Vestas: Turning Climate into Capital with Big DataIBM
Construction & Buildings
Structural Health Monitoring (SHM)
Data Processing Efficiency - Processing huge volumes of climate data and the ability to gain insight from that data enables Vestas to forecast optimal turbine placement in 15 minutes instead of three weeks.
System Flexibility - Ongoing application development and improvements are relatively quick and inexpensive to implement due to the system's flexibility.
Research Efficiency - Response time for wind forecasting information was reduced by approximately 97% which helped cut development time.
Vestas reduces the base resolution of its wind data grids from a 27x27 kilometer area down to a 3x3 kilometer area, a nearly 90% reduction.
The IBM System x iDataPlex supercomputer enables the company to use 40% less energy while increasing computational power.
Implementing a big data solution enables Vestas to create a wind library to hold 18 to 24 petabytes of weather and turbine data and reduce the geographic grid area by 90% to increased accuracy.