E!11909 Electrical Faults Diagnosis and Prognosis of Wind Turbine System Failures

Data analyzed in "The Wind Energy Operations & maintenance Report" 2014 suggest that average operations and maintenance costs of wind turbines run at approximately Euro 0.019/kWh. This may sound like a small investment, but profitable wind farms require operators to run a tight ship. The report quotes an operator saying 'Just a 1% improvement in O&M makes a huge difference on the bottom line'. From there, we can estimate that the total O&M cost (at Euro 0.019/kWh) would amount to around 3 billion Euro per year. Therefore, if the proper diagnosis and prognosis systems of wind turbines are improved only 1% in O&M, it would save around 30 million Euro per year. ElecTurSys will perform diagnosis and prognosis of electrical system failures for wind turbines. improve safety and reliability, minimise down time, lower the frequency of sudden breakdowns and associated huge maintenance and logistic costs related to wind turbines, especially to larger offshore turbines. The technology which is intended to be developed, will meet the market and legislative need for an efficient and effective predictive maintenance system that will enable lower cost of maintenance for wind turbines. We have studied the market with a view of finding proper solutions that provide all the desired technical functionalities, but no single solution exists. However, there are technologies, which can be modified and adapted and combined with newly developed system to solve the challenges

A digitalized and intelligent general-purpose condition monitor (CM) system for the wind turbine drivetrain was developed. It is an AWS cloud-based system. It includes sensors for taking high-resolution measurements and methodologies to retrieve various data types. It has a cloud-hosted database and Data processing modules implemented for detecting anomalies. A data presentation system is presented as a web dashboard for the User (Operators, Maintenance Eng., etc.) to see the data and manage maintenance logs and alarms. The system provides an opportunity for digital transformation by automating manual processes and general data analysis to detect anomalies to reduce unexpected downtime and eventually lower the maintenance cost. We plan to utilize the capabilities and systems to commercial its services to relevant industry players. In coming years, an important business area in our value chain will be renewable energy using the digitalized and intelligent CM solution.

Data analyzed in ‘The Wind Energy Operations & maintenance Report’ 2014 suggest that average operations and maintenance costs of wind turbines run at approximately €0.019/kWh. This may sound like a small investment, but profitable wind farms require operators to run a tight ship. The report quotes an operator saying “Just a 1% improvement in O&M makes a huge difference on the bottom line”. From there, we can estimate that the total O&M cost (at €0.019/kWh) would amount to around €3 billion per year. Therefore, if the proper diagnosis and prognosis systems of wind turbines are improved only 1% in O&M, it would save around €30 million per year. ElecTurSys will perform diagnosis and prognosis of electrical system failures for wind turbines. improve safety and reliability, minimise down time, lower the frequency of sudden breakdowns and associated huge maintenance and logistic costs related to wind turbines, especially to larger offshore turbines. The technology which is intended to be developed, will meet the market and legislative need for an efficient and effective condition monitoring system that will enable lower cost of maintenance for wind turbines. We have studied the market with a view of finding proper solutions that provide all the desired technical functionalities, but no single solution exists. But we found some technologies that we can adapt and combine with other technologies, and there are some technologies that could work with significant further development and hence there is a need for comprehensive development work in this field. But to do so we have the following obstacles: Difficulty in correlating incidents that happen in high frequency to faults that would happen months later. EMI effects of false signals in on the control monitoring systems can cause false trips The proposed system will generate large amounts of data for processing. So to handle and use only the relevant data properly we need to develop smart and high speed processing software.