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IBM > Case Studies > Vestas: Turning Climate into Capital with Big Data
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Vestas: Turning Climate into Capital with Big Data

 Vestas: Turning Climate into Capital with Big Data - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Big Data Analytics
Applicable Industries
  • Renewable Energy
Applicable Functions
  • Process Manufacturing
Use Cases
  • Outdoor Environmental Monitoring
The Challenge

Making wind a reliable source of energy depends greatly on the placement of the wind turbines used to produce electricity. Turbulence is a significant factor as it strains turbine components, making them more likely to fail. Vestas wanted to pinpoint the optimal location for wind turbines to maximize power generation and reduce energy costs.

The Customer
Vestas Wind Systems
About The Customer
Vestas Wind Systems is the largest manufacturer, seller, installer, and servicer of wind turbines in the world, with more than 17,000 employees globally.
The Solution

IBM InfoSphere BigInsights software running on an IBM System x iDataPlex system serves as the core infrastructure to help Vestas manage and analyze weather and location data in ways that were not previously possible. IBM InfoSphere BigInsights helps Vestas gain access to knowledge in an efficient and fast way and enables Vestas to use this knowledge to turn climate into capital. Software Components - IBM InfoSphere BigInsights software - IBM System x iDataPlex system - Apache Hadoop software

Data Collected
Asset Location, Energy Cost Per Unit, Energy Production, Power Output, Wind Speed
Operational Impact
  • [Data Management - Data Processing]
    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.
  • [Efficiency Improvement - R&D]
    Ongoing application development and improvements are relatively quick and inexpensive to implement due to the system's flexibility.
  • [Efficiency Improvement - R&D]
    Response time for wind forecasting information was reduced by approximately 97% which helped cut development time.
Quantitative Benefit
  • 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.

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