Server farms are becoming profoundly critical to the success of wind farms—offshore and otherwise. Data scientists armed with cloud-based analytics applications and tower-based telemetry can monitor wind turbine life every minute.
Take a brief look below at why analytics—the sciences of calculation and analysis—are critical to the evolution of offshore wind power.
Data Science and Predictive Maintenance
Thanks to advances in computer science and cloud storage, wind farm operations will construct dynamic models that cross-reference and compare the impact of wind, temperature, and wear in ways that were impossible ten years ago. The major challenge of offshore wind is to reduce massive construction costs and avoid expensive equipment failures. Improvements in analytics-driven predictive maintenance would make offshore wind installations much better track when key components malfunction and repair them until a costly failure.
The rewards of this deep dive into data processing are twofold: cutting running expenses and showing device designers the best prospects for higher performance in future generations of towers and turbines. Land-based wind power is now price-competing with conventional electricity sources in many markets. Careful research would be one of the keys to allowing offshore wind turbines to reach the same degree of success.
One lab is exploring a wide variety of technologies to help offshore wind operators take advantage of advanced data science. One of their studies has shown that a floating platform can use LIDAR (light detection and range) equipment to monitor offshore wind patterns. The police essentially use the same equipment to nab speeding drivers: directing the laser beam at a certain location and tracking the motion in the area that the light beam reaches.
LIDAR is an exemplary field measuring technology, but making it operate on the water is cost-prohibitive. That is why the good test of a floating LIDAR or FLIDAR prototype a few years ago was welcome news. With analytics, wind farm operators will fold extra-precise wind calculations into their total operational models and allow much smarter forecasts about their turbines' lifetime.