Revolutionizing Wind Turbine Maintenance: How Big Data Analytics and IoT help wind farm operators to maximize their ROI.
Ideally, a wind turbine must be ready to operate any time the wind blows. However, this is not always the case due to unexpected failures. Wind turbines consist of various moving parts and mainly operate in remote areas. Therefore, a reactive maintenance approach is very costly due to emergency repairs and decreased availability.
Big Data analytics and IoT revolutionize the maintenance approach by turning the unexpected failures into accurate predictions. Most of the faults give early signals before they lead to a breakdown. The signal can be a change in vibration or a deviation in temperature. The challenge is to capture these anomalies for each component of every wind turbine in real-time. A combination of IoT and Big Data analytics can achieve this.
A predictive maintenance strategy helps operators to avoid emergency repairs and make the most of their assets. Moreover, having a real-time health status of the turbine prevents unnecessary routine maintenance and allows operators to make better decisions related to inventory of spare parts and logistics.
This real business value of Big Data analytics and IoT is drawing attention from industry and academia. The major manufacturers of wind turbines continuously work on improving their accuracy in predictions. A variety of companies ranging from multinationals to start-ups offer solutions to digitize wind farms. New and more accurate algorithms to detect anomalies are published in academic journals.
Business Intelligence Services (BIS) Group is organizing the 4th edition Wind Power Big Data and IoT Forum on 8th and 9th of November in Berlin. The forum will allow visitors to catch up with the current status of Big Data analytics and IoT in wind power. What are the best practices? What are the cutting-edge technologies being applied in the field? What are the opinions of the experts on future developments? What further business value can be created?