coordinator Dr Jordi Cusido further explains, “The system can detect failures in different components, with close to 94 % accuracy, well in advance of problems. Thanks to this system, wind farm operators can save around 500 000 EUR annually.” An additional advantage of this platform is its adaptability. Given that wind turbines come in a range of shapes and sizes, SmartCast is designed to be widely compatible. Its algorithms recognise and adapt to different wind turbine characteristics, making the system customisable for each wind farm. The EU-supported SmartGear product enables users to track wind turbine transmission systems – the most common area for operational failure and containing the costliest components - 24/7 via a web-based platform. Drawing on sensors installed in bearings, shafts and gears, the system undertakes precision vibration analysis, identifying vibrations which are operating outside of the normal range. The solution also offers users the option to upgrade their SCADA by integrating SmartSCADA which includes a number of features including conventional system backups, along with the generation of operational management reports. The package can be collectively displayed on the interactive dashboard known as SmartBoard, which offers real time information on the principal indicators of the wind farm, on any devices with an internet connection. As well as historical data, it also generates daily, monthly and annual forecasts for operation and budgetary management decisions. The team are now focused on fine-tuning the algorithms which underpin the work-flow but are also working to standardise protocols to ensure the best solution possible. While Smartive has its eye on the European Market in general, for now its primary target markets lie within Germany, France, the UK, Italy and Portugal. Reflecting on the success of the project, Dr Cusido says, “Using our system typically results in about a 10 % reduction in maintenance costs We have constructed a very disruptive and unique solution currently otherwise non-existent in the sector.”

Keywords

CLOUD DIAGNOSIS energy, wind farms, turbines, maintenance, algorithms, gears, monitoring, sensors, productivity, prediction, prevention

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